Search results for: tumor segmentation

Authors: Diana Pombo, Maria Loaiza, Mauricio Quijano, Alberto Cadena, Juan Pablo Tello

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In this paper, we present a semi-automatic tool for calculating ejection fraction from an echocardiographic video signal which is derived from a database in DICOM format, of Clinica de la Costa - Barranquilla. Described in this paper are each of the steps and methods used to find the respective calculation that includes acquisition and formation of the test samples, processing and finally the calculation of the parameters to obtain the ejection fraction. Two imaging segmentation methods were compared following a methodological framework that is similar only in the initial stages of processing (process of filtering and image enhancement) and differ in the end when algorithms are implemented (Active Contour and Region Growing Algorithms). The results were compared with the measurements obtained by two different medical specialists in cardiology who calculated the ejection fraction of the study samples using the traditional method, which consists of drawing the region of interest directly from the computer using echocardiography equipment and a simple equation to calculate the desired value. The results showed that if the quality of video samples are good (i.e., after the pre-processing there is evidence of an improvement in the contrast), the values provided by the tool are substantially close to those reported by physicians; also the correlation between physicians does not vary significantly.

Keywords: echocardiography, DICOM, processing, segmentation, EDV, ESV, ejection fraction

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Authors: Manuel I. Capel, Antonio Tomeu, Alberto Salguero

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Tumor growth from a transformed cancer-cell up to a clinically apparent mass spans through a range of spatial and temporal magnitudes. Through computer simulations, Cellular Automata (CA) can accurately describe the complexity of the development of tumors. Tumor development prognosis can now be made -without making patients undergo through annoying medical examinations or painful invasive procedures- if we develop appropriate CA-based software tools. In silico testing mainly refers to Computational Biology research studies of application to clinical actions in Medicine. To establish sound computer-based models of cellular behavior, certainly reduces costs and saves precious time with respect to carrying out experiments in vitro at labs or in vivo with living cells and organisms. These aim to produce scientifically relevant results compared to traditional in vitro testing, which is slow, expensive, and does not generally have acceptable reproducibility under the same conditions. For speeding up computer simulations of cellular models, specific literature shows recent proposals based on the CA approach that include advanced techniques, such the clever use of supporting efficient data structures when modeling with deterministic stochastic cellular automata. Multiparadigm and multiscale simulation of tumor dynamics is just beginning to be developed by the concerned research community. The use of stochastic cellular automata (SCA), whose parallel programming implementations are open to yield a high computational performance, are of much interest to be explored up to their computational limits. There have been some approaches based on optimizations to advance in multiparadigm models of tumor growth, which mainly pursuit to improve performance of these models through efficient memory accesses guarantee, or considering the dynamic evolution of the memory space (grids, trees,…) that holds crucial data in simulations. In our opinion, the different optimizations mentioned above are not decisive enough to achieve the high performance computing power that cell-behavior simulation programs actually need. The possibility of using multicore and GPU parallelism as a promising multiplatform and framework to develop new programming techniques to speed-up the computation time of simulations is just starting to be explored in the few last years. This paper presents a model that incorporates parallel processing, identifying the synchronization necessary for speeding up tumor growth simulations implemented in Java and C++ programming environments. The speed up improvement that specific parallel syntactic constructs, such as executors (thread pools) in Java, are studied. The new tumor growth parallel model is proved using implementations with Java and C++ languages on two different platforms: chipset Intel core i-X and a HPC cluster of processors at our university. The parallelization of Polesczuk and Enderling model (normally used by researchers in mathematical oncology) proposed here is analyzed with respect to performance gain. We intend to apply the model and overall parallelization technique presented here to solid tumors of specific affiliation such as prostate, breast, or colon. Our final objective is to set up a multiparadigm model capable of modelling angiogenesis, or the growth inhibition induced by chemotaxis, as well as the effect of therapies based on the presence of cytotoxic/cytostatic drugs.

Keywords: cellular automaton, tumor growth model, simulation, multicore and manycore programming, parallel programming, high performance computing, speed up

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Authors: Taleb L., Benarbia M., Boutira F. M., Allam H., Boukerche A.

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Introduction and purpose of the study: Meningiomas are the most common non-glial intracranial tumors in adults, accounting for approximately 30% of all central nervous system tumors. The aim of our study is to determine the epidemiological, clinical, therapeutic, and evolutionary characteristics of a cohort of patients with intracranial meningioma treated with radiotherapy at the Emir Abdelkader Cancer Center in Oran. Material and methods: This is a retrospective study of 44 patients during the period from 2014 to 2020. The overall survival and relapse-free survival curves were calculated using the Kaplan-Meier method. Results and statistical analysis: The median age of the patients was 49 years [21-76 years] with a clear female predominance (sex ratio=2.4). The average diagnostic delay was seven months [2 to 24 months], the circumstances of the discovery of which were dominated by headaches in 54.5% of cases (n=24), visual disturbances in 40.9% (n=18), and motor disorders in 15.9% (n=7). The seat of the tumor was essentially at the level of the base of the skull in 52.3% of patients (n=23), including 29.5% (n=13) at the level of the cavernous sinus, 27.3% (n=12) at the parasagittal level and 20.5% (n=9) at the convexity. The diagnosis was confirmed surgically in 36 patients (81.8%) whose anatomopathological study returned in favor of grades I, II, and III in respectively 40.9%, 29.5%, and 11.4% of the cases. Radiotherapy was indicated postoperatively in 45.5% of patients (n=20), exclusive in 27.3% (n=12) and after tumor recurrence in 27.3% of cases (n=18). The irradiation doses delivered were as follows: 50 Gy (20.5%), 54 Gy (65.9%), and 60 Gy (13.6%). With a median follow-up of 69 months, the probabilities of relapse-free survival and overall survival at three years are 93.2% and 95.4%, respectively, whereas they are 71.2% and 80.7% at five years. Conclusion: Meningiomas are common primary brain tumors. Most often benign but can also progress aggressively. Their treatment is essentially surgical, but radiotherapy retains its place in specific situations, allowing good tumor control and overall survival.

Keywords: diagnosis, meningioma, surgery, radiotherapy, survival

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Authors: Guoqiang Yu, Mehrana Mohtasebi, Jinghong Sun, Thomas Pittman

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Malignant glioma (MG) is the most common type of primary malignant brain tumor. Surgical resection of MG remains the cornerstone of therapy, and the extent of resection correlates with patient survival. A limiting factor for resection, however, is the difficulty in differentiating the tumor from normal tissue during surgery. Fluorescence imaging is an emerging technique for real-time intraoperative visualization of MGs and their boundaries. However, most clinical-grade neurosurgical operative microscopes with fluorescence imaging ability are hampered by low adoption rates due to high cost, limited portability, limited operation flexibility, and lack of skilled professionals with technical knowledge. To overcome the limitations, we innovatively integrated miniaturized light sources, flippable filters, and a recording camera to the surgical eye loupes to generate a wearable fluorescence eye loupe (FLoupe) device for intraoperative imaging of fluorescent MGs. Two FLoupe prototypes were constructed for imaging of Fluorescein and 5-aminolevulinic acid (5-ALA), respectively. The wearable FLoupe devices were tested on tumor-simulating phantoms and patients with MGs. Comparable results were observed against the standard neurosurgical operative microscope (PENTERO® 900) with fluorescence kits. The affordable and wearable FLoupe devices enable visualization of both color and fluorescence images with the same quality as the large and expensive stationary operative microscopes. The wearable FLoupe device allows for a greater range of movement, less obstruction, and faster/easier operation. Thus, it reduces surgery time and is more easily adapted to the surgical environment than unwieldy neurosurgical operative microscopes.

Keywords: fluorescence guided surgery, malignant glioma, neurosurgical operative microscope, wearable fluorescence imaging device

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Authors: S. Zolghadri, M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani

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In this study, the absorbed dose of human organs after injection of ¹⁷⁷Lu-DOTATOC was studied based on the biodistribution of the complex in adenocarcinoma breast cancer bearing mice. For this purpose, the biodistribution of the radiolabelled complex was studied and compartmental modeling was applied to calculate the absorbed dose with high precision. As expected, ¹⁷⁷Lu-DOTATOC illustrated a notable specific uptake in tumor and pancreas, organs with high level of somatostatin receptor on their surface and the effectiveness of the radio-conjugate for targeting of the breast adenocarcinoma tumors was indicated. The elicited results of modeling were the exponential equations, and those are utilized for obtaining the cumulated activity data by taking their integral. The results also exemplified that non-target absorbed-doses such as the liver, spleen and pancreas were approximately 0.008, 0.004, and 0.039, respectively. While these values were so much lower than target (tumor) absorbed-dose, it seems due to this low toxicity, this complex is a good agent for therapy.

Keywords: ¹⁷⁷Lu, breast cancer, compartmental modeling, dosimetry

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Authors: Akterono Budiyati, Gita Kusumo, Teguh Putra, Fritzie Rexana, Antonius Kurniawan, Aru Sudoyo, Ahmad Utomo, Andi Utama

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The presence of the programmed death ligand-1 (PD-L1) has been used in multiple clinical trials and approved as biomarker for selecting patients more likely to respond to immune checkpoint inhibitors. However, the expression of PD-L1 is regulated in different ways, which leads to a different significance of its presence. Positive PD-L1 within tumors may result from two mechanisms, induced PD-L1 expression by T-cell presence or genetic mechanism that lead to constitutive PD-L1 expression. Amplification of PD-L1 genes was found as one of genetic mechanism which causes an increase in PD-L1 expression. In case of colorectal cancer (CRC), targeting immune checkpoint inhibitor has been recommended for patients with microsatellite instable (MSI). Although the correlation between PD-L1 expression and MSI status has been widely studied, so far the precise mechanism of PD-L1 gene activation in CRC patients, particularly in MSI population have yet to be clarified. In this present study we have profiled 61 archived formalin fixed paraffin embedded CRC specimens of patients from Medistra Hospital, Jakarta admitted in 2010 - 2016. Immunohistochemistry was performed to measure expression of PD-L1 in tumor cells as well as MSI status using antibodies against PD-L1 and MMR (MLH1, MSH2, PMS2 and MSH6), respectively. PD-L1 expression was measured on tumor cells with cut off of 1% whereas loss of nuclear MMR protein expressions in tumor cells but not in normal or stromal cells indicated presence of MSI. Subset of PD-L1 positive patients was then assessed for copy number variations (CNVs) using single Tube TaqMan Copy Number Assays Gene CD247PD-L1. We also observed KRAS mutation to profile possible genetic mechanism leading to the presence or absence of PD-L1 expression. Analysis of 61 CRC patients revealed 15 patients (24%) expressed PD-L1 on their tumor cell membranes. The prevalence of surface membrane PD-L1 was significantly higher in patients with MSI (87%; 7/8) compared to patients with microsatellite stable (MSS) (15%; 8/53) (P=0.001). Although amplification of PD-L1 gene was not found among PD-L1 positive patients, low-level amplification of PD-L1 gene was commonly observed in MSS patients (75%; 6/8) than in MSI patients (43%; 3/7). Additionally, we found 26% of CRC patients harbored KRAS mutations (16/61), so far the distribution of KRAS status did not correlate with PD-L1 expression. Our data suggest genetic mechanism through amplification of PD-L1 seems not to be the mechanism underlying upregulation of PD-L1 expression in CRC patients. However, further studies are warranted to confirm the results.

Keywords: colorectal cancer, gene amplification, microsatellite instable, programmed death ligand-1

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Authors: Eun-Joong Kim, Sankarprasad Bhuniya, Hyunseung Lee, Hyun Min Kim, Chaejoon Cheong, Su-khendu Maiti, Kwan Soo Hong, Jong Seung Kim

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Metastatic cancers have historically been difficult to treat. However, metastatic tumors have been found to have high levels of reactive oxygen species such as hydrogen peroxide (H2O2), supporting the hypothesis that a prodrug could be activated by intracellular H2O2 and lead to a potential anti-metastatic therapy. In this study, prodrug 7 was designed to be activated by H2O2-mediated boronate oxidation, resulting in activation of the fluorophore for detection and release of the therapeutic agent, SN-38. Drug release from prodrug 7 was investigated by monitoring fluorescence after addition of H2O2 to the cancer cells. Prodrug 7 activated by H2O2 selectively inhibited tumor cell growth. Furthermore, intratracheally administered prodrug 7 showed effective anti-tumor activity in a mouse model of metastatic lung disease. Thus, this H2O2-responsive prodrug has therapeutic potential as a novel treatment for metastatic cancer via cellular imaging with fluorescence as well as selective release of the anti-cancer drug, SN-38.

Keywords: hydrogen peroxide, prodrug, metastatic tumors, fluorescence

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Authors: Mateusz Bilski, Jakub Klas, Emilia Kowalczyk, Sylwia Koziej, Katarzyna Kulszo, Ludmiła Grzybowska- Szatkowska

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Background: Liver metastases are a common complication of primary solid tumors and sig-nificantly reduce patient survival. In the era of increasing diagnosis of oligometastatic disease and oligoprogression, methods of local treatment of metastases, i.e. MDT, are becoming more important. Implementation of such treatment can be considered for liver metastases, which are a common complication of primary solid tumors and significantly reduce patient survival. To date, the mainstay of treatment for oligometastatic disease has been surgical resection, but not all patients qualify for the procedure. As an alternative to surgical resection, radiotherapy techniques have become available, including stereotactic body radiation therapy (SBRT) or high-dose interstitial brachytherapy (iBT). iBT is an invasive method that emits very high doses of radiation from the inside of the tumor to the outside. This technique provides better tumor coverage than SBRT while having little impact on surrounding healthy tissue and elim-inates some concerns involving respiratory motion. Methods: We conducted a systematic re-view of the scientific literature on the use of brachytherapy in the treatment of liver metasta-ses from 2018 - 2023 using PubMed and ResearchGate browsers according to PRISMA rules. Results: From 111 articles, 18 publications containing information on 729 patients with liver metastases were selected. iBT has been shown to provide high rates of tumor control. Among 14 patients with 54 unresectable RCC liver metastases, after iBT LTC was 92.6% during a median follow-up of 10.2 months, PFS was 3.4 months. In analysis of 167 patients after treatment with a single fractional dose of 15-25 Gy with brachytherapy at 6- and 12-month follow-up, LRFS rates of 88,4-88.7% and 70.7 - 71,5%, PFS of 78.1 and 53.8%, and OS of 92.3 - 96.7% and 76,3% - 79.6%, respectively, were achieved. No serious complications were observed in all patients. Distant intrahepatic progression occurred later in patients with unre-sectable liver metastases after brachytherapy (PFS: 19.80 months) than in HCC patients (PFS: 13.50 months). A significant difference in LRFS between CRC patients (84.1% vs. 50.6%) and other histologies (92.4% vs. 92.4%) was noted, suggesting a higher treatment dose is necessary for CRC patients. The average target dose for metastatic colorectal cancer was 40 - 60 Gy (compared to 100 - 250 Gy for HCC). To better assess sensitivity to therapy and pre-dict side effects, it has been suggested that humoral mediators be evaluated. It was also shown that baseline levels of TNF-α, MCP-1 and VEGF, as well as NGF and CX3CL corre-lated with both tumor volume and radiation-induced liver damage, one of the most serious complications of iBT, indicating their potential role as biomarkers of therapy outcome. Con-clusions: The use of brachytherapy methods in the treatment of liver metastases of various cancers appears to be an interesting and relatively safe therapeutic method alternative to sur-gery. An important challenge remains the selection of an appropriate brachytherapy method and radiation dose for the corresponding initial tumor type from which the metastasis origi-nated.

Keywords: liver metastases, brachytherapy, CT-HDRBT, iBT

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Authors: Yogesh Rai, Saurabh Singh, Sanjay Pandey, Dhananjay K. Sah, B. G. Roy, B. S. Dwarakanath, Anant N. Bhatt

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One of the most common signatures of highly malignant gliomas is their capacity to metabolize more glucose to lactic acid than normal brain tissues, even under normoxic conditions (Warburg effect), indicating that aerobic glycolysis is constitutively upregulated through stable genetic or epigenetic changes. However, oxidative phosphorylation (OxPhos) is also required to maintain the mitochondrial membrane potential for tumor cell survival. In the process of tumorigenesis, tumor cells during fastest growth rate exhibit both high glycolytic and high OxPhos. Therefore, metabolically reprogrammed cancer cells with combination of both aerobic glycolysis and altered OxPhos develop a robust metabolic phenotype, which confers a selective growth advantage. In our study, we grew the high glycolytic BMG-1 (glioma) cells with continuous exposure of mitochondrial uncoupler 2, 4, dinitro phenol (DNP) for 10 passages to obtain a phenotype of high glycolysis with enhanced altered OxPhos. We found that OxPhos modified BMG (OPMBMG) cells has similar growth rate and cell cycle distribution but high mitochondrial mass and functional enzymatic activity than parental cells. In in-vitro studies, OPMBMG cells showed enhanced invasion, proliferation and migration properties. Moreover, it also showed enhanced angiogenesis in matrigel plug assay. Xenografted tumors from OPMBMG cells showed reduced latent period, faster growth rate and nearly five folds reduction in the tumor take in nude mice compared to BMG-1 cells, suggesting that robust metabolic phenotype facilitates tumor formation and growth. OPMBMG cells which were found radio-resistant, showed enhanced radio-sensitization by 2-DG as compared to the parental BMG-1 cells. This study suggests that metabolic reprogramming in cancer cells enhances the potential of migration, invasion and proliferation. It also strengthens the cancer cells to escape the death processes, conferring resistance to therapeutic modalities. Our data also suggest that combining metabolic inhibitors like 2-DG with conventional therapeutic modalities can sensitize such metabolically aggressive cancer cells more than the therapies alone.

Keywords: 2-DG, BMG, DNP, OPM-BMG

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Authors: Mohammad Izadkhah, Mojtaba Hoseini, Alireza Khalili Tehrani

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In this paper we presented a new method for tracking flying targets in color video sequences based on contour and kernel. The aim of this work is to overcome the problem of losing target in changing light, large displacement, changing speed, and occlusion. The proposed method is made in three steps, estimate the target location by particle filter, segmentation target region using neural network and find the exact contours by greedy snake algorithm. In the proposed method we have used both region and contour information to create target candidate model and this model is dynamically updated during tracking. To avoid the accumulation of errors when updating, target region given to a perceptron neural network to separate the target from background. Then its output used for exact calculation of size and center of the target. Also it is used as the initial contour for the greedy snake algorithm to find the exact target's edge. The proposed algorithm has been tested on a database which contains a lot of challenges such as high speed and agility of aircrafts, background clutter, occlusions, camera movement, and so on. The experimental results show that the use of neural network increases the accuracy of tracking and segmentation.

Keywords: video tracking, particle filter, greedy snake, neural network

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Authors: Hussein Alahmer, Amr Ahmed

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Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, fuzzy c means, lesion detection, liver segmentation

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Authors: Yaya Gao, Jifeng Liu, Yafeng Liu

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Objectives: This study aimed to improve clinicians' understanding and diagnosis of the Mammary analogue secretory carcinoma of the salivary gland（MASC）. Methods: The clinical features of a MASC patient who was admitted to WestChina Hospital of Sichuan University in July 2020 were reviewed and analyzed. A 49-year-old woman with left upper neck pain for three months was admitted to the hospital. She underwent adenoma resection of the left submandibular gland 14 years ago and mucoepidermoid carcinoma resection surgery five years ago. Three months before admission, the patient developed pain in the left mandibular angle after "fatigue" and gradually developed radiation pain in the left ear, which could be relieved after rest. A mass of 1cm could be touched at the mandibular, with tenderness, poor mobility, and hard texture. No swelling, heat, pain, rupture, or pus was found on the surrounding skin. Color doppler ultrasonography of the salivary gland indicated a weak echo mass of 23*14*17mm in the left parotid gland. Results: Surgical excision was completed. Immunohistochemistry of the tumor samples after operation showed that P63（a few，+）, CK7（+）, S100（+）, DOG1（-）, Ki67（MIB-1）（+，5%），pan-TRK（+）, PAS(+) . ETV-6 gene translocation was detected in FISH in postoperative pathology, which indicated MASC. After this diagnosis, the patient sent the postoperative specimen of the second submandibular tumor to our hospital for consultation. The morphology of the two was similar. FISH detected ETV-6 gene translocation, so the second pathological diagnosis was revised to MASC. Conclusion: MASC of the salivary gland is a rare salivary gland tumor whose diagnosis depends on the result of the ETV6-NTRK3 fusion gene.

Keywords: mammary analogue secretory carcinoma, ETV6-NTRK3, salivary gland, misdiagnosed

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Authors: Rachel Shukrun, Szilvia Baron, Victoria Fidel, Anna Shusterman, Osnat Sher, Netanya Kollender, Dror Levin, Yair Peled, Yair Gortzak, Yoav Ben-Shahar, Revital Caspi, Sagi Gordon, Michal Manisterski, Ronit Elhasid

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Ewing sarcoma (EWS) is a highly aggressive cancer with a survival rate of 70–80% for patients with localized disease and under 30% for those with metastatic disease. Tumor-infiltrating neutrophils (TIN) can generate extracellular net-like DNA structures known as neutrophil extracellular traps (NETs). However, little is known about the presence and prognostic significance of tumor-infiltrating NETs in EWS. Herein, we investigated 46 patients diagnosed with EWS and treated in the Tel Aviv Medical Center between 2010 and 2021. TINs and NETs were identified in diagnostic biopsies of EWS by immunofluorescent. In addition, NETs were investigated in neutrophils isolated from peripheral blood samples of EWS patients at diagnosis and following neoadjuvant chemotherapy. The relationships between the presence of TINs and NETs, pathological and clinical features, and outcomes were analyzed. Our results demonstrate that TIN and NETs at diagnosis were higher in EWS patients with metastatic disease compared to those with local disease. High NETs formation at diagnosis predicted poor response to neo-adjuvant chemotherapy, relapse, and death from disease (P < .05). NETs formation in peripheral blood samples at diagnosis was significantly elevated among patients with EWS compared to pediatric controls and decreased significantly following neoadjuvant chemotherapy. In conclusion, NETs formation seems to have a role in the EWS immune microenvironment. Their presence can refine risk stratification, predict chemotherapy resistance and survival, and serve as a therapeutic target in patients with EWS.

Keywords: Ewing sarcoma, tumor microenvironment, neutrophil, neutrophil extracellular traps (NETs), prognosis

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Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

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The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.

Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing

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Authors: Chengcao Sun, Shujun Li, Cuili Yang, Yongyong Xi, Liang Wang, Feng Zhang, Dejia Li

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Hsa-miRNA-139-5p (miR-139-5p) has recently been discovered having anticancer efficacy in different organs. However, the role of miR-139-5p on lung cancer is still ambiguous. In this study, we investigated the role of miR-139-5p on development of lung cancer. Results indicated miR-139-5p was significantly down-regulated in primary tumor tissues and very low levels were found in a non-small cell lung cancer (NSCLC) cell lines. Ectopic expression of miR-139-5p in NSCLC cell lines significantly suppressed cell growth through inhibition of cyclin D1 and up-regulation of p57(Kip2). In addition, miR-139-5p induced apoptosis, as indicated by up-regulation of key apoptosis gene cleaved caspase-3, and down-regulation of anti-apoptosis gene Bcl2. Moreover, miR-139-5p inhibited cellular metastasis through inhibition of matrix metalloproteinases (MMP)-7 and MMP-9. Further, oncogene c-Met was revealed to be a putative target of miR-139-5p, which was inversely correlated with miR-139-5p expression. Taken together, our results demonstrated that miR-139-5p plays a pivotal role in lung cancer through inhibiting cell proliferation, metastasis, and promoting apoptosis by targeting oncogenic c-Met.

Keywords: hsa-miRNA-139-5p (miR-139-5p), c-Met, non-small cell lung cancer (NSCLC), proliferation, apoptosis

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Authors: Jasminka Mujic, Karin Milde-Langosch, Volkmar Mueller, Mirza Suljagic, Tea Becirevic, Jozo Coric, Daria Ler

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MACC1 (metastasis associated in colon cancer-1) is a prognostic biomarker for tumor progression, metastasis, and survival of a variety of solid cancers. MACC1 also causes tumor growth in xenograft models and acts as a master regulator of the HGF/MET signaling pathway. In breast cancer, the expression of MACC1 determined by immunohistochemistry was significantly associated with positive lymph node status and advanced clinical stage. The aim of the present study was to further investigate the prognostic or predictive value of MACC1 expression in breast cancer using western blot analysis and immunohistochemistry. The results of our study have shown that high MACC1 expression in breast cancer is associated with shorter disease-free survival, especially in node-negative tumors. The MACC1 might be a suitable biomarker to select patients with a higher probability of recurrence which might benefit from adjuvant chemotherapy. Our results support a biologic role and potentially open the perspective for the use of MACC1 as predictive biomarker for treatment decision in breast cancer patients.

Keywords: breast cancer, biomarker, HGF/MET, MACC1

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Authors: Parveen Kundu, Zile Singh, Kunika Kundu, Swaran Kaur

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Context: Tuberculous osteomyelitis is a relatively uncommon condition that can present with various clinical and radiological features, often mimicking bone tumors or tumor-like lesions. In endemic countries like India, tuberculosis should be considered as a potential differential diagnosis for lytic bone lesions. This study aimed to highlight the different presentations of tuberculosis that can mimic tumors or tumor-like lesions in bone and emphasize the successful outcome of antitubercular therapy (ATT) in treating these cases. Research Aim: The main objective of this research was to explore the varied presentations of tuberculosis that mimic bone tumors or tumor-like lesions both clinically and radiologically, focusing on different bones. The study aimed to raise awareness among clinicians about this possibility and highlight the importance of histopathological confirmation before initiating treatment for lytic bone lesions. Methodology: This study utilized a retrospective review of 22 patients with suspected lytic bone lesions, who were subsequently diagnosed with tuberculous osteomyelitis through histopathological examination. The cases were collected over a period of ten years. Eleven cases required curettage for extensive lesions with sequestrations, while all 22 patients received 12 months of antitubercular therapy. Findings: The study included 14 male and 8 female patients, ranging in age from 3 to 61 years, with an average age of 22.05. The clinical and radiological presentations varied, with examples including bone cysts in the metaphyseal area of long bones, lesions resembling chondroblastomas, giant cell tumors, and osteoid osteoma, as well as multifocal lytic lesions resembling metastasis or multiple myeloma. One patient had lesions in both the clavicle and hand. Lesions mimicking chondromas were also observed in the phalanges of the hand and foot metatarsal. All patients showed resolution of the lesions and no residual disability following ATT. Theoretical Importance: This study highlights the importance of considering tuberculosis as a potential differential diagnosis for lytic bone lesions, particularly in endemic regions. It emphasizes the need for histopathological confirmation to accurately diagnose tuberculous osteomyelitis, as this is considered the gold standard. Data Collection and Analysis Procedures: Data for this study were collected retrospectively from medical records and radiological images of the 22 patients. The cases were analyzed based on clinical presentation, radiological findings, and histopathological confirmation. The outcomes of antitubercular therapy were also assessed. The data were summarized and presented descriptively. Question Addressed: This study aimed to address the question of how tuberculosis can mimic different bone tumors and tumor-like lesions clinically and radiologically. It also aimed to assess the successful outcome of antitubercular therapy in treating these cases. Conclusion: Tuberculous osteomyelitis can present with varied clinical and radiological features, often mimicking bone tumors or tumor-like lesions. Clinicians should consider tuberculosis as a potential diagnosis for lytic bone lesions, especially in endemic areas. Histopathological confirmation is essential for accurate diagnosis. Antitubercular therapy is an effective treatment for tuberculous osteomyelitis, leading to the resolution of the lesions with no residual disability.

Keywords: tuberculosis, tumor, curettage, bone

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Authors: Spira A., Marabelle A., Kientop D., Moser E., Mumm J.

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Background: Both interleukin-2 (IL-2) and interleukin-10 (IL-10) have been extensively studied for their stimulatory function on T cells and their potential to obtain sustainable tumor control in RCC, melanoma, lung, and pancreatic cancer as monotherapy, as well as combination with PD-1 blockers, radiation, and chemotherapy. While approved, IL-2 retains significant toxicity, preventing its widespread use. The significant efforts undertaken to uncouple IL-2 toxicity from its anti-tumor function have been unsuccessful, and early phase clinical safety observed with PEGylated IL-10 was not met in a blinded Phase 3 trial. Deka Biosciences has engineered a novel molecule coupling wild-type IL-2 to a high affinity variant of Epstein Barr Viral (EBV) IL-10 via a scaffold (scFv) that binds to epidermal growth factor receptors (EGFR). This patented molecule, termed DK210 (EGFR), is retained at high levels within the tumor microenvironment for days after dosing. In addition to overlapping and non-redundant anti-tumor function, IL-10 reduces IL-2 mediated cytokine release syndrome risks and inhibits IL-2 mediated T regulatory cell proliferation. Methods: DK210 (EGFR) is being evaluated in an open-label, dose-escalation (Phase 1) study with 5 (0.025-0.3 mg/kg) monotherapy dose levels and (expansion cohorts) in combination with PD-1 blockers, or radiation or chemotherapy in patients with advanced solid tumors overexpressing EGFR. Key eligibility criteria include 1) confirmed progressive disease on at least one line of systemic treatment, 2) EGFR overexpression or amplification documented in histology reports, 3) at least a 4 week or 5 half-lives window since last treatment, and 4) excluding subjects with long QT syndrome, multiple myeloma, multiple sclerosis, myasthenia gravis or uncontrolled infectious, psychiatric, neurologic, or cancer disease. Plasma and tissue samples will be investigated for pharmacodynamic and predictive biomarkers and genetic signatures associated with IFN-gamma secretion, aiming to select subjects for treatment in Phase 2. Conclusion: Through successful coupling of wild-type IL-2 with a high affinity IL-10 and targeting directly to the tumor microenvironment, DK210 (EGFR) has the potential to harness IL-2 and IL-10’s known anti-cancer promise while reducing immunogenicity and toxicity risks enabling safe concomitant cytokine treatment with other anti-cancer modalities.

Keywords: cytokine, EGFR over expression, interleukine-2, interleukine-10, clinical trial

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Authors: Kristina Sakalauskiene, Renaldas Raisutis, Gintare Linkeviciute, Skaidra Valiukeviciene

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Cutaneous melanoma is a melanocytic skin tumour, which has a very poor prognosis while is highly resistant to treatment and tends to metastasize. Thickness of melanoma is one of the most important biomarker for stage of disease, prognosis and surgery planning. In this study, we hypothesized that the automatic analysis of spectrophotometric images and high-frequency ultrasonic 2D data can improve differential diagnosis of cutaneous melanoma and provide additional information about tumour penetration depth. This paper presents the novel complex automatic system for non-invasive melanocytic skin tumour differential diagnosis and penetration depth evaluation. The system is composed of region of interest segmentation in spectrophotometric images and high-frequency ultrasound data, quantitative parameter evaluation, informative feature extraction and classification with linear regression classifier. The segmentation of melanocytic skin tumour region in ultrasound image is based on parametric integrated backscattering coefficient calculation. The segmentation of optical image is based on Otsu thresholding. In total 29 quantitative tissue characterization parameters were evaluated by using ultrasound data (11 acoustical, 4 shape and 15 textural parameters) and 55 quantitative features of dermatoscopic and spectrophotometric images (using total melanin, dermal melanin, blood and collagen SIAgraphs acquired using spectrophotometric imaging device SIAscope). In total 102 melanocytic skin lesions (including 43 cutaneous melanomas) were examined by using SIAscope and ultrasound system with 22 MHz center frequency single element transducer. The diagnosis and Breslow thickness (pT) of each MST were evaluated during routine histological examination after excision and used as a reference. The results of this study have shown that automatic analysis of spectrophotometric and high frequency ultrasound data can improve non-invasive classification accuracy of early-stage cutaneous melanoma and provide supplementary information about tumour penetration depth.

Keywords: cutaneous melanoma, differential diagnosis, high-frequency ultrasound, melanocytic skin tumours, spectrophotometric imaging

Procedia PDF Downloads 267

Authors: Jaeyoung Lee

Abstract:

Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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Authors: C. A. Anser Pasha

Abstract:

In this paper, a new Vehicular Speed Detection Camera System that is applicable as an alternative to traditional radars with the same accuracy or even better is presented. The real-time measurement and analysis of various traffic parameters such as speed and number of vehicles are increasingly required in traffic control and management. Image processing techniques are now considered as an attractive and flexible method for automatic analysis and data collections in traffic engineering. Various algorithms based on image processing techniques have been applied to detect multiple vehicles and track them. The SDCS processes can be divided into three successive phases; the first phase is Objects detection phase, which uses a hybrid algorithm based on combining an adaptive background subtraction technique with a three-frame differencing algorithm which ratifies the major drawback of using only adaptive background subtraction. The second phase is Objects tracking, which consists of three successive operations - object segmentation, object labeling, and object center extraction. Objects tracking operation takes into consideration the different possible scenarios of the moving object like simple tracking, the object has left the scene, the object has entered the scene, object crossed by another object, and object leaves and another one enters the scene. The third phase is speed calculation phase, which is calculated from the number of frames consumed by the object to pass by the scene.

Keywords: radar, image processing, detection, tracking, segmentation

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Authors: Ingrid Argote, John Archila, Marcelo Becker

Abstract:

In agriculture, intelligent systems applications have generated great advances in automating some of the processes in the production chain. In order to improve the efficiency of those systems is proposed a vision system to estimate the amount of fruits in sweet orange trees. This work presents a system proposal using capture of thermal images and fuzzy logic. A bibliographical review has been done to analyze the state-of-the-art of the different systems used in fruit recognition, and also the different applications of thermography in agricultural systems. The algorithm developed for this project uses the metrics of the fuzzines parameter to the contrast improvement and segmentation of the image, for the counting algorith m was used the Hough transform. In order to validate the proposed algorithm was created a bank of images of sweet orange Citrus (L.) Osbeck acquired in the Maringá Farm. The tests with the algorithm Indicated that the variation of the tree branch temperature and the fruit is not very high, Which makes the process of image segmentation using this differentiates, This Increases the amount of false positives in the fruit counting algorithm. Recognition of fruits isolated with the proposed algorithm present an overall accuracy of 90.5 % and grouped fruits. The accuracy was 81.3 %. The experiments show the need for a more suitable hardware to have a better recognition of small temperature changes in the image.

Keywords: Agricultural systems, Citrus, Fuzzy logic, Thermal images.

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Authors: Nicholas Fletcher, Zachary Houston, Yongmei Zhao, Christopher Howard, Kristofer Thurecht

Abstract:

One promising approach to enhance nanomedicine therapeutic efficacy is to include a targeting agent, such as an antibody, to increase accumulation at the tumor site. However, the application of such targeted nanomedicines remains limited, in part due to difficulties involved with biomolecule conjugation to synthetic nanomaterials. One approach recently developed to overcome this has been to engineer bispecific antibodies (BsAbs) with dual specificity, whereby one portion binds to methoxy polyethyleneglycol (mPEG) epitopes present on synthetic nanomedicines, while the other binds to molecular disease markers of interest. In this way, noncovalent complexes of nanomedicine core, comprising a hyperbranched polymer (HBP) of primarily mPEG, decorated with targeting ligands are able to be produced by simple mixing. Further work in this area has now demonstrated such complexes targeting the breast cancer marker epidermal growth factor receptor (EGFR) to show enhanced binding to tumor cells both in vitro and in vivo. Indeed the enhanced accumulation at the tumor site resulted in improved therapeutic outcomes compared to untargeted nanomedicines and free chemotherapeutics. The current work on these BsAb-HBP conjugates focuses on further probing antibody-nanomaterial interactions and demonstrating broad applicability to a range of cancer types. Herein are reported BsAb-HBP materials targeted towards prostate-specific membrane antigen (PSMA) and study of their behavior in vivo using ⁸⁹Zr positron emission tomography (PET) in a dual-tumor prostate cancer xenograft model. In this model mice bearing both PSMA+ and PSMA- tumors allow for PET imaging to discriminate between nonspecific and targeted uptake in tumors, and better quantify the increased accumulation following BsAb conjugation. Also examined is the potential for formation of these targeted complexes in situ following injection of individual components? The aim of this approach being to avoid undesirable clearance of proteinaceous complexes upon injection limiting available therapeutic. Ultimately these results demonstrate BsAb functionalized nanomaterials as a powerful and versatile approach for producing targeted nanomedicines for a variety of cancers.

Keywords: bioengineering, cancer, nanomedicine, polymer chemistry

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Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

Abstract:

Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

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Authors: Dor Oppenheim, Yael Edan, Guy Shani

Abstract:

This paper presents an image analysis algorithm to detect and count yellow tomato flowers in a greenhouse with uneven illumination conditions, complex growth conditions and different flower sizes. The algorithm is designed to be employed on a drone that flies in greenhouses to accomplish several tasks such as pollination and yield estimation. Detecting the flowers can provide useful information for the farmer, such as the number of flowers in a row, and the number of flowers that were pollinated since the last visit to the row. The developed algorithm is designed to handle the real world difficulties in a greenhouse which include varying lighting conditions, shadowing, and occlusion, while considering the computational limitations of the simple processor in the drone. The algorithm identifies flowers using an adaptive global threshold, segmentation over the HSV color space, and morphological cues. The adaptive threshold divides the images into darker and lighter images. Then, segmentation on the hue, saturation and volume is performed accordingly, and classification is done according to size and location of the flowers. 1069 images of greenhouse tomato flowers were acquired in a commercial greenhouse in Israel, using two different RGB Cameras – an LG G4 smartphone and a Canon PowerShot A590. The images were acquired from multiple angles and distances and were sampled manually at various periods along the day to obtain varying lighting conditions. Ground truth was created by manually tagging approximately 25,000 individual flowers in the images. Sensitivity analyses on the acquisition angle of the images, periods throughout the day, different cameras and thresholding types were performed. Precision, recall and their derived F1 score were calculated. Results indicate better performance for the view angle facing the flowers than any other angle. Acquiring images in the afternoon resulted with the best precision and recall results. Applying a global adaptive threshold improved the median F1 score by 3%. Results showed no difference between the two cameras used. Using hue values of 0.12-0.18 in the segmentation process provided the best results in precision and recall, and the best F1 score. The precision and recall average for all the images when using these values was 74% and 75% respectively with an F1 score of 0.73. Further analysis showed a 5% increase in precision and recall when analyzing images acquired in the afternoon and from the front viewpoint.

Keywords: agricultural engineering, image processing, computer vision, flower detection

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Authors: Taleb Lotfi, Benarbia Maheidine, Allam Hamza, Boutira Fatima, Boukerche Abdelbaki

Abstract:

Introduction and purpose of the study: This is a retrospective single-center study with an analytical aim to determine the prognostic factors for relapse in patients treated with radiotherapy after total laryngectomy with lymph node dissection for laryngeal cancer at the Emir Abdelkader cancer center in Oran (Algeria). Material and methods: During the study period from January 2014 to December 2018, eighty-nine patients (n=89) with squamous cell carcinoma of the larynx were treated with postoperative radiotherapy. Relapse-free survival was studied in the univariate analysis according to pre-treatment criteria using Kaplan-Meier survival curves. We performed a univariate analysis to identify relapse factors. Statistically significant factors have been studied in the multifactorial analysis according to the Cox model. Results and statistical analysis: The average age was 62.7 years (40-86 years). It was a squamous cell carcinoma in all cases. Postoperatively, the tumor was classified as pT3 and pT4 in 93.3% of patients. Histological lymph node involvement was found in 36 cases (40.4%), with capsule rupture in 39% of cases, while the limits of surgical excision were microscopically infiltrated in 11 patients (12.3%). Chemotherapy concomitant with radiotherapy was used in 67.4% of patients. With a median follow-up of 57 months (23 to 104 months), the probabilities of relapse-free survival and five-year overall survival are 71.2% and 72.4%, respectively. The factors correlated with a high risk of relapse were locally advanced tumor stage pT4 (p=0.001), tumor site in case of subglottic extension (p=0.0003), infiltrated surgical limits R1 (p=0.001), l lymph node involvement (p=0.002), particularly in the event of lymph node capsular rupture (p=0.0003) as well as the time between surgery and adjuvant radiotherapy (p=0.001). However, in the subgroup analysis, the major prognostic factors for disease-free survival were subglottic tumor extension (p=0.001) and time from surgery to adjuvant radiotherapy (p=0.005). Conclusion: Combined surgery and postoperative radiation therapy are effective treatment modalities in the management of laryngeal cancer. Close cooperation of the entire cervicofacial oncology team is essential, expressed during a multidisciplinary consultation meeting, with the need to respect the time between surgery and radiotherapy.

Keywords: laryngeal cancer, laryngectomy, postoperative radiotherapy, survival

Procedia PDF Downloads 100

Authors: Marrone Silverio Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner, Djamel Fawzi Hadj Sadok

Abstract:

The creation of a dataset is time-consuming and often discourages researchers from pursuing their goals. To overcome this problem, we present and discuss two solutions adopted for the automation of this process. Both optimize valuable user time and resources and support video object segmentation with object tracking and 3D projection. In our scenario, we acquire images from a moving robotic arm and, for each approach, generate distinct annotated datasets. We evaluated the precision of the annotations by comparing these with a manually annotated dataset, as well as the efficiency in the context of detection and classification problems. For detection support, we used YOLO and obtained for the projection dataset an F1-Score, accuracy, and mAP values of 0.846, 0.924, and 0.875, respectively. Concerning the tracking dataset, we achieved an F1-Score of 0.861, an accuracy of 0.932, whereas mAP reached 0.894. In order to evaluate the quality of the annotated images used for classification problems, we employed deep learning architectures. We adopted metrics accuracy and F1-Score, for VGG, DenseNet, MobileNet, Inception, and ResNet. The VGG architecture outperformed the others for both projection and tracking datasets. It reached an accuracy and F1-score of 0.997 and 0.993, respectively. Similarly, for the tracking dataset, it achieved an accuracy of 0.991 and an F1-Score of 0.981.

Keywords: RJ45, automatic annotation, object tracking, 3D projection

Procedia PDF Downloads 164

Authors: Luciano Tarantino, Emanuele Balzano, Paolo Tarantino, Riccardo Aurelio Nasto, Aurelio Nasto

Abstract:

Liver transplantation (OLT) is contraindicate in Portal Vein tumor Thrombosis (PVTT) from Hepatocellular Carcinoma at hepatic hilum(pH-HCC) Surgery,Thermal ablation and chemotherapy show poorer outcomes Electrochemotherapy (ECT) has been successfully used in patients with pH-HCC with PVTT. We report the results of ECT as downstaging aimed to definitive cure by OLT. F.P. 53 years HBV related Cirrhosis Child-Pugh B7 class; EGDS F2 aesophageal Varices. Diabetes. April 2016 : Enhanced Computed Tomography (CT) detected HCC(n.3 nodules in VII-VIII-VI;diameter range=25 cm) and PVTT of right portal vein. The patient was considered ineligible for OLT. May 2016: first ablation session with percutaneous Radiofrequency-ablation(RFA) of 3 HCC-nodules . August 2016: second ablation session with ECT of PVTT. CT october 2016: disappearance of PVTT and patent right portal vein. No intraparenchymal recurrence. CT march 2017: No recurrence in portal vein and in the left lobe. local recurrence in the VII-VIII segments. May 2017 : transarterial chemoembolization (TACE) of right lobe recurrences. CT October 2017: patent right portal vein. No recurrence. The patient was reconsidered for OLT. He underwent OLT in April 2018. At 36-months follow-up , no intrahepatic recurrence of HCC occurred. March 2021: enhanced CT and PET/CT detected a single small nodule (1.5 cm) uptaking tracer in the left upper pulmonary lobe, no hepatic recurrence . CT-guided FNB showed metastasis from HCC . June 2021: left lung upper lobectomy . At the current time the patient is alive and recurrence-free at 64 months follow-up. ECT Could be aneffective technique as pre-OLT dowstaging in HCC with PVTT.

Keywords: liver tumor ablation, interventional ultrasound, electrochemotherapy, liver transplantation

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Authors: A. Y. Tsidulko, T. M. Pankova, E. V. Grigorieva

Abstract:

High-grade gliomas are the most frequent and most aggressive brain tumors which are characterized by active invasion of tumor cells into the surrounding brain tissue, where the extracellular matrix (ECM) plays a crucial role. Disruption of ECM can be involved in anticancer drugs effectiveness, side-effects and also in tumor relapses. The anti-inflammatory agent dexamethasone is a common drug used during high-grade glioma treatment for alleviating cerebral edema. Although dexamethasone is widely used in the clinic, its effects on normal brain tissue ECM remain poorly investigated. It is known that proteoglycans (PGs) are a major component of the extracellular matrix in the central nervous system. In our work, we studied the effects of dexamethasone on the ECM proteoglycans (syndecan-1, glypican-1, perlecan, versican, brevican, NG2, decorin, biglican, lumican) using RT-PCR in the experimental animal model. It was shown that proteoglycans in rat brain have age-specific expression patterns. In early post-natal rat brain (8 days old rat pups) overall PGs expression was quite high and mainly expressed PGs were biglycan, decorin, and syndecan-1. The overall transcriptional activity of PGs in adult rat brain is 1.5-fold decreased compared to post-natal brain. The expression pattern was changed as well with biglycan, decorin, syndecan-1, glypican-1 and brevican becoming almost equally expressed. PGs expression patterns create a specific tissue microenvironment that differs in developing and adult brain. Dexamethasone regimen close to the one used in the clinic during high-grade glioma treatment significantly affects proteoglycans expression. It was shown that overall PGs transcription activity is 1.5-2-folds increased after dexamethasone treatment. The most up-regulated PGs were biglycan, decorin, and lumican. The PGs expression pattern in adult brain changed after treatment becoming quite close to the expression pattern in developing brain. It is known that microenvironment in developing tissues promotes cells proliferation while in adult tissues proliferation is usually suppressed. The changes occurring in the adult brain after dexamethasone treatment may lead to re-activation of cell proliferation due to signals from changed microenvironment. Taken together obtained data show that dexamethasone treatment significantly affects the normal brain ECM, creating the appropriate microenvironment for tumor cells proliferation and thus can reduce the effectiveness of anticancer treatment and promote tumor relapses. This work has been supported by a Russian Science Foundation (RSF Grant 16-15-10243)

Keywords: dexamthasone, extracellular matrix, glioma, proteoglycan

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Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

Abstract:

The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

Procedia PDF Downloads 501