Search results for: Sahithi Talasila
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2

Search results for: Sahithi Talasila

2 Diagnosis, Treatment, and Prognosis in Cutaneous Anaplastic Lymphoma Kinase-Positive Anaplastic Large Cell Lymphoma: A Narrative Review Apropos of a Case

Authors: Laura Gleason, Sahithi Talasila, Lauren Banner, Ladan Afifi, Neda Nikbakht

Abstract:

Primary cutaneous anaplastic large cell lymphoma (pcALCL) accounts for 9% of all cutaneous T-cell lymphomas. pcALCL is classically characterized as a solitary papulonodule that often enlarges, ulcerates, and can be locally destructive, but overall exhibits an indolent course with overall 5-year survival estimated to be 90%. Distinguishing pcALCL from systemic ALCL (sALCL) is essential as sALCL confers a poorer prognosis with average 5-year survival being 40-50%. Although extremely rare, there have been several cases of ALK-positive ALCL diagnosed on skin biopsy without evidence of systemic involvement, which poses several challenges in the classification, prognostication, treatment, and follow-up of these patients. Objectives: We present a case of cutaneous ALK-positive ALCL without evidence of systemic involvement, and a narrative review of the literature to further characterize that ALK-positive ALCL limited to the skin is a distinct variant with a unique presentation, history, and prognosis. A 30-year-old woman presented for evaluation of an erythematous-violaceous papule present on her right chest for two months. With the development of multifocal disease and persistent lymphadenopathy, a bone marrow biopsy and lymph node excisional biopsy were performed to assess for systemic disease. Both biopsies were unrevealing. The patient was counseled on pursuing systemic therapy consisting of Brentuximab, Cyclophosphamide, Doxorubicin, and Prednisone given the concern for sALCL. Apropos of the patient we searched for clinically evident, cutaneous ALK-positive ALCL cases, with and without systemic involvement, in the English literature. Risk factors, such as tumor location, number, size, ALK localization, ALK translocations, and recurrence, were evaluated in cases of cutaneous ALK-positive ALCL. The majority of patients with cutaneous ALK-positive ALCL did not progress to systemic disease. The majority of cases that progressed to systemic disease in adults had recurring skin lesions and cytoplasmic localization of ALK. ALK translocations did not influence disease progression. Mean time to disease progression was 16.7 months, and significant mortality (50%) was observed in those cases that progressed to systemic disease. Pediatric cases did not exhibit a trend similar to adult cases. In both the adult and pediatric cases, a subset of cutaneous-limited ALK-positive ALCL were treated with chemotherapy. All cases treated with chemotherapy did not progress to systemic disease. Apropos of an ALK-positive ALCL patient with clinical cutaneous limited disease in the histologic presence of systemic markers, we discussed the literature data, highlighting the crucial issues related to developing a clinical strategy to approach this rare subtype of ALCL. Physicians need to be aware of the overall spectrum of ALCL, including cutaneous limited disease, systemic disease, disease with NPM-ALK translocation, disease with ALK and EMA positivity, and disease with skin recurrence.

Keywords: anaplastic large cell lymphoma, systemic, cutaneous, anaplastic lymphoma kinase, ALK, ALCL, sALCL, pcALCL, cALCL

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1 An Evolutionary Approach for Automated Optimization and Design of Vivaldi Antennas

Authors: Sahithi Yarlagadda

Abstract:

The design of antenna is constrained by mathematical and geometrical parameters. Though there are diverse antenna structures with wide range of feeds yet, there are many geometries to be tried, which cannot be customized into predefined computational methods. The antenna design and optimization qualify to apply evolutionary algorithmic approach since the antenna parameters weights dependent on geometric characteristics directly. The evolutionary algorithm can be explained simply for a given quality function to be maximized. We can randomly create a set of candidate solutions, elements of the function's domain, and apply the quality function as an abstract fitness measure. Based on this fitness, some of the better candidates are chosen to seed the next generation by applying recombination and permutation to them. In conventional approach, the quality function is unaltered for any iteration. But the antenna parameters and geometries are wide to fit into single function. So, the weight coefficients are obtained for all possible antenna electrical parameters and geometries; the variation is learnt by mining the data obtained for an optimized algorithm. The weight and covariant coefficients of corresponding parameters are logged for learning and future use as datasets. This paper drafts an approach to obtain the requirements to study and methodize the evolutionary approach to automated antenna design for our past work on Vivaldi antenna as test candidate. The antenna parameters like gain, directivity, etc. are directly caged by geometries, materials, and dimensions. The design equations are to be noted here and valuated for all possible conditions to get maxima and minima for given frequency band. The boundary conditions are thus obtained prior to implementation, easing the optimization. The implementation mainly aimed to study the practical computational, processing, and design complexities that incur while simulations. HFSS is chosen for simulations and results. MATLAB is used to generate the computations, combinations, and data logging. MATLAB is also used to apply machine learning algorithms and plotting the data to design the algorithm. The number of combinations is to be tested manually, so HFSS API is used to call HFSS functions from MATLAB itself. MATLAB parallel processing tool box is used to run multiple simulations in parallel. The aim is to develop an add-in to antenna design software like HFSS, CSTor, a standalone application to optimize pre-identified common parameters of wide range of antennas available. In this paper, we have used MATLAB to calculate Vivaldi antenna parameters like slot line characteristic impedance, impedance of stripline, slot line width, flare aperture size, dielectric and K means, and Hamming window are applied to obtain the best test parameters. HFSS API is used to calculate the radiation, bandwidth, directivity, and efficiency, and data is logged for applying the Evolutionary genetic algorithm in MATLAB. The paper demonstrates the computational weights and Machine Learning approach for automated antenna optimizing for Vivaldi antenna.

Keywords: machine learning, Vivaldi, evolutionary algorithm, genetic algorithm

Procedia PDF Downloads 80