SAGE: Sequential Attribute Generator for Analyzing Glioblastomas using Limited Dataset

While deep learning approaches have shown remarkable performance in many imaging tasks, most of these methods rely on availability of large quantities of data. Medical image data, however, is scarce and fragmented. Generative Adversarial Networks (GANs) have recently been very effective in handling such datasets by generating more data. If the datasets are very small, however, GANs cannot learn the data distribution properly, resulting in less diverse or low-quality results. One such limited dataset is that for the concurrent gain of 19 and 20 chromosomes (19/20 co-gain), a mutation with positive prognostic value in Glioblastomas (GBM). In this paper, we detect imaging biomarkers for the mutation to streamline the extensive and invasive prognosis pipeline. Since this mutation is relatively rare, i.e. small dataset, we propose a novel generative framework - the Sequential Attribute GEnerator (SAGE), that generates detailed tumor imaging features while learning from a limited dataset. Experiments show that not only does SAGE generate high quality tumors when compared to standard Deep Convolutional GAN (DC-GAN) and Wasserstein GAN with Gradient Penalty (WGAN-GP), it also captures the imaging biomarkers accurately

A curious case of T2-FLAIR mismatch in H3K27M mutant glioma

Diffuse midline gliomas are a rare relatively new classification of primary central nervous system tumors which include astrocytomas, oligodendrogliomas, and glioblastomas. The T2-FLAIR mismatch sign is regarded as a highly specific imaging feature of IDH-mutant, 1p/19q non-codeleted astrocytomas. The case presented herein demonstrates this sign, however, in a non-IDH mutated diffuse midline glioma with a H3K27M mutation, a World Health Organization Grade IV neoplasm. Although preoperative diagnosis can provide important treatment and prognostic information, it is often quite difficult particularly in primary central nervous system tumors

Giant phyllodes tumor of the breast: A case report

Phyllodes tumors of the breast are rare fibroepithelial neoplasms that account for less than 1% of all breast tumors. They tend to affect middle-aged women, who present with a rapidly growing, palpable mass. Here we present a case of a 34-year-old female surrogate mother without any reported personal or family history of breast cancer who presented with a rapidly growing left breast mass, pathologically proven to be a phyllodes tumor. The patient was a G7P7 surrogate mother who received estrogen and progesterone injections for her twin surrogate pregnancy starting 4 months before embryo implantation, after which, she discovered a large palpable mass in the left breast at approximately week 7 gestational age. At the initial presentation, the patient was at week 23 gestational age. She underwent C-section delivery of the twins at this time and obtained further work-up of the mass. She had a core needle biopsy which yielded a benign fibroepithelial tumor. Due to the size of her breast mass and atypical morphology, including extension to the nipple, and skin ulceration, the patient subsequently underwent left mastectomy. At the time of mastectomy, which was 8 months after the initial work-up, the mass had grown to measure approximately 12 × 10 cm on physical examination and took up most of her left breast. It was completely resected and was pathologically determined to be a borderline phyllodes tumor. Only a few cases have been reported about the development of phyllodes tumor during pregnancy in the literature, and we believe this is the first case report of phyllodes tumor related to a surrogate pregnancy. Although the relationship between exogenous hormones and fibroepithelial tumors is not well understood, the case poses the clinical question if screening mammograms should be offered to patients undergoing exogenous hormonal therapy, regardless of age to establish a baseline and monitor for the development (if any) or growth of these tumors

Enlarging premaxillary mass: A unique manifestation of extranodal diffuse B-cell lymphoma

Lymphomas are the most common nonepithelial malignancy in the head and neck region. Among these, non-Hodgkin Lymphoma (NHL) is the most prevalent, and diffuse large B-cell lymphoma (DLBCL) is the most common histologic subtype. NHL is known for its propensity for extranodal involvement, which can affect any anatomical location. The presence of perineural spread is frequently encountered in head and neck malignancies, including lymphomas. We report a case of a 40-year-old male with an enlarging infraorbital facial mass with associated erythema, pain, and paresthesia, which was subsequently found to be extranodal DLBCL with retrograde perineural spread along the infraorbital nerve

Abstracts of National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020

This book presents the abstracts of the papers presented to the Online National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020 (RDMPMC-2020) held on 26th and 27th August 2020 organized by the Department of Metallurgical and Materials Science in Association with the Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, India. Conference Title: National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020Conference Acronym: RDMPMC-2020Conference Date: 26–27 August 2020Conference Location: Online (Virtual Mode)Conference Organizer: Department of Metallurgical and Materials Engineering, National Institute of Technology JamshedpurCo-organizer: Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, IndiaConference Sponsor: TEQIP-