Clinical, hematological and cytogenetic profile in fibroblast growth factor receptor 1 rearranged hematoloymphoid malignancies

The background of this study is FGFR1 belongs to a family of four, high-affinity receptor tyrosine kinase and is a legitimate oncogene associated with uterine, cervical, prostate, bladder, colorectal and lung cancers. It is rarely concomitant in myeloid and lymphoid neoplasms but has an aggressive clinical course with a high mortality rate when present. Cytogenetic abnormalities involving the FGFR1 gene is most frequently observed in AML, MPN with eosinophilia, T-ALL and T-LBL with ZMYM2 gene being the most common fusion partner. Methods of this study was to authors report a series of 4 cases with FGFR1 rearrangements. Results is three patients presented as T-cell Lymphoblastic lymphoma (T-LBL) and one as mixed phenotype acute leukemia (MPAL). The T-LBL cases harboured the FGFR1/ ZMYM2 fusion and the MPAL case harbored the CNTRL/FGFR1 fusion as identified by conventional cytogenetics and confirmed by molecular studies. Conclusion is authors herewith describe the clinical, biochemical, molecular and cytogenetic features observed in these cases

Artificially Intelligent Readers: An Adaptive Framework for Original Handwritten Numerical Digits Recognition with OCR Methods

Advanced artificial intelligence (AI) techniques have led to significant developments in optical character recognition (OCR) technologies. OCR applications, using AI techniques for transforming images of typed text, handwritten text, or other forms of text into machine-encoded text, provide a fair degree of accuracy for general text. However, even after decades of intensive research, creating OCR with human-like abilities has remained evasive. One of the challenges has been that OCR models trained on general text do not perform well on localized or personalized handwritten text due to differences in the writing style of alphabets and digits. This study aims to discuss the steps needed to create an adaptive framework for OCR models, with the intent of exploring a reasonable method to customize an OCR solution for a unique dataset of English language numerical digits were developed for this study. We develop a digit recognizer by training our model on the MNIST dataset with a convolutional neural network and contrast it with multiple models trained on combinations of the MNIST and custom digits. Using our methods, we observed results comparable with the baseline and provided recommendations for improving OCR accuracy for localized or personalized handwritten text. This study also provides an alternative perspective to generating data using conventional methods, which can serve as a gold standard for custom data augmentation to help address the challenges of scarce data and data imbalance

A retrospective observational study to evaluate the reliability of staging and risk stratification of adolescent and adult patients with Hodgkin's lymphoma registered at the lymphoma clinic of a tertiary cancer center in Western India

Background: The treatment for Hodgkin's lymphoma is based on risk stratification of the disease, which is determined by staging, clinical, and laboratory parameters. The current staging systems are highly prone to error due to overlapping components and inter-observer variability. Objectives: We aimed to assess the reliability of staging and risk stratification performed by the clinicians at our busy multidisciplinary clinic. Materials and Methods: We conducted a retrospective analysis of 115 patients with newly diagnosed Hodgkin's lymphoma at the Tata Memorial Hospital, Mumbai, India, from 2016-2018. Patients who underwent baseline staging and risk stratification in the multidisciplinary lymphoma clinic were included in the analysis. The multidisciplinary lymphoma clinic is a collaboration between medical oncologists, radiation oncologists, nurses, social workers, and patient navigators. The staging and risk stratification performed during the multidisciplinary clinic were compared with those of a team of independent experts from medical oncology, radiation oncology, and nuclear medicine based on standard references (guidelines established by the German Hodgkin Study Group and the Ann Arbor Staging). Results: Discordance rates of 11.3% (n = 13) in disease staging and 7.8% (n = 9) in risk stratification were observed between the multidisciplinary clinic and the independent expert team. In all the discordant cases, there was up-staging of patients by the multidisciplinary clinic; all nine patients in early favorable risk category were misclassified as early unfavorable. The discordance rates were not significant, with a kappa score of 0.841 for staging and 0.855 for risk stratification. Conclusion: Misclassification of patients with Hodgkin's lymphoma based on the staging, and risk stratification may lead to over- or under-treatment. There is a need for a simpler, objective, and technology-driven risk stratification process

BRAFV600E mutation in hairy cell leukemia: A single-center experience

Background: BRAFV600E mutation has been reported as a unique genetic lesion of hairy cell leukemia (HCL), a subset of which lacks this lesion and shows adverse outcomes. Aims: To determine the prevalence of BRAFV600E in HCL from our center and derive clinicopathological correlation, if any. Materials and Methods: A 9-year retrospective analysis of 46 consecutive cases of HCL diagnosed on morphology and immunophenotyping was done. Stained smears were used as samples for amplification refractory mutation system polymerase-chain reaction using fluorescent primers for mutation detection. Results: BRAFV600E mutation was detected in 41/46 patients (89.1%) while absent in control samples of chronic lymphocytic leukemia. Cases mimicking HCL-variant clinically or immunophenotypically too showed the presence of this mutation. HCL with mutated BRAF presented at a younger age. No statistical difference in blood counts, tumor load, and immunophenotype patterns existed among BRAF mutated and unmutated group. Nine patients (45%) with mutated BRAF had residual disease following treatment with cladribine. Conclusion: BRAFV600E mutation analysis has a definitive role in the diagnosis of HCL