Online ISSN: 2515-8260

Keywords : Leukemia

Classification of Leukemia Using Convolution Neural Network

Dr. T. C. Kalaiselvi; D.Santhosh Kumar; K.S. Subhashri; S.M. Siddharth

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 1286-1293

The death caused by Leukemia has been ranked in the top ten most dangerous mortality cause for the human being. There are numerous reasons and causes, in spite of the causes and reasons the profound problem is the slow decision-making process which delays the time required to proceed with medical treatment for the patients. That’s why the enhanced medical support process has become necessary for the classification of leukemia. The four different types of Leukemia are as follows Myeloid Leukemia where we have acute and chronic subcategories and in the same way, it goes for the myeloid type as well, these affect various cells and systems such as the blood cells, bone marrow, lymphatic system and which causes the death of patients. The proposed method improves the CML, CLL, AML and ALL characteristic accuracy by scanning color and textural features from the blood image using image processing and to aid in the grouping of CML, CLL, AML and ALL. The following technique proposes a quantitative microscopic approach toward the grouping of blood sample images. A model using Modified Convolution Neural Network (CNN) architecture is used to optimize the classification process. Based on optimized feature space, a CNN model with various kernel functions (filters) used to abstract the features from the pixel values. The proposed method is tested using nearly 10000 microscopic blood images. The outcome confirmed that the accuracy of the classification using blood sampled images which was up to 98%.

Leukemia Recurrence Exclusively in the Breast after Stem Cell Transplant

Naziya Samreen; Shahrukh K. Hashmi; Amy Lynn Conners; Asha Bhatt; Katrina N. Glazebrook

European Journal of Molecular & Clinical Medicine, 2018, Volume 5, Issue 1, Pages 41-45

Introduction: Leukemic involvement of the breast is extremely rare but constitutes an oncologic emergency. Imaging findings of T-Cell acute lymphoblastic leukemia (T-ALL) recurrence in the breasts have not been previously described. Case Description: Patient is a 25 year old female who presented with symptoms of superior vena cava (SVC) obstruction secondary to a mediastinal mass status post biopsy demonstrating T-ALL, which was cluster of differentiation 3 (CD3) positive and B-cell lymphoma 2 (BCL-2), and 80% Ki-67 positive. She was treated with chemotherapy and post-treatment positron emission tomography/computed tomography (PET/CT) demonstrated resolution of mediastinal mass, with no evidence of distant disease. She underwent allogeneic hematopoietic stem cell transplant (HSCT) in first remission. Seven months post-HSCT, patient presented with a large area of tender swelling of both the breasts with biopsy demonstrating relapsed T-ALL. Radiologic findings showed bilateral breast masses on ultrasound and mammogram, which were hypermetabolic on PET/CT. Conclusions: Breast involvement in leukemia recurrence, a very rare entity, can present with palpable masses. Mammographic findings in leukemia can include masses or architectural distortion, they are typically hyperechoic on ultrasound, and can have marked uptake on PET/CT. Oncologists, primary care providers and radiologists should be aware of leukemia presentations in the breast for prompt referral for urgent management.