A Rare Case of a Metastatic Malignant Abrikossoff Tumor

Abrikossoff tumor, also called granular cell tumor (GCT), is a neoplasm of the soft tissues which is most commonly a solitary, painless, and benign tumor. However, 2% of Abrikossoff tumors can be malignant. We report here the case of a 75-year-old male who presented a local recurrence of Abrikossoff tumor of the left thigh. The anatomopathological analysis concluded to a malignant GCT, and the F-18 fluorodeoxyglucose positron emission tomography showed multiple lesions in the lymph nodes and bones. The potential conversion to malignancy should alert practitioners because of the extremely poor prognosis. The diagnosis of malignant granular cell tumor should be based on a bundle of clinical and histological features and not solely on histologic features because of the challenging distinction between malignant and benign tumors due to the lack of well-defined criteria for the diagnosis of malignancy. Large size and recurrence are the most important clinical features predicting malignant behavior. Patients with a history of Abrikossoff tumor should be followed closely to monitor recurrence and malignant transformation. The apparent originality of our observation – which could lie in the evolution of a GCT tumor, initially considered as benign, to a malignant form – has to be challenged regarding the issue of classifying some cases according to the classical “benign” and “malignant” dichotomy.

Neurologic Complications of Radiation Therapy and Chemotherapy

Separate from neurosurgery, radiation and chemotherapy have been used in the treatment of malignant and benign tumors of the brain and spinal cord. Although effective, the treatments can be associated with serious neurologic adverse effects. This chapter reviews the adverse effects of these treatments. External beam radiation therapy (RT) is a common mode of radiation and is most effective for high-grade glioma. Intensity-modulated RT and stereotactic radiosurgery are usually reserved for pituitary tumors, skull-base masses, metastatic disease, and primary parenchymal tumors.

A novel optical needle probe for deep learning-based tissue elasticity characterization

The distinction between malignant and benign tumors is essential to the treatment of cancer. The tissue's elasticity can be used as an indicator for the required tissue characterization. Optical coherence elastography (OCE) probes have been proposed for needle insertions but have so far lacked the necessary load sensing capabilities. We present a novel OCE needle probe that provides simultaneous optical coherence tomography (OCT) imaging and load sensing at the needle tip. We demonstrate the application of the needle probe in indentation experiments on gelatin phantoms with varying gelatin concentrations. We further implement two deep learning methods for the end-toend sample characterization from the acquired OCT data. We report the estimation of gelatin sample weight ratios [wt%] in unseen samples with a mean error of 1.21 ± 0.91 wt%. Both evaluated deep learning models successfully provide sample characterization with different advantages regarding the accuracy and inference time.

“ROLE OF SPECTROSCOPY IN MAGNETIC RESONANCE IMAGING: A CLINICAL REVIEW”

Magnetic Resonance Spectroscopy (MRS) is used in diagnostic imaging for disease metabolism evaluation. The H MRS is highly used because of the abundance, high sensitivity, etc. The various clinical implementation includes whole-brain MRS is used in measuring metabolites of different brain areas simultaneously. The breast MRS is used in malignant and benign tumors differentiation by the total choline compound. The prostate MRS is used to map the metabolites like citrate, choline, and creatinine. For spinal cord MRS, the myoinositol and N acetyl aspartate were 31 23 1 considered markers for various diseases. The MRS uses nuclei like P, Na, and H for metabolic and biochemical evaluation of cardiac muscles. The liver MRS spectrum has mainly methylene group of lipid, methyl groups of choline, and water. The MRS measures choline, creatinine, lactate, and lipid peaks in uterine leiomyoma and myometrium. Hence there are organ-specic metabolites used as a reference to map the metabolic process by using spectroscopy, making it one of the commonly preferred technique.

Analysis of the Incidence and Clinical Features of Colorectal Nonadenocarcinoma in Korea: A National Cancer Registry-Based Study

Purpose: Although most colorectal malignancies are adenocarcinomas from mucosa, various types of malignant and benign tumors can develop. Due to extremely low incidence, little research has been conducted. The purpose was to assess incidence and compare it according to demographic factors.Methods: Data from the Korea National Cancer Registry from 2007 to 2016 were used. The crude incidence, age-standard incidence rate (ASR) of colorectal nonadenocarcinomas were calculated.Results: Over 11 years, there were 267,142 patients with colorectal malignancies. The patients of 14,495 (5.43%) were diagnosed with nonadenocarcinoma. The ASR was 2.52 per 100,000 in men and 1.56 in women. Lesions were classified according to histologic categories; neuroendocrine tumor (NET) was the most common malignancy (10,919 [75.33%]). Nonadenocarcinoma was the most common in 40s and 50s (40 to 49 years, 3,530 [24.35%]; 50 to 59 years, 3,991 [27.53%]). Lymphoma was high (54.46%) in patients in teenagers. Proportion of NET decreased with age and that of carcinoma increased with age. Carcinoma, sarcoma, and lymphoma were more common among men and melanoma was more common among women. The most common site was the rectum (11,066 [76.34%]). Lymphoma occurred more frequently in proximal colon. Melanoma, gastrointestinal stromal tumor, and NET occurred mostly in rectum. A total of 10,155 patients (70.06%) were classified as having localized disease.Conclusion: This study is meaningful as it is the first study to examine incidence of colorectal nonadenocarcinoma. Differences in incidence of different lesions based on demographic factors were identified. This study will play a role in cancer prevention and diagnosis projects.

Ovarian papilloma

By its structure, the papilloma is the borderline between malignant and benign tumors; but in clinical terms it is wrong to classify it as a type of malignant tumor.

KPNA2 expression is a potential marker for differential diagnosis between osteosarcomas and other malignant bone tumor mimickers

Background Karyopherin α 2 (KPNA2), a member of the Karyopherin α family, has been observed in several cancers but lack substantial investigation in malignant bone tumors. The purpose of the current study was to evaluate KPNA2 expression level and its utility as a novel diagnostic biomarker in osteosarcomas and their malignant bone tumor mimickers, such as chondrosarcomas and Ewing sarcomas.Method We investigated the expression of KPNA2 protein by immunohistochemistry on paraffin embedded surgical specimens from 217 patients with malignant and benign tumors of bone, including 81 osteosarcomas, 42 chondrosarcomas, 9 Ewing sarcomas, 28 osteoid osteoma, 20 osteochondroma and 37 Chondroblastoma. Immunoreactivity was scored semi quantitatively based on stain extent and intensity.Results Seventy one of 81 (87.7%) osteosarcomas, zero of 42 (0%) chondrosarcomas and one of 9 (11.1%) Ewing sarcomas showed immunoreactivity for KPNA2. Negative KPNA2 expression was observed in all of benign bone tumors. Much more positive expression of KPNA2 was found in osteosarcomas as compared with chondrosarcomas and Ewing sarcomas. The sensitivity and specificity of KPNA2 immuno-expression for osteosarcoma was 87.7% and 100%, respectively. In several subtypes of osteosarcomas, immunohistochemical expression of KNA2 was more frequent in osteoblastic (94.5%), with 39 (70.9%) showing strong-intensity staining. KPNA2 positivity was observed in eleven of 13 (84.6%) chondroblastic, three of 6 (50%) fibroblastic, three of 4 (75%) telangiectatic and two of 3 (66.7%) giant cell-rich osteosarcoma. Stronger-intensity staining was observed in osteoblastic osteosarcoma.Conclusion KPNA2 is most frequently expressed in osteosarcomas, particularly in osteoblastic and chondroblastic tumors, but is rarely positive in chondrosarcomas and Ewing sarcomas. This feature may have diagnostic value since it is very useful for distinguishing between osteosarcomas and other bone sarcomas mimickers. This report supports KPNA2 as a novel marker for the diagnosis of osteosarcoma.

Tabu Search and Machine-Learning Classification of Benign and Malignant Proliferative Breast Lesions

Breast cancer is the most diagnosed cancer among women around the world. The development of computer-aided diagnosis tools is essential to help pathologists to accurately interpret and discriminate between malignant and benign tumors. This paper proposes the development of an automated proliferative breast lesion diagnosis based on machine-learning algorithms. We used Tabu search to select the most significant features. The evaluation of the feature is based on the dependency degree of each attribute in the rough set. The categorization of reduced features was built using five machine-learning algorithms. The proposed models were applied to the BIDMC-MGH and Wisconsin Diagnostic Breast Cancer datasets. The performance measures of the used models were evaluated owing to five criteria. The top performing models were AdaBoost and logistic regression. Comparisons with others works prove the efficiency of the proposed method for superior diagnosis of breast cancer against the reviewed classification techniques.