What do we know about inflammatory myofibroblastic tumors? - A systematic review.

BACKGROUND: Inflammatory myofibroblastic tumors (IMTs) are rare intermediate-grade neoplasms that have a high recurrence rate after excision and exhibit low metastatic potential. These tumors contain proliferating neoplastic, fibroblastic and myofibroblastic cells, and are also characterized by chronic inflammatory infiltration by lymphocytes, plasma cells, eosinophils, and histiocytes. They belong to the group of inflammatory spindle cell lesions. Some reactive lesions, such as inflammatory pseudotumors, may appear to be IMTs, which makes their differential diagnosis extremely difficult. The aim of this article is to compile the recent information on IMTs to aid in their diagnosis and treatment. METHODS: We reviewed articles published between 2017 and 2021, which were selected from online medical databases. In addition, some earlier articles and latest scientific monographies were analyzed. RESULTS: The terminology used for inflammatory spindle cell lesions seems to be confusing. The terms "inflammatory myofibroblastic tumors" and "inflammatory pseudotumors" are interchangeably used by many scientists. However, a detailed analysis of the development of terminology suggests that the term "inflammatory myofibroblastic tumors" should be used to refer to a neoplastic lesion. CONCLUSIONS: IMTs are rare neoplasms, which have not been investigated in detail due to the difficulty in collecting a large number of cases. Thus, our knowledge about this disease remains unsatisfactory. Recently developed techniques such as next-generation sequencing and computer-aided histopathological diagnosis may be useful in understanding the etiopathology of IMTs, which will help in the selection of the most appropriate therapy for patients.

System for quantitative evaluation of DAB&H-stained breast cancer biopsy digital images (CHISEL).

This study presents CHISEL (Computer-assisted Histopathological Image Segmentation and EvaLuation), an end-to-end system capable of quantitative evaluation of benign and malignant (breast cancer) digitized tissue samples with immunohistochemical nuclear staining of various intensity and diverse compactness. It stands out with the proposed seamless segmentation based on regions of interest cropping as well as the explicit step of nuclei cluster splitting followed by a boundary refinement. The system utilizes machine learning and recursive local processing to eliminate distorted (inaccurate) outlines. The method was validated using two labeled datasets which proved the relevance of the achieved results. The evaluation was based on the IISPV dataset of tissue from biopsy of breast cancer patients, with markers of T cells, along with Warwick Beta Cell Dataset of DAB&H-stained tissue from postmortem diabetes patients. Based on the comparison of the ground truth with the results of the detected and classified objects, we conclude that the proposed method can achieve better or similar results as the state-of-the-art methods. This system deals with the complex problem of nuclei quantification in digitalized images of immunohistochemically stained tissue sections, achieving best results for DAB&H-stained breast cancer tissue samples. Our method has been prepared with user-friendly graphical interface and was optimized to fully utilize the available computing power, while being accessible to users with fewer resources than needed by deep learning techniques.

Prenatal diagnosis of glutaric acidemia type 2 with the use of exome sequencing - an up-to-date review and new case report.

INTRODUCTION: Inborn errors of metabolism (IEM) also called metabolic diseases constitute a large and heterogenous group of disorders characterized by a failure of essential cellular functions. Antenatal manifestation of IEM is absent or nonspecific, which makes prenatal diagnosis challenging. Glutaric acidemia type 2 (GA2) is a rare metabolic disease clinically manifested in three different ways: neonatal-onset with congenital anomalies, neonatal-onset without congenital anomalies and late-onset. Neonatal forms are usually lethal. Congenital anomalies present on prenatal ultrasound as large, hyperechoic or cystic kidneys with reduced amniotic fluid volume. MATERIAL AND METHODS: We present a systematic literature review describing prenatal diagnosis of GA2 and a new prenatal case. RESULTS: Ten prenatally diagnosed cases of GA2 have been published to date, mainly based on biochemical methods. New case of GA2 was diagnosed using exome sequencing method. DISCUSSION: All prenatal cases from literature review had positive history of GA2 running in the family. In our study trio exome sequencing was performed in case of fetal hyperechoic kidneys without a history of GA2. Consequently, we were able to identify two novel pathogenic variants of the ETFDH gene and to indicate their parental origin. SUMMARY: Exome sequencing approach used in case of fetal hyperechoic kidneys allows to identify pathogenic variants without earlier knowledge of the precise genetic background of the disease. Hyperechoic, enlarged kidneys could be one of the clinical features of metabolic diseases. After exclusion of chromosomal abnormalities, urinary tract obstruction and intrauterine infections, glutaric acidemia type 2 and number of monogenic disorders should be consider.