WISE: Efficient WSI selection for active learning in histopathology.

Deep neural network (DNN) models have been applied to a wide variety of medical image analysis tasks, often with the successful performance outcomes that match those of medical doctors. However, given that even minor errors in a model can impact patients' life, it is critical that these models are continuously improved. Hence, active learning (AL) has garnered attention as an effective and sustainable strategy for enhancing DNN models for the medical domain.

Artificial Intelligence-Assisted Daily Quality Control System for the Histologic Diagnosis of Gastrointestinal Endoscopic Biopsies: A 1-Year Experience.

Context.—: Seegene Medical Foundation, one of the major clinical laboratories in South Korea, developed SeeDP, an artificial intelligence (AI)-based postanalytic daily quality control (QC) system that reassesses all gastrointestinal (GI) endoscopic biopsy (EB) slides for incorrect diagnoses.

Objective.

Automatic Tumor Cellularity Measurement: AI-Based Pipeline for Multi-Organ Pathology Imaging.

Tumor Cellularity (TC) is an important metric for assessing organ tumor burden. However, manual cell counting is not feasible due to large volumes of pathology images and inconsistent measurements between pathologists. The PAIP 2023 Challenge aimed to solve this problem using AI.

A predicted-loss based active learning approach for robust cancer pathology image analysis in the workplace.

Background: Convolutional neural network-based image processing research is actively being conducted for pathology image analysis. As a convolutional neural network model requires a large amount of image data for training, active learning (AL) has been developed to produce efficient learning with a small amount of training data. However, existing studies have not specifically considered the characteristics of pathological data collected from the workplace.

Improving quality control in the routine practice for histopathological interpretation of gastrointestinal endoscopic biopsies using artificial intelligence.

Background: Colorectal and gastric cancer are major causes of cancer-related deaths. In Korea, gastrointestinal (GI) endoscopic biopsy specimens account for a high percentage of histopathologic examinations. Lack of a sufficient pathologist workforce can cause an increase in human errors, threatening patient safety.

Overexpression of protein is closely related to triple-negative breast cancer.

Purpose: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with a poor prognosis and a lack of targeted therapy. Overexpression of is thought to be associated with this aggressive subtype of cancer. Here, we performed a comprehensive analysis and assessed the association between overexpression of and TNBC.

MixPatch: A New Method for Training Histopathology Image Classifiers.

CNN-based image processing has been actively applied to histopathological analysis to detect and classify cancerous tumors automatically. However, CNN-based classifiers generally predict a label with overconfidence, which becomes a serious problem in the medical domain. The objective of this study is to propose a new training method, called MixPatch, designed to improve a CNN-based classifier by specifically addressing the prediction uncertainty problem and examine its effectiveness in improving diagnosis performance in the context of histopathological image analysis.

A loss-based patch label denoising method for improving whole-slide image analysis using a convolutional neural network.

This paper proposes a deep learning-based patch label denoising method (LossDiff) for improving the classification of whole-slide images of cancer using a convolutional neural network (CNN). Automated whole-slide image classification is often challenging, requiring a large amount of labeled data. Pathologists annotate the region of interest by marking malignant areas, which pose a high risk of introducing patch-based label noise by involving benign regions that are typically small in size within the malignant annotations, resulting in low classification accuracy with many Type-II errors.

Diagnostic Limitation of Fine-Needle Aspiration (FNA) on Indeterminate Thyroid Nodules Can Be Partially Overcome by Preoperative Molecular Analysis: Assessment of RET/PTC1 Rearrangement in BRAF and RAS Wild-Type Routine Air-Dried FNA Specimens.

Molecular markers are helpful diagnostic tools, particularly for cytologically indeterminate thyroid nodules. Preoperative rearrangement analysis in and wild-type indeterminate thyroid nodules would permit the formulation of an unambiguous surgical plan. Cycle threshold values according to the cell count for detection of the rearrangement by real-time reverse transcription-polymerase chain reaction (RT-PCR) using fresh and routine air-dried TPC1 cells were evaluated.

Cytomorphological findings and histological correlation of low-grade cribriform cystadenocarcinoma of salivary gland in fine-needle aspiration: a case study.

Low-grade cribriform cystadenocarcinoma (LGCCC) of the salivary gland is a rare tumor. We report the cytologic features and histologic correlation of a patient with LGCCC. A 57-year-old man had a hardly palpable, nontender mass in the right cheek area followed over nine months.

A Case of Multifocal Papillary Thyroid Carcinoma Consisting of One Encapsulated Follicular Variant with BRAF K601E Mutation and Three Conventional Types with BRAF V600E Mutation.

Multifocal papillary thyroid carcinoma (mPTC) comprises about 20-30% of PTC. In mPTC, individual tumor foci can be identical or frequently composed of different histological types including follicular, solid, tall-cell or conventional patterns. We report a case of mPTC consisting of one encapsulated follicular variant of papillary thyroid carcinoma (FVPTC) and three conventional PTCs in a 44-year-old woman.

Primary pure squamous cell carcinoma of the thyroid: report and histogenic consideration of a case involving a BRAF mutation.

Primary squamous cell carcinoma of the thyroid (SCC-T) is extremely rare. Its clinical presentation is similar to that of anaplastic carcinoma. Metastasis or extension from the head and neck area should be ruled out, as patients with SCC-T have a poorer prognosis than patients who have a thyroid extension from an adjacent tumor.

Therapy-related acute leukemia with mixed phenotype and t(9;22)(q32;q11.2): a case report and review of the literature.

Therapy-related acute leukemia showing mixed phenotype is extremely rare. We report a 49-year-old woman who presented with palpable masses in her neck and back. She had received systemic chemotherapy (adriamycin and cisplatin) and radiotherapy for endometrial adenocarcinoma 7 years before.

Fluoroscopy and sonographic guided injection of obliquus capitis inferior muscle in an intractable occipital neuralgia.

Occipital neuralgia is a form of headache that involves the posterior occiput in the greater or lesser occipital nerve distribution. Pain can be severe and persistent with conservative treatment. We present a case of intractable occipital neuralgia that conventional therapeutic modalities failed to ameliorate.