Development of multiple AI pipelines that predict neoadjuvant chemotherapy response of breast cancer using H&E-stained tissues.

In recent years, the treatment of breast cancer has advanced dramatically and neoadjuvant chemotherapy (NAC) has become a common treatment method, especially for locally advanced breast cancer. However, other than the subtype of breast cancer, no clear factor indicating sensitivity to NAC has been identified. In this study, we attempted to use artificial intelligence (AI) to predict the effect of preoperative chemotherapy from hematoxylin and eosin images of pathological tissue obtained from needle biopsies prior to chemotherapy.

Prediction of non-muscle invasive bladder cancer recurrence using machine learning of quantitative nuclear features.

Non-muscle invasive bladder cancer (NMIBC) generally has a good prognosis; however, recurrence after transurethral resection (TUR), the standard primary treatment, is a major problem. Clinical management after TUR has been based on risk classification using clinicopathological factors, but these classifications are not complete. In this study, we attempted to predict early recurrence of NMIBC based on machine learning of quantitative morphological features.

Prediction of early recurrence of hepatocellular carcinoma after resection using digital pathology images assessed by machine learning.

Hepatocellular carcinoma (HCC) is a representative primary liver cancer caused by long-term and repetitive liver injury. Surgical resection is generally selected as the radical cure treatment. Because the early recurrence of HCC after resection is associated with low overall survival, the prediction of recurrence after resection is clinically important.

Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach.

Machine learning systems have recently received increased attention for their broad applications in several fields. In this study, we show for the first time that histological types of breast tumors can be classified using subtle morphological differences of microenvironmental myoepithelial cell nuclei without any direct information about neoplastic tumor cells. We quantitatively measured 11661 nuclei on the four histological types: normal cases, usual ductal hyperplasia and low/high grade ductal carcinoma in situ (DCIS).

Pathological Diagnosis of Gastric Cancers with a Novel Computerized Analysis System.

Background: Recent studies of molecular biology have provided great advances for diagnostic molecular pathology. Automated diagnostic systems with computerized scanning for sampled cells in fluids or smears are now widely utilized. Automated analysis of tissue sections is, however, very difficult because they exhibit a complex mixture of overlapping malignant tumor cells, benign host-derived cells, and extracellular materials.

A novel method for morphological pleomorphism and heterogeneity quantitative measurement: Named cell feature level co-occurrence matrix.

Background: Recent developments in molecular pathology and genetic/epigenetic analysis of cancer tissue have resulted in a marked increase in objective and measurable data. In comparison, the traditional morphological analysis approach to pathology diagnosis, which can connect these molecular data and clinical diagnosis, is still mostly subjective. Even though the advent and popularization of digital pathology has provided a boost to computer-aided diagnosis, some important pathological concepts still remain largely non-quantitative and their associated data measurements depend on the pathologist's sense and experience.

Mitotic figure recognition: agreement among pathologists and computerized detector.

Despite the prognostic importance of mitotic count as one of the components of the Bloom-Richardson grade, several studies have found that pathologists' agreement on the mitotic grade is fairly modest. Collecting a set of more than 4,200 candidate mitotic figures, we evaluate pathologists' agreement on individual figures, and train a computerized system for mitosis detection, comparing its performance to the classifications of three pathologists. The system's and the pathologists' classifications are based on evaluation of digital micrographs of hematoxylin and eosin stained breast tissue.

Are the votes of ethics committees in Germany for the protection of clinical study trial subjects "sovereign acts?".

A sudden paradigm shift has resulted in governmental measures that greatly impact the scope in which the ethics committees in Germany can perform their task of providing expert opinions for clinical research. The so-called "revaluation" of the Medical Device Law Deutsches Medizinproduktegesetz-MPG) is, in our opinion, not based on sound political and professional judgment. In accordance with the changed regulations, ethics committees are now seen as being sub-organs of the state medical associations or the medical faculties and are therefore official authorities.

Mitotic index of invasive breast carcinoma. Achieving clinically meaningful precision and evaluating tertial cutoffs.

Context: Mitotic figure counts are related to breast cancer behavior but have not been sufficiently reproducible to be accepted for clinical decision-making.

Objective: To improve reproducibility and accuracy of the mitotic count.

Design: Mitotic index (MI) was defined as the mitotic cell count per 10 high-power fields (HPFs), an area 0.

Swiss psychiatrists beliefs and attitudes about cannabis risks in psychiatric patients: ideologically determined or evidence-based?

The objective of this survey was to assess the beliefs of Swiss psychiatrists about the risks associated with cannabis, and to assess their prohibitive attitudes toward their patients. Eighty-two doctors agreed to fill-up the questionnaire. Cluster analysis retained a 3-cluster solution.