Fast-Track Development and Multi-Institutional Clinical Validation of an Artificial Intelligence Algorithm for Detection of Lymph Node Metastasis in Colorectal Cancer.

Lymph node metastasis (LNM) detection can be automated using artificial intelligence (AI)-based diagnostic tools. Only limited studies have addressed this task for colorectal cancer (CRC). This study aimed to develop of a clinical-grade digital pathology tool for LNM detection in CRC using the original fast-track framework. The training cohort included 432 slides from one department. A segmentation algorithm detecting 8 relevant tissue classes was trained. The test cohorts consisted of materials from 5 pathology departments digitized by 4 different scanning systems. A high-quality, large training data set was generated within 7 days and a minimal amount of annotation work using fast-track principles. The AI tool showed very high accuracy for LNM detection in all cohorts, with sensitivity, negative predictive value, and specificity ranges of 0.980 to 1.000, 0.997 to 1.000, and 0.913 to 0.990, correspondingly. Only 5 of 14,460 analyzed test slides with tumor cells over all cohorts were classified as false negative (3/5 representing clusters of tumor cells in lymphatic vessels). A clinical-grade tool was trained in a short time using fast-track development principles and validated using the largest international, multi-institutional, multiscanner cohort of cases to date, showing very high precision for LNM detection in CRC. We are releasing a part of the test data sets to facilitate academic research.

Addition of seminal plasma proteins effecting the in vitro kinetic properties of canine spermatozoa.

The objective of this study is to evaluate the changes in the motility and kinetic patterns of canine spermatozoa, capacitated and decapacitated, after the addition of seminal plasma protein fractions with different molecular weight. It has been proposed that proteins in seminal plasma support the survival of the spermatozoa and exert a dual effect: capacitation and decapacitation. The seminal plasma from fresh ejaculates was subjected to chromatographic separation and four protein fractions were obtained. Computer-assisted sperm analysis was used to determine the sperm subpopulations with specific motion and kinetic characteristics after incubation with each of the four protein fractions. Two-dimensional electrophoresis of the fractions that exhibit a significant effect on the capacitation and decapacitation was performed. By sperm class analyser, capacitation changes were observed in the sperm subpopulation with a high curvilinear velocity and amplitude of lateral head displacement incubated with the seminal plasma protein fraction with a high molecular weight, which was also reflected in the decreased linearity, straightness, and progressive motility. The sperm subpopulation incubated with the seminal plasma protein fraction with a low molecular weight seemed to undergo a process of decapacitation (decreasing of the curvilinear velocity, increasing of the linearity, straightness and showing progressive motility). Despite their ample panorama of actions, the role of seminal plasma proteins regarding capacitation and decapacitation is still undetermined.