Extracellular Competing Endogenous RNA Networks Reveal Key Regulators of Early Amyloid Pathology Propagation in Alzheimer's Disease.

Extracellular vesicles (EVs) are small capsular bodies released by cells, mediating responses in intercellular communication. The role of EVs in Aβ pathology spreading in the Alzheimer's disease (AD) brain has been evidenced, although whether this occurs due to the co-transportation of Aβ peptides or contribution of other factors, such as EV-associated transcripts, remains uncertain. In vitro studies of miRNA cargo in neuron-derived extracellular vesicles (NDEVs) show that Aβ hyperexpression alters the transcriptomic profile; however, it is not clear to what extent this causes changes at the organ level.

Robust, credible, and interpretable AI-based histopathological prostate cancer grading.

Background: Prostate cancer (PCa) is among the most common cancers in men and its diagnosis requires the histopathological evaluation of biopsies by human experts. While several recent artificial intelligence-based (AI) approaches have reached human expert-level PCa grading, they often display significantly reduced performance on external datasets. This reduced performance can be caused by variations in sample preparation, for instance the staining protocol, section thickness, or scanner used.

Noninvasive Autopsy-Validated Tumor Probability Maps Identify Glioma Invasion Beyond Contrast Enhancement.

Background And Objectives: This study identified a clinically significant subset of patients with glioma with tumor outside of contrast enhancement present at autopsy and subsequently developed a method for detecting nonenhancing tumor using radio-pathomic mapping. We tested the hypothesis that autopsy-based radio-pathomic tumor probability maps would be able to noninvasively identify areas of infiltrative tumor beyond traditional imaging signatures.

Methods: A total of 159 tissue samples from 65 subjects were aligned to MRI acquired nearest to death for this retrospective study.

Quantitative Histomorphometric Features of Prostate Cancer Predict Patients Who Biochemically Recur Following Prostatectomy.

Prostate cancer is the most commonly diagnosed cancer in men, accounting for 27% of the new male cancer diagnoses in 2022. If organ-confined, removal of the prostate through radical prostatectomy is considered curative; however, distant metastases may occur, resulting in a poor patient prognosis. This study sought to determine whether quantitative pathomic features of prostate cancer differ in patients who biochemically experience biological recurrence after surgery.

Expansion-enhanced super-resolution radial fluctuations enable nanoscale molecular profiling of pathology specimens.

Expansion microscopy physically enlarges biological specimens to achieve nanoscale resolution using diffraction-limited microscopy systems. However, optimal performance is usually reached using laser-based systems (for example, confocal microscopy), restricting its broad applicability in clinical pathology, as most centres have access only to light-emitting diode (LED)-based widefield systems. As a possible alternative, a computational method for image resolution enhancement, namely, super-resolution radial fluctuations (SRRF), has recently been developed.

Comparison of a machine and deep learning model for automated tumor annotation on digitized whole slide prostate cancer histology.

One in eight men will be affected by prostate cancer (PCa) in their lives. While the current clinical standard prognostic marker for PCa is the Gleason score, it is subject to inter-reviewer variability. This study compares two machine learning methods for discriminating between cancerous regions on digitized histology from 47 PCa patients.

Diffusion Restriction Comparison between Gleason 4 Fused Glands and Cribriform Glands within Patient Using Whole-Mount Prostate Pathology as Ground Truth.

The presence and extent of cribriform patterned Gleason 4 (G4) glands are associated with poor prognosis following radical prostatectomy. This study used whole-mount prostate histology and multiparametric magnetic resonance imaging (MP-MRI) to evaluate diffusion differences in G4 gland morphology. Fourty-eight patients underwent MP-MRI prior to prostatectomy, of whom 22 patients had regions of both G4 cribriform glands and G4 fused glands (G4CG and G4FG, respectively).

Multi-Site Concordance of Diffusion-Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness.

Background: Diffusion-weighted imaging (DWI) is commonly used to detect prostate cancer, and a major clinical challenge is differentiating aggressive from indolent disease.

Purpose: To compare 14 site-specific parametric fitting implementations applied to the same dataset of whole-mount pathologically validated DWI to test the hypothesis that cancer differentiation varies with different fitting algorithms.

Study Type: Prospective.

Cardiac Magnetic Resonance for Early Detection of Radiation Therapy-Induced Cardiotoxicity in a Small Animal Model.

Background: Over half of all cancer patients receive radiation therapy (RT). However, radiation exposure to the heart can cause cardiotoxicity. Nevertheless, there is a paucity of data on RT-induced cardiac damage, with limited understanding of safe regional RT doses, early detection, prevention and management.

Radio-pathomic mapping model generated using annotations from five pathologists reliably distinguishes high-grade prostate cancer.

Our study predictively maps epithelium density in magnetic resonance imaging (MRI) space while varying the ground truth labels provided by five pathologists to quantify the downstream effects of interobserver variability. Clinical imaging and postsurgical tissue from 48 recruited prospective patients were used in our study. Tissue was sliced to match the MRI orientation and whole-mount slides were stained and digitized.

Radiomic Features of Multiparametric MRI Present Stable Associations With Analogous Histological Features in Patients With Brain Cancer.

Magnetic resonance (MR)-derived radiomic features have shown substantial predictive utility in modeling different prognostic factors of glioblastoma and other brain cancers. However, the biological relationship underpinning these predictive models has been largely unstudied, and the generalizability of these models had been called into question. Here, we examine the localized relationship between MR-derived radiomic features and histology-derived "histomic" features using a data set of 16 patients with brain cancer.

Association Between Knee Anatomic Metrics and Biomechanics for Male Soldiers Landing With Load.

Background: Anterior cruciate ligament (ACL) injury is a military occupational hazard that may be attributed to an individual's knee biomechanics and joint anatomy. This study sought to determine if greater flexion when landing with load resulted in knee biomechanics thought to decrease ACL injury risk and whether knee biomechanics during landing relate to knee anatomic metrics.

Hypothesis: Anatomic metrics regarding the slope and concavity of the tibial plateau will exhibit a significant relation to the increased anterior shear force on the knee and decreased knee flexion posture during landing with body-borne load.

Atlas-based algorithm for automatic anatomical measurements in the knee.

We present an algorithm for automatic anatomical measurements in tomographic datasets of the knee. The algorithm uses a set of atlases, each consisting of a knee image, surface segmentations of the bones, and locations of landmarks required by the anatomical metrics. A multistage volume-to-volume and surface-to-volume registration is performed to transfer the landmarks from the atlases to the target volume.

Cone-beam CT measurements of distal tibio-fibular syndesmosis in asymptomatic uninjured ankles: does weight-bearing matter?

Objective: To evaluate the influence of weight-bearing (WB) load in standard axial ankle syndesmotic measurements using cone beam CT (CBCT) examination of asymptomatic uninjured ankles.

Materials And Methods: In this IRB approved, prospective study, patients with previous unilateral ankle fractures were recruited. We simultaneously scanned the injured ankles and asymptomatic contralateral ankles of 27 patients in both WB and NWB modes.

Penalized-Likelihood Reconstruction With High-Fidelity Measurement Models for High-Resolution Cone-Beam Imaging.

We present a novel reconstruction algorithm based on a general cone-beam CT forward model, which is capable of incorporating the blur and noise correlations that are exhibited in flat-panel CBCT measurement data. Specifically, the proposed model may include scintillator blur, focal-spot blur, and noise correlations due to light spread in the scintillator. The proposed algorithm (GPL-BC) uses a Gaussian Penalized-Likelihood objective function, which incorporates models of blur and correlated noise.

Modeling and evaluation of a high-resolution CMOS detector for cone-beam CT of the extremities.

Purpose: Quantitative assessment of trabecular bone microarchitecture in extremity cone-beam CT (CBCT) would benefit from the high spatial resolution, low electronic noise, and fast scan time provided by complementary metal-oxide semiconductor (CMOS) x-ray detectors. We investigate the performance of CMOS sensors in extremity CBCT, in particular with respect to potential advantages of thin (<0.7 mm) scintillators offering higher spatial resolution.

Articular surface segmentation using active shape models for intraoperative implant assessment.

Purpose: In orthopedic surgeries, it is important to avoid intra-articular implant placements, which increase revision rates and the risk of arthritis. In order to support the intraoperative assessment and correction of surgical implants, we present an automatic detection approach using cone-beam computed tomography (CBCT).

Methods: Multiple active shape models (ASM) with specified articular surface regions are used to isolate the joint spaces.

Intra-operative assessment of fractured articular surfaces in cone beam CT image data.

Purpose: The assessment of intra-operatively acquired volumetric data is a difficult and often time-consuming task, which demands a new set of skills from the surgeons. In the case of orthopedic surgeries such as the treatment of calcaneal fractures, the correctness of the reduction of the bone fragments can be verified with the help of C-arm CT volumetric images. For an accurate intra-operative assessment of the displaced fragments, an automatic segmentation of the articular surfaces and color-coded visualization was developed.

Intra-operative adjustment of standard planes in C-arm CT image data.

Purpose: With the help of an intra-operative mobile C-arm CT, medical interventions can be verified and corrected, avoiding the need for a post-operative CT and a second intervention. An exact adjustment of standard plane positions is necessary for the best possible assessment of the anatomical regions of interest but the mobility of the C-arm causes the need for a time-consuming manual adjustment. In this article, we present an automatic plane adjustment at the example of calcaneal fractures.