CD24 Positive Nucleus Pulposus Cells in Adult Human Intervertebral Discs Maintain a More Notochordal Phenotype Than GD2 Positive Cells.

Background: Notochordal cells (NCs) present in the nucleus pulposus (NP) of the developing human intervertebral disc (IVD) disappear during the first decade of life. This loss coincides with the onset of IVD degeneration, therefore these cells are hypothesized to be important in NP homeostasis. Putative NC-derived (CD24) and progenitor (TIE2/GD2) cell sub-populations have previously been identified in the adult human NP, but their characteristics have yet to be compared.

Improving the prediction of chemotherapy dose-limiting toxicity in colon cancer patients using an AI-CT-based 3D body composition of the entire L1-L5 lumbar spine.

Purpose: Chemotherapy dose-limiting toxicities (DLT) pose a significant challenge in successful colon cancer treatment. Body composition analysis may enable tailored interventions thereby supporting the mitigation of chemotherapy toxic effects. This study aimed to evaluate and compare the effectiveness of using three-dimensional (3D) CT body composition measures from the entire lumbar spine levels (L1-L5) versus a single vertebral level (L3), the current gold standard, in predicting chemotherapy DLT in colon cancer patients.

Healthcare professionals beliefs and priorities for the rehabilitation of patients after ankle fracture surgery: A qualitative study.

Objective: The study aims to understand healthcare professionals' (HCPs) beliefs and practices in the treatment and rehabilitation of patients after ankle fracture surgery, with the goal of informing new rehabilitation interventions based on these insights.

Background: There is considerable variation in postoperative rehabilitation advice given to patients with ankle fractures, leading to inconsistent care. Prior studies have primarily focused on patients' experiences, making it crucial to explore HCPs' perspectives to identify areas for intervention.

Using a new artificial intelligence-aided method to assess body composition CT segmentation in colorectal cancer patients.

Introduction: This study aimed to evaluate the accuracy of our own artificial intelligence (AI)-generated model to assess automated segmentation and quantification of body composition-derived computed tomography (CT) slices from the lumber (L3) region in colorectal cancer (CRC) patients.

Methods: A total of 541 axial CT slices at the L3 vertebra were retrospectively collected from 319 patients with CRC diagnosed during 2012-2019 at a single Australian tertiary institution, Western Health in Melbourne. A two-dimensional U-Net convolutional network was trained on 338 slices to segment muscle, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT).

The Royal College of Radiologists National Vulvar Cancer Audit.

Aims: This audit examined UK vulvar cancer practice from March 2018 to January 2019 and compared it to standards from national and international recommendations. Follow-up data collection in 2020 examined patient outcomes and toxicity.

Materials And Methods: Audit standards were based on Royal College of Radiologists (RCR) guidance and published literature.

Body composition assessment by artificial intelligence can be a predictive tool for short-term postoperative complications in Hartmann's reversals.

Background: Hartmann's reversal, a complex elective surgery, reverses and closes the colostomy in individuals who previously underwent a Hartmann's procedure due to colonic pathology like cancer or diverticulitis. It demands careful planning and patient optimisation to help reduce postoperative complications. Preoperative evaluation of body composition has been useful in identifying patients at high risk of short-term postoperative outcomes following colorectal cancer surgery.

Artificial intelligence measured 3D body composition to predict pathological response in rectal cancer patients.

Background: The treatment of locally advanced rectal cancer (LARC) is moving towards total neoadjuvant therapy and potential organ preservation. Of particular interest are predictors of pathological complete response (pCR) that can guide personalized treatment. There are currently no clinical biomarkers which can accurately predict neoadjuvant therapy (NAT) response but body composition (BC) measures present as an emerging contender.

The association of body composition on chemotherapy toxicities in non-metastatic colorectal cancer patients: a systematic review.

Background: In recent years, certain body composition measures, assessed by computed tomography (CT), have been found to be associated with chemotherapy toxicities. This review aims to explore available data on the relationship between skeletal muscle and adiposity, including visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), intramuscular and intermuscular adipose tissue and their association with chemotherapy toxicity in non-metastatic colorectal cancer (CRC) patients.

Methods: A systematic literature search following PRISMA guidelines was conducted in Medline, Embase, Cochrane and Web of Science, for papers published between 2011 and 2023.

Identification of Differences in Body Composition Measures Using 3D-Derived Artificial Intelligence from Multiple CT Scans across the L3 Vertebra Compared to a Single Mid-Point L3 CT Scan.

Purpose: Body composition analysis in colorectal cancer (CRC) typically utilises a single 2D-abdominal axial CT slice taken at the mid-L3 level. The use of artificial intelligence (AI) allows for analysis of the entire L3 vertebra (non-mid-L3 and mid-L3). The goal of this study was to determine if the use of an AI approach offered any additional information on capturing body composition measures.

Vision-Related Quality of Life and Ocular Parameters in End-Stage Renal Disease Patients Undergoing Hemodialysis.

Purpose: To evaluate the vision-related quality of life (VRQoL) of patients receiving hemodialysis through the assessment of the impact of vision impairment (IVI) questionnaire and ocular parameters, including best-corrected visual acuity (BCVA), intraocular pressure (IOP), and refraction as calculated by spherical equivalent (SE) of each eye.

Methods: Fifty-one patients with end-stage renal disease undergoing hemodialysis at a single center were recruited, and a total of 77 eyes were evaluated. BCVA, IOP, and SE were evaluated before and after hemodialysis (within 30 min).

Can AI-based body composition assessment outperform body surface area in predicting dose-limiting toxicities for colonic cancer patients on chemotherapy?

Purpose: Gold standard chemotherapy dosage is based on body surface area (BSA); however many patients experience dose-limiting toxicities (DLT). We aimed to evaluate the effectiveness of BSA, two-dimensional (2D) and three-dimensional (3D) body composition (BC) measurements derived from Lumbar 3 vertebra (L3) computed tomography (CT) slices, in predicting DLT in colon cancer patients.

Methods: 203 patients (60.

Keratoconus International Consortium (KIC)- advancing keratoconus research.

Clinical Relevance: The Keratoconus International Consortium (KIC) will allow better understanding of keratoconus.

Background: Keratoconus is a disorder characterised by corneal elevation and thinning, leading to reduced vision. The current gaps in understanding of this disease will be discussed and the need for a multi-pronged and multi-centre engagement to enhance our understanding of keratoconus will be highlighted.

Can sarcopenia predict survival in locally advanced rectal cancer patients?

Background: There is mounting evidence that suggests sarcopenia can be used to predict survival outcomes in patients with colon cancer. However, the effect on locally advanced rectal cancer (LARC) is less clear. We sought to determine the association between sarcopenia on Overall Survival and Recurrence-free Survival (OS and RFS) in patients with LARC undergoing multimodal treatment.

The extracellular microenvironment in immune dysregulation and inflammation in retinal disorders.

Inherited retinal dystrophies (IRDs) as well as genetically complex retinal phenotypes represent a heterogenous group of ocular diseases, both on account of their phenotypic and genotypic characteristics. Therefore, overlaps in clinical features often complicate or even impede their correct clinical diagnosis. Deciphering the molecular basis of retinal diseases has not only aided in their disease classification but also helped in our understanding of how different molecular pathologies may share common pathomechanisms.

Comparison of CT derived body composition at the thoracic T4 and T12 with lumbar L3 vertebral levels and their utility in patients with rectal cancer.

Background: Computed tomography (CT) derived body composition measurements of sarcopenia are an emerging form of prognostication in many disease processes. Although the L3 vertebral level is commonly used to measure skeletal muscle mass, other studies have suggested the utilisation of other segments. This study was performed to assess the variation and reproducibility of skeletal muscle mass at vertebral levels T4, T12 and L3 in pre-operative rectal cancer patients.

Exploring the contribution of ARMS2 and HTRA1 genetic risk factors in age-related macular degeneration.

Age-related macular degeneration (AMD) is the leading cause of severe irreversible central vision loss in individuals over 65 years old. Genome-wide association studies (GWASs) have shown that the region at chromosome 10q26, where the age-related maculopathy susceptibility (ARMS2/LOC387715) and HtrA serine peptidase 1 (HTRA1) genes are located, represents one of the strongest associated loci for AMD. However, the underlying biological mechanism of this genetic association has remained elusive.

Developing current procedural terminology codes that describe the work performed by machines.

The "Taxonomy of Artificial Intelligence for Medical Services and Procedures" became part of the Current Procedural Terminology (CPT®) code set effective January 1, 2022. It provides a framework for discrete and differentiable CPT codes which; are consistent with the features of the devices' output, characterize interaction between the device and the physician or other qualified health care professional, and foster appropriate payment. Descriptors include "Assistive", "Augmentative", and "Autonomous".

Assessment of Quality of Life in Rectal Cancer with Organ-Preservation Treatment: Are We There yet?

Rectal cancer is a common cancer and shows an increased incidence with older age. Although the gold standard treatment is surgical excision, minimally invasive approaches are increasingly used and organ preservation is becoming a reasonable approach. The conservative treatment approach includes local excision, external beam radiotherapy and brachytherapy.

Non-genetic risk factors for keratoconus.

Keratoconus is a complex and multifactorial disease and its exact aetiology remains unknown. This current study examined the important environmental risk factors and their association with keratoconus. This study was registered in the PROSPERO International Prospective Register of systematic reviews under registration number CRD42021256792 in 2021.

Accuracy of Machine Learning Assisted Detection of Keratoconus: A Systematic Review and Meta-Analysis.

(1) Background: The objective of this review was to synthesize available data on the use of machine learning to evaluate its accuracy (as determined by pooled sensitivity and specificity) in detecting keratoconus (KC), and measure reporting completeness of machine learning models in KC based on TRIPOD (the transparent reporting of multivariable prediction models for individual prognosis or diagnosis) statement. (2) Methods: Two independent reviewers searched the electronic databases for all potential articles on machine learning and KC published prior to 2021. The TRIPOD 29-item checklist was used to evaluate the adherence to reporting guidelines of the studies, and the adherence rate to each item was computed.

Machine Learning for Health: Algorithm Auditing & Quality Control.

Developers proposing new machine learning for health (ML4H) tools often pledge to match or even surpass the performance of existing tools, yet the reality is usually more complicated. Reliable deployment of ML4H to the real world is challenging as examples from diabetic retinopathy or Covid-19 screening show. We envision an integrated framework of algorithm auditing and quality control that provides a path towards the effective and reliable application of ML systems in healthcare.

Machine learning with a reduced dimensionality representation of comprehensive Pentacam tomography parameters to identify subclinical keratoconus.

Purpose: To investigate the performance of a machine learning model based on a reduced dimensionality parameter space derived from complete Pentacam parameters to identify subclinical keratoconus (KC).

Methods: All 1692 available parameters were obtained from the Pentacam imaging machine on 145 subclinical KC and 122 control eyes. We applied a principal component analysis (PCA) to the complete Pentacam dataset to reduce its parameter dimensionality.

Identification of novel loci influencing refractive error in East Asian populations using an extreme phenotype design.

The global "myopia boom" has raised significant international concerns. Despite a higher myopia prevalence in Asia, previous large-scale genome-wide association studies (GWASs) were mostly based on European descendants. Here, we report a GWAS of spherical equivalent (SE) in 1852 Chinese Han individuals with extreme SE from Guangzhou (631 < -6.

Examining Corneal Tissue Exportation Fee and Its Impact on Equitable Allocation.

Methods: We conducted grounded theory semistructured interviews, purposively inviting participants until themed saturation was met. Sentiment analysis was used to determine opinion.

Results: We interviewed n = 92 global eye tissue and eye bank professionals.

Corneal supply and the use of technology to reduce its demand: A review.

Recovery and access to end-of-life corneal tissue for corneal transplantation, training and research is globally maldistributed. The reasons for the maldistribution are complex and multifaceted, and not well defined or understood. Currently there are few solutions available to effectively address these issues.