Review of MRI radiomic features aids Alzheimer's disease classification and progression modeling in 382 participants.
MRI Scan Finds Alzheimer's Signs Before Memory Loss Starts
This observational review synthesizes findings from 382 participants across three cognitive stages regarding MRI-derived radiomic features. …
New imaging tools might catch Alzheimer's changes years before memory fades.
Preclinical deep learning framework shows improved dose prediction for unseen cancer sites
A Heavy Burden on Doctors
This is a preclinical development study of a deep learning framework for radiotherapy dose prediction. The framework performed comparably to…
A new AI tool can plan radiation doses for many different cancers at once.
TACE plus donafenib and camrelizumab shows improved outcomes in unresectable hepatocellular carcinoma
Liver Cancer Patients May Live Twice as Long With New Combo
This single-center retrospective cohort study compared TACE plus donafenib and camrelizumab to TACE plus donafenib alone in 116 patients wit…
A new combination therapy could nearly double survival time for advanced liver cancer patients.
3D-DXA imaging shows strong correlation with QCT for assessing femoral bone density in international cohorts.
3D-DXA scans match the accuracy of more complex bone density tests.
This cohort study of 537 subjects from Spain, the United States, and Japan compared 3D-DXA imaging to quantitative computed tomography (QCT)…
New data shows 3D-DXA scans match the accuracy of complex CT scans for measuring bone strength, offering a safer, easier way to check bone h…
MELD Graph and 3D-nnUNet Deep Learning Approaches Detect Focal Cortical Dysplasia in Pediatric Drug-Resistant Epilepsy
AI Spots Hidden Brain Lesions in Kids with Epilepsy
This retrospective single-center study evaluated MELD Graph and 3D-nnUNet deep-learning approaches against expert neuroradiological evaluati…
A 6-year-old has seizures. Doctors try two, then three medications.
Systematic evaluation of harmonisation methods reduces variability in multisite MRI volumetric imaging-derived phenotypes
New Scan Fix Helps Compare Brain Changes Across Clinics
This systematic evaluation reviews image-based and statistical harmonisation methods applied to a clinically realistic, multisite, multiscan…
Scientists found a better way to fix differences in brain scans so doctors can track changes accurately.
Deep learning model segments nasal cavity from CT scans with high accuracy in preclinical evaluation.
New AI Maps Nasal Passages for Smarter Surgery
This preclinical study evaluates a deep learning model for segmenting nasal cavity structures from CT scans. The AFS-DSN architecture achiev…
A new computer program helps doctors see inside the nose more clearly before surgery.
Secondary Analysis Review Quantifying Fiber Disconnections Predicts Outcomes in Basilar Artery Occlusion
New Scan Predicts Stroke Recovery Better Than Standard Tests
This secondary analysis review evaluates disconnected fiber volume versus conventional metrics in 201 patients with acute basilar artery occ…
A new imaging technique measures broken brain connections to predict stroke outcomes more accurately than traditional methods.
Multi-phase DCE-MRI delta-radiomics predicts Ki-67 changes in 148 breast cancer patients after neoadjuvant therapy.
MRI features may help predict Ki-67 changes in breast cancer after treatment
This retrospective cohort study evaluated 148 breast cancer patients who underwent surgical resection after 6–8 cycles of neoadjuvant therap…
A new MRI analysis predicts Ki-67 changes in breast cancer after treatment with 82% accuracy, outperforming simpler models that were only 62…
Multimodal machine learning model differentiation of benign from malignant pulmonary space-occupying lesions in cohort study
Lung Spot Results in Minutes, Not Weeks
This cohort study evaluated 384 patients with pulmonary space-occupying lesions using a multimodal machine learning model integrating CT rad…
A new AI tool can tell if a lung spot is cancer or harmless in minutes, helping patients avoid risky biopsies and long waits for answers.
Meta-analysis of connectome-based fMRI models shows high diagnostic accuracy in obsessive-compulsive disorder.
Brain Scan Pattern Can Spot OCD with High Accuracy
This meta-analysis evaluated connectome-based diagnostic models derived from resting-state fMRI in 563 individuals with obsessive-compulsive…
A new brain scan pattern can spot obsessive-compulsive disorder with high accuracy, offering a clear test for millions who currently struggl…
Cross-site reproducibility study of brain multifrequency MRE in healthy volunteers
New Brain Scan Technique Works Just as Well Across Different Hospitals
This is a prospective cross-site reproducibility study of brain multifrequency magnetic resonance elastography (MRE) in 16 healthy adults. I…
A new brain scan method delivers consistent results across different hospital machines, offering reliable tracking for future monitoring of …