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Predicting Clinically Significant Prostate Cancer: Can a Prostate MRI Point-Based Model Have an Impact?

Diagnostic Imaging

A point-based model that incorporates prostate MRI findings offered a sensitivity rate of 89.5 percent for detecting clinically significant prostate cancer and could prevent over 20 percent of biopsies, according to new research.

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Clinical value of some knee and hip MRIs questioned

AuntMinnie

While MRI-detected biomarkers may serve a beneficial role for people with hip and knee pain, the modality's clinical utility may be limited in patients over the age of 45 in patients with advanced osteoarthritis, according to an article published in the American Journal of Roentgenology ( AJR ). Erin Alaia, MD.

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AI model comparable to radiologists for finding prostate cancer on MRI

AuntMinnie

A deep-learning model performs comparably to an abdominal radiologist when it comes to finding clinically significant prostate cancer on MRI, researchers have reported. This progress promises to improve patient outcomes through earlier and more accurate diagnosis of [clinically significant prostate cancer]." External 0.86

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Prostate MRI: A Vital Tool for Men’s Health

The Radiology Clinic

Understanding Prostate MRI Prostate MRI (Magnetic Resonance Imaging) is an advanced imaging technique used to visualize the prostate gland in high detail. Why Prostate MRI Matters Prostate cancer is the second most common cancer among men worldwide ! as MRI uses strong magnetic fields. as MRI uses strong magnetic fields.

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PET/MRI superior to PET/CT in cancer patients

AuntMinnie

FDG-PET/MRI is comparable or superior in diagnostic performance to FDG-PET/CT across a range of cancers and endpoints, according to a review of head-to-head studies published July 17 in the American Journal of Roentgenology. PET/MRI showed a staging accuracy in breast cancer of 98% versus 74.5% versus 69.2%. versus 69.2%. versus 66.2%

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Can Multimodal AI Enhance Prediction of Axillary Lymph Node Metastasis Beyond MRI or Ultrasound-Based Models?

Diagnostic Imaging

External validation testing revealed a deep learning combination of breast MRI, ultrasound and clinical factors had a 10 percent higher AUC for predicting axillary lymph node metastasis than sole use of MRI- or ultrasound-based deep learning models in patients with breast cancer.

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Multicenter Study Shows 26 Percent of Multiple Sclerosis Relapses Not Associated with New Lesions on MRI

Diagnostic Imaging

Acute clinical events with stable MRI (ACES) in patients with multiple sclerosis (MS) are reportedly associated with significantly higher rates of confirmed disability accrual, relapse-associated worsening, and transition to secondary progressive MS.

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