AIMC Topic: Technetium Tc 99m Medronate

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Radiomics based on multiple machine learning methods for diagnosing early bone metastases not visible on CT images.

Skeletal radiology
OBJECTIVES: This study utilizes [Tc]-methylene diphosphate (MDP) single photon emission computed tomography (SPECT) images as a reference standard to evaluate whether the integration of radiomics features from computed tomography (CT) and machine lea...

Deep learning enhanced ultra-fast SPECT/CT bone scan in patients with suspected malignancy: quantitative assessment and clinical performance.

Physics in medicine and biology
. To evaluate the clinical performance of deep learning-enhanced ultrafast single photon emission computed tomography/computed tomography (SPECT/CT) bone scans in patients with suspected malignancy.. In this prospective study, 102 patients with poten...

Detecting lumbar lesions in Tc-MDP SPECT by deep learning: Comparison with physicians.

Medical physics
PURPOSE: Tc-MDP single-photon emission computed tomography (SPECT) is an established tool for diagnosing lumbar stress, a common cause of low back pain (LBP) in pediatric patients. However, detection of small stress lesions is complicated by the low...

Study of the Usefulness of Bone Scan Index Calculated From 99m-Technetium- Hydroxymethylene Diphosphonate (Tc-HMDP) Bone Scintigraphy for Bone Metastases from Prostate Cancer Using Deep Learning Algorithms.

Current medical imaging
BACKGROUND: BSI calculated from bone scintigraphy using technetium-methylene diphosphonate (Tc-MDP) is used as a quantitative indicator of metastatic bone involvement in bone metastasis diagnosis, therapeutic effect assessment, and prognosis predicti...