The World's no. 1 Radiology journal focusing on technological advances : Investigative Radiology

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This issue of the journal, as always, has many outstanding articles, representing cutting edge research and technology in diagnostic imaging. Critical new developments and findings in our field are presented, including that in CT, MR, MR elastography (in pulmonary fibrosis), MR imaging of potassium and sodium, and deep learning in MR. Two ground-breaking articles demonstrate the utility of photon-counting detector CT for liver lesion detection (with radiation dose reduction) and for accuracy of nodule volume and airway wall thickness measurement (using low radiation dose). 7 T MRI is featured for sodium and potassium imaging, demonstrating the ability to detect concentration changes in muscle with exercise. The value of deep learning is validated in two different MR studies, one for triaging and computer diagnosis of breast cancer (reducing workload and workup of benign lesions without missing cancer) and a second for automatic bone marrow segmentation and ADC measurements (overcoming inter-rater variability and non-representative measurements in patients with plasma cell infiltration). A final critical study examines the topic of non-reproducibility of radiomics features with different MR sequences or MR scanners and identifiers a subset of features robust to variations in MR acquisition, allowing the building of reproducible models for evaluation of monoclonal plasma cell disorders in multicenter applications.

Current Issue Highlights

In Vivo Repeatability and Multiscanner Reproducibility of MRI Radiomics Features in Patients With Monoclonal Plasma Cell Disorders: A Prospective Bi-institutional Study

Wennmann, Markus; Bauer, Fabian; Klein, André; More

Investigative Radiology. 58(4):253-264, April 2023.

Deep Learning for Automatic Bone Marrow Apparent Diffusion Coefficient Measurements From Whole-Body Magnetic Resonance Imaging in Patients With Multiple Myeloma: A Retrospective Multicenter Study

Wennmann, Markus; Neher, Peter; Stanczyk, Nikolas; More

Investigative Radiology. 58(4):273-282, April 2023.

Validation of Combined Deep Learning Triaging and Computer-Aided Diagnosis in 2901 Breast MRI Examinations From the Second Screening Round of the Dense Tissue and Early Breast Neoplasm Screening Trial

Verburg, Erik; van Gils, Carla H.; van der Velden, Bas H.M.; More

Investigative Radiology. 58(4):293-298, April 2023.