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Applying principles of personality theory to one’s development as a radiologist, this author discusses trust in what is bring taught, autonomy and interactions with peers.

Catch up on the most-well viewed radiology content in April 2024.

Catch up on the top radiology content of the past week.

Reportedly the smallest and thinnest implantable spinal cord stimulator (SCS) device, the Inceptiv closed-loop SCS modality allows access to 1.5T and 3T full-body MRI without power restrictions.

Catch up on the top AI-related news and research in radiology over the past month.

An emerging deep learning radiomics model, based on B-mode ultrasound and color Doppler flow imaging, demonstrated a 91 percent AUC for predicting lymphovascular invasion in a multicenter study of women with invasive breast cancer.

Combining a support crossing catheter with intravascular ultrasound imaging, the Provisio SLT IVUS System offers simultaneous real-time visualization and measurement of vessel lumen.

One of the recommendations from the European Society of Breast Imaging (EUSOBI) is annual breast MRI exams starting at 25 years of age for women deemed to be at high risk for breast cancer.

In a recent interview, Kenneth J. Pienta, M.D., discussed the impact of piflufolastat F18, current directions in research with other PSMA-targeted radiotracers and future possibilities for the role of PSMA PET in the imaging paradigm for prostate cancer.

The artificial intelligence (AI)-powered applications reportedly allow clinicians to diagnose pulmonary edema and measure left ventricle ejection fraction within seconds.

Review the case and test your knowledge to make the correct diagnosis.

In addition to advanced imaging quality and dose efficiency, the Philips Zenition 30 mobile C-arm device emphasizes personalized user profiles and automated customization to help reduce procedure time.

In a study of women with oligometastatic breast cancer, the use of 18F-FDG PET/CT detected additional metastases in one-third of cases that were not evident on conventional CT.

With dramatic changes less likely with respect to reimbursement and one’s career in radiology, have we downsized our expectations to be more accepting of a floor of stability and slow progress?

Catch up on the top radiology content of the past week.

Examining current trends in brain cancer diagnostics, these authors discuss diagnostic imaging advances, pathways with adaptive radiotherapy and the ongoing quest to provide optimal precision with dosimetry.

One of the features on the new Voluson Signature 20 and 18 ultrasound devices reportedly uses automated AI tools to facilitate a 40 percent reduction in the time it takes to perform second trimester exams.

While noting inconsistencies with the diagnostic yield of cardiac MRI in patients who survived sudden cardiac arrest, researchers cited unique advantages in characterizing ischemic cardiomyopathy (ICM) and facilitating alternate diagnoses.

The combination of the optical imaging agent Lumisight and the fluorescence imaging device Lumicell Direct Visualization System, collectively known as LumiSystem, reportedly offers 84 percent accuracy with real-time detection of residual breast cancer after lumpectomy procedures.

A recent meta-analysis found that multiparametric MRI and PET/CT had comparable detection rates for diagnosing prostate cancer recurrence.

The use of continuous ofatumumab in patients within three years of a relapsing multiple sclerosis diagnosis led to substantial reductions in associated lesions on brain MRI scans, according to research recently presented at the American Academy of Neurology (AAN) conference.

A new study shows that GPT-4 may offer comparable error detection rates to those of attendings and radiology residents in reviewing radiology reports, but researchers noted key caveats as well.

A positron emission tomography (PET) agent that targets LAT1 and LAT2 membrane transport proteins, TLX101-CDx or 18F-floretyrosine could be utilized to help characterize progressive or recurrent glioma.

Artificial intelligence (AI) assessment of mammography images may significantly enhance the prediction of invasive breast cancer and ductal carcinoma in situ (DCIS) in women with breast cancer, according to new research presented at the Society for Breast Imaging (SBI) conference.

For the prediction of axillary lymph node metastasis in patients with breast cancer, an MRI-based, 4D convolutional neural network model demonstrated an AUC of 87 percent and sensitivity of 89 percent, according to new research.

While no job is perfect, there is the time-honored wisdom about picking your battles and the realization that some positions are stuck in a status-quo quagmire.

Catch up on the top radiology content of the past week.

Discussing findings from a new study presented at the Society for Breast Imaging (SBI) conference, Shahrzad Tavana, M.D., detailed the significant impact of training sessions for MRI technologists in improving breast positioning, optimal field of view and accuracy of sequence submissions to PACS for breast MRI exams.