AI: Page 15

Podcast: Moving from a role in academic medicine to leading a company

Katherine High, MD, joins Saurabh (Harry) Jha, MD, and Mitchell Schnall, MD, for this episode of the "Keeping Up With the Radiologists" podcast series.

July 26, 2024

How imaging AI developers can avoid pitfalls when testing algorithms

By Amerigo Allegretto

AI developers can recognize and avoid pitfalls when creating models and tools for interpretative imaging performance.

July 25, 2024

CT images from a 24-year-old woman with history of ventriculopleural shunt placement who presented with chest pain show two small linear hyperattenuating structures (A, arrows), with larger hyperattenuating structure oriented parallel and very close to the rib. The AI algorithm interpreted the finding as a rib fracture. (B) An additional axial image from same exam indicates that the finding relates to the patient’s ventriculopleural shunt (arrow), passing alongside the rib. The radiologist made a correct interpretation upon assessment of the entire exam. Image courtesy of the ARRS.

GPT-4 can assist in management of glioblastoma patients

Research suggests GPT-4 could streamline longitudinal assessment process by providing a comprehensive overview of prior imaging.

July 23, 2024

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Mammo AI falls short to ultrasound in screening dense breasts

By Amerigo Allegretto

Mammography plus ultrasound yields better results than AI-enhanced mammography alone when it comes to screening of women with dense breasts.

July 23, 2024

Imaging in a 56-year-old woman with heterogeneously dense breasts (BIRADS C). (A) Left craniocaudal (left) and mediolateral oblique (right) digital mammograms show no abnormality. (B) Left craniocaudal (LCC, top) and left mediolateral oblique (LMLO, bottom) mammograms with retrospectively applied AI (Lunit Insight MMG, version 1.1.7.1; Lunit) show the lesion was given abnormality scores of 97% and 71%, respectively. The color bar indicates pixel-level abnormality scores corresponding to heatmap contour lines. Breast ultrasound performed the same day was considered negative (not shown). (C) Left craniocaudal (left) and mediolateral oblique (right) digital mammograms acquired nine months later show an irregular mass (arrows) in the left breast, which correlates with the heatmap areas scored as 97% and 71% by AI in the earlier screening mammogram (B). The radiopaque round marker denotes the site of the palpable abnormality indicated by the patient. (D) Transverse ultrasound imaging shows an irregular mass (arrow) in the left breast. The patient was treated with breast-conserving surgery, and the mass was proven to be invasive lobular carcinoma. Image courtesy of the RSNA.

GPT-4V generates mixed results in online image quiz

A recent study shows the GPT-4 Vision multimodal AI model erred when answering medical quiz questions based on clinical images and a text summary.

July 23, 2024

SCCT: AI identifies at-risk cardiac patients from CT images

By Amerigo Allegretto

AI helps identify patients who may benefit from preventive cardiology services via CT images.

July 20, 2024

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Breast Cancer Canada launches research funding fellowship

By AuntMinnie.com staff writers

Breast Cancer Canada is launching a 1-million-Canadian-dollar ($730,695 U.S.) fellowship to expand breast cancer research funding.

July 15, 2024

Money Hundred Bills

AI in radiology: The kids are alright

By Amerigo Allegretto

Young people are optimistic about the use of AI in medicine, including in radiology.

July 15, 2024

Experts outline how best to deploy AI in radiology

By AuntMinnie.com staff writers

The RSNA and the MICCAI Society have published a special report on how best to deploy AI tools into clinical radiology practice.

July 11, 2024

AI improves evaluations of knee osteoarthritis on x-rays

A commercially available AI algorithm improved the performance of junior radiologists when grading knee osteoarthritis on x-rays.

July 9, 2024

An example of the study platform as seen by a reader receiving assistance from the AI tool. On the left is the overlay generated by the AI tool. On the right is the grading panel. Note that the grading fields are prefilled with the outputs of the AI tool. In this study, the left knee was to be graded. When the right was to be graded, the grading panel was on the left. The size of some user interface elements, primarily text and buttons, have been enhanced to improve legibility. JSN = joint space narrowing, KL = Kellgren-Lawrence, OST = osteophytes, PA = posteroanterior, SCL = subchondral sclerosis. Image and caption courtesy of Radiology.

AI increases breast MRI's cancer detection 4-fold

By Amerigo Allegretto

An AI approach for supplemental breast MRI is about four times more efficient at detecting breast cancers than traditional methods.

July 9, 2024

(A) Case A was a 13-mm large BI-RADS 4 finding on MRI that corresponded to a 13-mm large invasive cancer as diagnosed in the surgical specimen. (B) Case B was a 9-mm large BI-RADS 4 finding on MRI that corresponded to an 8-mm invasive cancer and 14-mm ductal cancer in situ. (C) Case C was three suspicious lesions within a total area of 60 mm, BI-RADS 5 finding on MRI, that corresponded to a 50-mm multifocal invasive lobular cancer. (D) Case D was two suspicious lesions, the largest 13 mm, BI-RADS 3 on MRI, which corresponded to a 10-mm invasive lobular cancer with 85-mm extent including ductal cancer in situ. Images courtesy of Nature Medicine. Licensed under CC BY 4.0.

Radiology departments can adopt responsible frameworks to deploy AI

By Amerigo Allegretto

Adopting a responsible framework could help overcome challenges in applying AI to medical imaging.

July 8, 2024

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