Subtle Medical secures CE Mark for SubtleHD

Mar 17, 2025

AI software developer Subtle Medical has secured the CE Mark, which allows it to market its SubtleHD platform in Europe.

SubtleHD offers radiologists, imaging centers, and hospitals a vendor-neutral AI tool that integrates with existing MRI scanners, thus allowing facilities to run faster scans and add additional patients while enhancing diagnostic confidence, according to the firm. It denoises and sharpens images and can be used with all body parts and all contrasts, including 2D and 3D images, Subtle Medical said.

Full-field digital screening mammograms in participants recalled by the consensus discussion after being flagged by artificial intelligence (AI) computer-aided detection (CAD) but not by either of the two radiologists. (A) Mammogram with AI CAD score of 73 for a 55-year-old woman diagnosed with grade 3 in situ cancer and T1 (9-mm) invasive cancer in the left breast and lymph node metastasis. (B) Mammogram with AI CAD score of 54 for a 49-year-old woman diagnosed with grade 2 in situ cancer and T1 (6-mm) invasive cancer in the right breast and without lymph node metastasis. All images and caption courtesy of the RSNA.

Do radiologists trust mammography AI software?

March 18, 2025

MRI scans show two areas of clinically significant prostate cancer in a 65-year-old man with a prostate-specific antigen level of 8.23 ng/mL. Images are (A, E) axial T2-weighted images, (B, F) axial diffusion-weighted images obtained with a b value of 1500 sec/mm2, (C, G) axial apparent diffusion coefficient images, and (D, H) lesion masks generated by the deep learning algorithm (DLA) on T2-weighted images. The DLA detected a lesion in the right posteromedial peripheral zone of the apex (D), which was assigned as Prostate Imaging Reporting and Data System (PI-RADS) 4. A radiologist also detected the lesion and assigned it PI-RADS 4 (arrow in A-C). A lesion in the right anterior transition zone (H) was detected by the DLA, which was assigned PI-RADS 4. The radiologist did not detect the lesion (arrow in E-G). Both lesions were confirmed as prostate cancer with Gleason grade group 2. Caption and image courtesy of RSNA.

DL algorithm targeting prostate cancer demonstrates clinical impact

March 12, 2025

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AI boosts identification of incident vertebral fractures on chest CT

March 11, 2025

(A) SHAP summary plot shows the global contributions of variables to the model predictions. (B-E) Local explanation of the model for a single instance of ovarian endometrioid carcinoma: SHAP waterfall plot (B), ultrasound grayscale image (C), ultrasound color Doppler image (D), and 10×10 histopathological image (E). Images are available for republishing under a Creative Commons license (CC BY-NC-ND 4.0).

Deep-learning radiomics model aids in ovarian cancer diagnosis

March 5, 2025

Do radiologists trust mammography AI software?

By Erik L. Ridley

A large-scale prospective trial exploring the use of mammography AI software in a breast cancer screening program has found that recalls were lower when cases were flagged by AI.

March 18, 2025

Full-field digital screening mammograms in participants recalled by the consensus discussion after being flagged by artificial intelligence (AI) computer-aided detection (CAD) but not by either of the two radiologists. (A) Mammogram with AI CAD score of 73 for a 55-year-old woman diagnosed with grade 3 in situ cancer and T1 (9-mm) invasive cancer in the left breast and lymph node metastasis. (B) Mammogram with AI CAD score of 54 for a 49-year-old woman diagnosed with grade 2 in situ cancer and T1 (6-mm) invasive cancer in the right breast and without lymph node metastasis. All images and caption courtesy of the RSNA.

DL algorithm targeting prostate cancer demonstrates clinical impact

Per participant, a deep-learning (DL) algorithm demonstrated increased specificity of 64.8% compared with radiologists at 21.3%.

March 12, 2025

MRI scans show two areas of clinically significant prostate cancer in a 65-year-old man with a prostate-specific antigen level of 8.23 ng/mL. Images are (A, E) axial T2-weighted images, (B, F) axial diffusion-weighted images obtained with a b value of 1500 sec/mm2, (C, G) axial apparent diffusion coefficient images, and (D, H) lesion masks generated by the deep learning algorithm (DLA) on T2-weighted images. The DLA detected a lesion in the right posteromedial peripheral zone of the apex (D), which was assigned as Prostate Imaging Reporting and Data System (PI-RADS) 4. A radiologist also detected the lesion and assigned it PI-RADS 4 (arrow in A-C). A lesion in the right anterior transition zone (H) was detected by the DLA, which was assigned PI-RADS 4. The radiologist did not detect the lesion (arrow in E-G). Both lesions were confirmed as prostate cancer with Gleason grade group 2. Caption and image courtesy of RSNA.

AI boosts identification of incident vertebral fractures on chest CT

By Kate Madden Yee

An AI algorithm that measures 3D whole thoracic vertebral bone mineral density on conventional chest CT can help predict incident vertebral fractures.

March 11, 2025

Back Spine Skeleton

Deep-learning radiomics model aids in ovarian cancer diagnosis

By Amerigo Allegretto

An ensemble model combining clinical variables, O-RADS, and deep learning radiomics can diagnose ovarian tumors.

March 5, 2025

(A) SHAP summary plot shows the global contributions of variables to the model predictions. (B-E) Local explanation of the model for a single instance of ovarian endometrioid carcinoma: SHAP waterfall plot (B), ultrasound grayscale image (C), ultrasound color Doppler image (D), and 10×10 histopathological image (E). Images are available for republishing under a Creative Commons license (CC BY-NC-ND 4.0).

AI model aimed at adrenal glands, nodules could reduce workload by 10%

A future vision of AI in this context could entail analyzing adrenal nodules across multiple phases, extracting radiomic data, and providing a predictability score, study authors said.

March 4, 2025

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CNN models help determine best treatment for kids with GI obstructions

By Kate Madden Yee

Convolutional neural network (CNN) algorithms show promise for identifying gastrointestinal (GI) obstructions on x-ray in a pediatric population, researchers have reported.

February 28, 2025

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ECR: Integrating AI into radiology workflows benefits the environment

By Kate Madden Yee

Sustainability in radiology is a hot topic at this year's ECR in Vienna, and a February 27 talk focused on "green" radiology using AI technology.

February 28, 2025

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ECR: Repurposed AI boosts breast cancer detection in diverse patient groups

By Amerigo Allegretto

Repurposed AI imaging tools can improve breast malignancy detection across diverse patient groups.

February 27, 2025

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ECR: Generative AI yields potential for assisting radiologists

By Amerigo Allegretto

Generative AI may have novel applications in the clinic, but using the technology comes with its share of challenges and future directions.

February 26, 2025

Marc Kohli, MD, discusses current and potential future uses of generative AI in radiology at ECR 2025 in Vienna, Austria. Behind him is an image created by one such generative AI model, which illustrates humans working alongside AI.

LLM Mistral rivals GPT-4 Turbo for extracting clinical history elements

Mistral outperformed Llama and GPT-4 Turbo in a real-world application that assessed the completeness of clinical histories accompanying radiology imaging orders from the emergency department.

February 25, 2025

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AI helps predict kidney function decline in Lu-177 patients

An open-source AI tool can help predict renal function decline in prostate cancer patients undergoing lutetium-177 (Lu-177) radiopharmaceutical therapy.

February 25, 2025

An axial CT image illustrating segmentation of functioning kidney tissue (blue areas), excluding kidney cysts and renal pelvis, using TotalSegmentator. Image and caption courtesy of RSNA.

What's best practice for using AI for thoracic imaging?

By Kate Madden Yee

The use of AI in thoracic imaging has begun to demonstrate "cumulative evidence of effectiveness," but more testing and research are needed to determine its feasibility for this application.

February 25, 2025

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