Sigmascreening touts breast compression study at RSNA 2016

AuntMinnie.com staff writers

Nov 27, 2016

Sigmascreening is touting the results of a study that focused on the impact of pressure in breast compression on screening outcomes at RSNA 2016 in Chicago.

The study, presented by Nico Karssemeijer, PhD, from Nijmegen, the Netherlands, found that breast compression with intermediate target pressure may improve breast cancer detection rates. The researchers wanted to determine breast cancer screening outcomes in relation to the compression pressure applied during mammography. After adjusting for confounders, they found that pressure around 75 mmHg (± 5 mmHg) showed the best breast cancer detection rate and the best positive predictive value when compared with lower and higher compression groups.

Sensitivity decreased with increasing pressure, resulting in a higher interval cancer rate in the group with the highest compression pressure. If too much or too little pressure is applied, this may increase the number of interval cancers and decrease the positive predictive value (PPV), the researchers concluded. The data support the introduction and use of pressure-guided compression, according to the vendor.

(A) Free-response receiver operating characteristic (FROC) curve for DBT-DINO and DINOv2 (Meta AI) on the detection task. DINOv2 achieved higher sensitivity than DBT-DINO across most false-positive thresholds. (B) Detection rates of DBT-DINO and DINOv2 for lesions that were ultimately found to be benign (n = 70) and lesions that were found to be cancerous (n = 66). Error bars represent 95% CIs estimated via patient-level bootstrapping with 1000 repetitions. Both models showed similar detection rates for cancerous lesions, whereas DINOv2 detected more benign lesions than DBT-DINO. (C) Example bounding box predictions for DBT-DINO and DINOv2 on the detection test set. Each image is a single two-dimensional section from a three-dimensional digital breast tomosynthesis volume; the first column shows a mediolateral oblique view, and the second and third columns show craniocaudal views. Both models struggled to detect very small lesions, such as the 3-mm-diameter lesion shown in the first column. FP = false positive.

DBT-based foundational model classifies breast density

August 4, 2026

RadSite publishes clinical coverage guideline for breast CBCT imaging

July 30, 2026

Images in a 70-year-old asymptomatic woman with a prior excisional biopsy in the left breast yielding lobular carcinoma in situ 3 years earlier. Screening contrast-enhanced mammography (CEM) was performed, which was considered a prevalence screen as the woman had no prior breast MRI in the past 3 years and no prior CEM. (A) Low-energy (26–30 kVp) mediolateral oblique (MLO) and (B) craniocaudal (CC) views show surgical clips but no abnormality. (C) Recombined MLO and (D) CC images show an enhancing mass in the medial left breast (arrows). Biopsy revealed invasive lobular carcinoma. Size was 0.2 cm; tumor grade II/III; negative lymph nodes; and estrogen receptor–positive, progesterone receptor–positive, and human epidermal growth factor receptor 2–negative.

CEM finds breast cancer at baseline, incidence screening

July 28, 2026

Minnie Cast Thumbnail (15)

Women's Imaging MinnieCast, Episode 13: Partial breast irradiation in the spotlight

July 17, 2026

DBT-based foundational model classifies breast density

By Amerigo Allegretto

DBT-DINO showed strong performance in classifying breast density from DBT images.

August 4, 2026

(A) Free-response receiver operating characteristic (FROC) curve for DBT-DINO and DINOv2 (Meta AI) on the detection task. DINOv2 achieved higher sensitivity than DBT-DINO across most false-positive thresholds. (B) Detection rates of DBT-DINO and DINOv2 for lesions that were ultimately found to be benign (n = 70) and lesions that were found to be cancerous (n = 66). Error bars represent 95% CIs estimated via patient-level bootstrapping with 1000 repetitions. Both models showed similar detection rates for cancerous lesions, whereas DINOv2 detected more benign lesions than DBT-DINO. (C) Example bounding box predictions for DBT-DINO and DINOv2 on the detection test set. Each image is a single two-dimensional section from a three-dimensional digital breast tomosynthesis volume; the first column shows a mediolateral oblique view, and the second and third columns show craniocaudal views. Both models struggled to detect very small lesions, such as the 3-mm-diameter lesion shown in the first column. FP = false positive.

RadSite publishes clinical coverage guideline for breast CBCT imaging

By AuntMinnie.com staff writers

The guide outlines how breast CBCT should be used when conventional imaging approaches are inconclusive or inaccessible.

July 30, 2026

CEM finds breast cancer at baseline, incidence screening

By Amerigo Allegretto

Incidence screening with CEM maintains high performance and may offer more benefits over baseline CEM screening.

July 28, 2026

Images in a 70-year-old asymptomatic woman with a prior excisional biopsy in the left breast yielding lobular carcinoma in situ 3 years earlier. Screening contrast-enhanced mammography (CEM) was performed, which was considered a prevalence screen as the woman had no prior breast MRI in the past 3 years and no prior CEM. (A) Low-energy (26–30 kVp) mediolateral oblique (MLO) and (B) craniocaudal (CC) views show surgical clips but no abnormality. (C) Recombined MLO and (D) CC images show an enhancing mass in the medial left breast (arrows). Biopsy revealed invasive lobular carcinoma. Size was 0.2 cm; tumor grade II/III; negative lymph nodes; and estrogen receptor–positive, progesterone receptor–positive, and human epidermal growth factor receptor 2–negative.

Women's Imaging MinnieCast, Episode 13: Partial breast irradiation in the spotlight

By Amerigo Allegretto

Two committee members for ASTRO's PBI guidelines share insights about this breast cancer treatment option.

July 17, 2026

Minnie Cast Thumbnail (15)

Incorrect AI suggestions influence reader performance on mammography

By Amerigo Allegretto

The biggest impact on reader performance stemmed from false-negative AI suggestions.

July 14, 2026

A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.

Breast cancer screening higher among civically engaged women

By Amerigo Allegretto

Women who voted, attended a public meeting, or volunteered are more likely to get their breast cancer screening.

July 14, 2026

Mammogram Calendar 400

CEM on par with MRI for breast cancer diagnosis, local staging

By Amerigo Allegretto

CEM alone in a prospective study achieved perfect sensitivity and negative predictive value in diagnosing breast cancer.

July 10, 2026

MRI false positive for additional disease, (top to bottom): A. Index lesion—grade 2 invasive ductal carcinoma; B. MRI lesion two, upper inner quadrant: Stromal sclerosis and columnar cell change; C. MRI lesion three, upper outer quadrant: No ultrasound correlate, no malignancy on follow-up; D. CEM marked background parenchymal enhancement with a unifocal retroareolar lesion demonstrating wash-out on delayed MLO. Images are republished under a Creative Commons license (CC BY 4.0).

Siemens Healthineers gets FDA nod for CEM on Mammomat B.brilliant

By AuntMinnie.com staff writers

Siemens Healthineers has received FDA clearance for CEM and CEM biopsy capabilities for its Mammomat B.brilliant system.

June 30, 2026

Mammomat B.brilliant breast imaging system

Fujifilm, IAEA sign agreement to expand cancer imaging

By AuntMinnie.com staff writers

The two organizations will collaborate on awareness campaigns, education and training programs for healthcare professionals, and the provision of Fujifilm medical equipment.

June 29, 2026

DeepHealth gets FDA nod for two mammography AI tools

By AuntMinnie.com staff writers

DeepHealth has received FDA clearance for two parts of the company's Breast Suite AI platform: BAC Assessment and Mammo Dx.

June 25, 2026

Deephealth White On Purple

QT Imaging reports low variability for breast scanner biomarkers

By AuntMinnie.com staff writers

Study analyzes Breast Acoustic CT speed-of-sound (SoS) measurements.

June 24, 2026

Breast Update 2 T76 Vuzvgq

Komen awards $15.4 million in breast cancer research grants

By AuntMinnie.com staff writers

Susan G. Komen has awarded over $15 million in grant funding toward breast cancer research.

June 23, 2026

Research Money 400

Page 1 of 584