Ikonopedia hosts web version of breast cancer risk tool

AuntMinnie.com staff writers

May 23, 2016

Breast imaging software developer Ikonopedia has signed an agreement to host a web-based version of the Tyrer-Cuzick breast cancer risk assessment tool.

Available for free, the tool informs women about their lifetime risk of developing breast cancer and helps them make decisions about genetic testing and breast cancer screening options.

The Tyrer-Cuzick model incorporates family history, endogenous hormonal factors, benign disease, and risk factors such as age and body mass index as well as genetic factors (including BRCA) into a single statistical model that estimates the likelihood of a woman developing breast cancer within 10 years of her current age and over the course of her lifetime.

The Tyrer-Cuzick tool has been integrated into Ikonopedia's PC-based report generation software tools since 2014 and automatically populates reports for high-risk patients.

NME breast lesions have high malignancy rate on MRI-guided biopsy

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(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

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RadSite publishes clinical coverage guideline for breast CBCT imaging

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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

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NME breast lesions have high malignancy rate on MRI-guided biopsy

By Amerigo Allegretto

Biopsies from women with a known ipsilateral malignancy have a higher frequency of breast cancer.

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DBT-based foundational model classifies breast density

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

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(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

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

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CEM finds breast cancer at baseline, incidence screening

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

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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

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

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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.

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Mammogram Calendar 400

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

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

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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).

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Deephealth White On Purple

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Breast Update 2 T76 Vuzvgq

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