Mach7 adds mammography support to DocPanel partnership

AuntMinnie.com staff writers

Aug 9, 2022

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Mach7 Technologies has inked a deal to provide its eUnity enterprise diagnostic image viewing software to the DocPanel radiology marketplace for use in cloud-based mammography reading services.

DocPanel previously employed Mach7's eUnity enterprise diagnostic image viewing software as a viewing platform for CT, MR, ultrasound, x-ray, and dual-energy x-ray absorptiometry (DEXA) exams. The new partnership provides for the use of eUnity for mammography and digital breast tomosynthesis interpretation, obviating the need for third-party mammography-specific workstation software, Mach7 said.

In addition, DocPanel and Mach7 said they are in "advanced discussions" over also potentially implementing Mach7's vendor-neutral archive (VNA).

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.

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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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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.

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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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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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Screening mammograms and AI score changes are depicted over time in two individuals with screen-detected cancer. Full-field digital mammograms show craniocaudal (top) and mediolateral (bottom) views of the left and right breast. The description below each mammogram indicates whether AI scores from three AI-based computer-aided detection systems (AI-1, AI-2, and AI-3) were above or below the 90th percentile. (A) Mammograms from three screening time points (in 2009, 2011, and 2014) in an individual who was diagnosed in February 2014 (at age 73 years) with a left-sided 25-mm grade 2 invasive breast carcinoma, no special type (arrow). Mammographic breast density was classified as BI-RADS B on all three mammograms. (B) Mammograms from four screening time points (in 2009, 2011, 2013, and 2015) in an individual who was diagnosed in October 2015 (at age 65 years) with a left-sided 45-mm grade 2 lobular carcinoma (arrow). Mammographic breast density was classified as BI-RADS C on all four mammograms. Screen-detected cancers were defined as those diagnosed within 90 days for individuals who were recalled at screening (*).

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