Ductal Carcinoma In Situ: Non-Mass Enhancement on MRI 10 Years Before Mammographic Microcalcifications

In developed countries, the lifetime risk of developing breast cancer among women is 11%. Therefore, screening asymptomatic women for breast cancer is widely accepted as preventive health care. Mammography is the primary imaging modality for the detection of breast abnormalities. Digital breast imaging detects 90% of symptomatic or asymptomatic cancers. The sensitivity, specificity, and negative predictive values of this modality are each about 90%. As a standard of care, the Breast Imaging Reporting and Data System (BI-RADS) is used to quantify increasing degrees of positive predictive values in mammography. This can help clinicians identify abnormalities that may need additional imaging studies or biopsies. To reduce false-negative breast cancer screening results, efforts have focused on increasing the sensitivity of mammography or supplementing it with ultrasound or MRI. Advanced practitioners are strategically positioned to detect incongruities between imaging techniques and physical assessments. With increased knowledge, advanced practitioners are better prepared for shared decision-making discussions regarding follow-up imaging procedures. The case report in this article describes a 10-year discordance of imaging that proved to be high-grade ductal carcinoma in situ (DCIS) and offers a hypothesis of the physiology to explain this discordance. A better understanding of breast imaging will enable the advanced practitioner to recommend the most appropriate follow-up study for patients.

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Publication Details

Journal
Journal of the Advanced Practitioner in Oncology
Published
2025-05-15
DOI
https://doi.org/10.6004/jadpro.2025.16.3.3
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Ductal Carcinoma In Situ: Non-Mass Enhancement on MRI 10 Years Before Mammographic Microcalcifications

Andria P Caton, Nancy W. Stead
Journal of the Advanced Practitioner in Oncology
Radiomics and Machine Learning in Medical Imaging
article

Ductal Carcinoma In Situ: Non-Mass Enhancement on MRI 10 Years Before Mammographic Microcalcifications

Andria P Caton, Nancy W. Stead
article en

Abstract

In developed countries, the lifetime risk of developing breast cancer among women is 11%. Therefore, screening asymptomatic women for breast cancer is widely accepted as preventive health care. Mammography is the primary imaging modality for the detection of breast abnormalities. Digital breast imaging detects 90% of symptomatic or asymptomatic cancers. The sensitivity, specificity, and negative predictive values of this modality are each about 90%. As a standard of care, the Breast Imaging Reporting and Data System (BI-RADS) is used to quantify increasing degrees of positive predictive values in mammography. This can help clinicians identify abnormalities that may need additional imaging studies or biopsies. To reduce false-negative breast cancer screening results, efforts have focused on increasing the sensitivity of mammography or supplementing it with ultrasound or MRI. Advanced practitioners are strategically positioned to detect incongruities between imaging techniques and physical assessments. With increased knowledge, advanced practitioners are better prepared for shared decision-making discussions regarding follow-up imaging procedures. The case report in this article describes a 10-year discordance of imaging that proved to be high-grade ductal carcinoma in situ (DCIS) and offers a hypothesis of the physiology to explain this discordance. A better understanding of breast imaging will enable the advanced practitioner to recommend the most appropriate follow-up study for patients.

Journal of the Advanced Practitioner in OncologyVol. 16(3)
Northeast Georgia Medical Center (US)
Partnerships for the goals
Openalex Percentile: Top 84%
Radiomics and Machine Learning in Medical Imaging
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