News | Breast Biopsy Systems | May 08, 2018

New Analytics Approach Offers Potential of Reducing Unnecessary Breast Biopsies

Study defines advanced statistical methods that can be used with diagnostic imaging output to downgrade breast mass risk classification

New Analytics Approach Offers Potential of Reducing Unnecessary Breast Biopsies

May 8, 2018 — The American Journal of Roentgenology recently published findings on statistical methods for downgrading the risk classification of breast masses to reduce the need for unnecessary breast biopsies. Clinicians from Seno Medical and medical center collaborators from The University of Texas co-authored the report.1  

"The perceived risk of missing a breast cancer diagnosis with breast imaging studies is much higher than the risk of a false-positive diagnosis, leading to breast imagers recommending a breast biopsy whenever the risk of cancer is greater than 2 percent. Sometimes ancillary diagnostic breast imaging studies are performed to reduce risk to less than 2 percent, but it is difficult to know exactly how much risks are reduced even after a negative ancillary diagnostic imaging examination," said Thomas Stavros, M.D., chief medical officer of Seno Medical and a co-author of the report. "However, the use of the Negative Likelihood Ratio (NLR) along with BI-RADS [Breast Imaging-Reporting and Data System] 4 subcategories can help to reduce the number of false-positives without experiencing excessive negative results that would lead to cancer going undiagnosed."

The report explores the use of a statistical calculation known as the Negative Likelihood Ratio (NLR). It shows how NLR can be calculated from a diagnostic test's sensitivity and specificity and also show the NLRs of some currently available diagnostic imaging modalities. It outlines how the BI-RADS 4A sub-category has low enough and narrow enough range of pre-test probabilities (see Table 1) to allow downgrading to a post-test probability of 2 percent or less after a negative diagnostic imaging test with an adequately low NLR.

 

FINAL ASSESSMENT CATEGORIES

Category

Management

Likelihood of cancer

0

Need Additional Imaging or Prior Examinations

Recall for Additional Imaging and/or Await Prior Examinations

n/a

1

Negative

Routine Screening

Essentially 0%

2

Benign

Routing Screening

Essentially 0%

3

Probably Benign

Short Interval Follow-up (6 month) or Continued

>0% but < 2%

4

Suspicious

Tissue Diagnosis

  • 4a. low suspicion for malignancy (>2% to < 10%)
  • 4b. moderate suspicion for malignancy (>10% to < 50%)
  • 4c. high suspicion for malignancy (>50% to <95%)

5

Highly Suggestive of Malignancy

Tissue Diagnosis

>95%

6

Known Biopsy-Proven

Surgical Excision when Clinically Appropriate

n/a

Table 1. BI-RADS Categories

Source: http://www.radiologyassistant.nl/data/bin/a53b4293920e94_TAB-Birads

"Reducing the number of unnecessary breast biopsies is an essential advancement toward improving women's healthcare and protecting breast health," said Pam Otto, M.D., Department of Radiology, The University of Texas Health Science Center at San Antonio and co-author. "I would encourage breast imagers to consider using BI-RADS 4 subcategories and NLR as important tools for helping them minimize false positive studies with minimum adverse effect on sensitivity, optimizing their patients' breast health. The availability of web-based programs for automating the NLR calculations should help to facilitate routine use of this important statistical tool."

For more information: www.ajronline.org

References

1. Yang WT, Parikh JR, Stavros AT, Otto P and Maislin G. Exploring the Negative Likelihood Ratio and How It Can Be Used to Minimize False-Positives in Breast Imaging. AJR 2018;210:301-306.

 

 

Related Content

Developed by medical AI company Lunit, Software detects breast cancer with 97% accuracy; Study in Lancet Digital Health shows that Lunit INSIGHT MMG-aided radiologists showed an increase in sensitivity

Lunit INSIGHT MMG

News | Artificial Intelligence | June 02, 2020
June 2, 2020 — Lunit announced that its artificia...
AI has the potential to help radiologists improve the efficiency and effectiveness of breast cancer imaging

Getty Images

Feature | Breast Imaging | May 28, 2020 | By January Lopez, M.D.
Headlines around the world the past several months declared that...
a Schematic of the system. The entire solid tumour is illuminated from four sides by a four-arm fibre bundle. A cylindrically focused linear array is designed to detect optoacoustic signals from the tumour. In vivo imaging is performed in conical scanning geometry by controlling the rotation and translation stages. The sensing part of the transducer array and the tumour are submerged in water to provide acoustic coupling. b Maximum intensity projections of the optoacoustic reconstruction of a phantom of pol

a Schematic of the system. The entire solid tumour is illuminated from four sides by a four-arm fibre bundle. A cylindrically focused linear array is designed to detect optoacoustic signals from the tumour. In vivo imaging is performed in conical scanning geometry by controlling the rotation and translation stages. The sensing part of the transducer array and the tumour are submerged in water to provide acoustic coupling. b Maximum intensity projections of the optoacoustic reconstruction of a phantom of polyethylene microspheres (diameter, 20 μm) dispersed in agar. The inset shows a zoomed-in view of the region boxed with a yellow dashed line. In addition, the yellow boxes are signal profiles along the xy and z axes across the microsphere centre, as well as the corresponding full width at half-maximum values. c Normalized absorption spectra of Hb, HbO2 and gold nanoparticles (AuNPs). The spectrum for the AuNPs was obtained using a USB4000 spectrometer (Ocean Optics, Dunedin, FL, USA), while the spectra for Hb and HbO2 were taken from http://omlc.org/spectra/haemoglobin/index.html. The vertical dashed lines indicate the five wavelengths used to stimulate the three absorbers: 710, 750, 780, 810 and 850 nm. Optoacoustic signals were filtered into a low-frequency band (red) and high-frequency band (green), which were used to reconstruct separate images.

News | Breast Imaging | May 26, 2020
May 26, 2020 — Breast cancer is the most common cancer in women.
Phone call and linkage-to-care-based intervention increases mammography uptake among primary care patients at an urban safety-net hospital

Getty Images

News | Mammography | May 22, 2020
May 22, 2020 — Telephone outreach coupled with scheduling assistance significantly increased...
The Breast Imaging and Reporting System (BI-RADS) was established by the American College of Radiology to help classify findings on mammography. Findings are classified based on the risk of breast cancer, with a BI-RADS 2 lesion being benign, or not cancerous, and BI-RADS 6 representing a lesion that is biopsy-proven to be malignant.

Getty Images

News | Breast Imaging | May 19, 2020
May 19, 2020 — Women with mammographically detected breast lesions that are probably benign should have follow-up sur
Podcast: Impact of COVID-19 on Breast Cancer Treatment with Dr. Andrea Madrigrano

Kubtec hosts a Podcast: Impact of COVID-19 on Breast Cancer Treatment with Andrea Madrigrano, M.D., as part of its public service campaign.

News | Coronavirus (COVID-19) | May 06, 2020
May 6, 2020 — The COVID-19 pandemic is an unprec
The American Society of Breast Surgeons (ASBrS), the National Accreditation Program for Breast Centers (NAPBC), the National Comprehensive Cancer Network (NCCN), the Commission on Cancer (CoC) of the American College of Surgeons, and the American College of Radiology (ACR) have released new joint recommendations for prioritization, treatment and triage of breast cancer patients during the coronavirus (COVID-19) pandemic

Getty Images

News | Breast Imaging | April 13, 2020
April 13, 2020 — The American Society of Breast Surgeons (...
Table 1. Compared to 2-D mammography, which yields four images per patient, digital breast tomosynthesis (DBT), or 3-D mammography, produces hundreds of images per patient. While this provides more information for clinicians, the exponential increase in data can result in reader fatigue and burnout, which may ultimately affect patient care.

Table 1. Compared to 2-D mammography, which yields four images per patient, digital breast tomosynthesis (DBT), or 3-D mammography, produces hundreds of images per patient. While this provides more information for clinicians, the exponential increase in data can result in reader fatigue and burnout, which may ultimately affect patient care.

Sponsored Content | Case Study | Artificial Intelligence | April 09, 2020
As the largest independent imaging group in Michigan with 10 locations across the state,...