Screening in Patients With Dense Breasts : Comparison of Mammography, Artificial Intelligence, and Supplementary Ultrasound
BACKGROUND. Screening mammography has decreased performance in patients with dense breasts. Supplementary screening ultrasound is a recommended option in such patients, although it has yielded mixed results in prior investigations. OBJECTIVE. The purpose of this article is to compare the performance characteristics of screening mammography alone, standalone artificial intelligence (AI), ultrasound alone, and mammography in combination with AI and/or ultrasound in patients with dense breasts. METHODS. This retrospective study included 1325 women (mean age, 53 years) with dense breasts who underwent both screening mammography and supplementary breast ultrasound within a 1-month interval from January 2017 to December 2017; prior mammography and prior ultrasound examinations were available for comparison in 91.2% and 91.8%, respectively. Mammography and ultrasound examinations were interpreted by one of 15 radiologists (five staff; 10 fellows); clinical reports were used for the present analysis. A commercial AI tool was used to retrospectively evaluate mammographic examinations for presence of cancer. Screening performances were compared among mammography, AI, ultrasound, and test combinations, using generalized estimating equations. Benign diagnoses required 24 months or longer of imaging stability. RESULTS. Twelve cancers (six invasive ductal carcinoma; six ductal carcinoma in situ) were diagnosed. Mammography, standalone AI, and ultrasound showed cancer detection rates (per 1000 patients) of 6.0, 6.8, and 6.0 (all p > .05); recall rates of 4.4%, 11.9%, and 9.2% (all p < .05); sensitivity of 66.7%, 75.0%, and 66.7% (all p > .05); specificity of 96.2%, 88.7%, and 91.3% (all p < .05); and accuracy of 95.9%, 88.5%, and 91.1% (all p < .05). Mammography with AI, mammography with ultrasound, and mammography with both ultrasound and AI showed cancer detection rates of 7.5, 9.1, and 9.1 (all p > .05); recall rates of 14.9, 11.7, and 21.4 (all p < .05); sensitivity of 83.3%, 100.0%, and 100.0% (all p > .05); specificity of 85.8%, 89.1%, and 79.4% (all p < .05); and accuracy of 85.7%, 89.2%, and 79.5% (all p < .05). CONCLUSION. Mammography with supplementary ultrasound showed higher accuracy, higher specificity, and lower recall rate in comparison with mammography with AI and in comparison with mammography with both ultrasound and AI. CLINICAL IMPACT. The findings fail to show benefit of AI with respect to screening mammography performed with supplementary breast ultrasound in patients with dense breasts.
| Errataetall: |
CommentIn: AJR Am J Roentgenol. 2023 Aug 9;:. - PMID 37556603 |
|---|---|
| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2024 |
|---|---|
| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:222 |
|---|---|
| Enthalten in: |
AJR. American journal of roentgenology - 222(2024), 1 vom: 18. Jan., Seite e2329655 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Lee, Si Eun [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Artificial intelligence |
|---|
| Anmerkungen: |
Date Completed 08.02.2024 Date Revised 11.03.2024 published: Print-Electronic CommentIn: AJR Am J Roentgenol. 2023 Aug 9;:. - PMID 37556603 Citation Status MEDLINE |
|---|
| doi: |
10.2214/AJR.23.29655 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM359934862 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM359934862 | ||
| 003 | DE-627 | ||
| 005 | 20240312233132.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.2214/AJR.23.29655 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1324.xml |
| 035 | |a (DE-627)NLM359934862 | ||
| 035 | |a (NLM)37493324 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Lee, Si Eun |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Screening in Patients With Dense Breasts |b Comparison of Mammography, Artificial Intelligence, and Supplementary Ultrasound |
| 264 | 1 | |c 2024 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 08.02.2024 | ||
| 500 | |a Date Revised 11.03.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a CommentIn: AJR Am J Roentgenol. 2023 Aug 9;:. - PMID 37556603 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a BACKGROUND. Screening mammography has decreased performance in patients with dense breasts. Supplementary screening ultrasound is a recommended option in such patients, although it has yielded mixed results in prior investigations. OBJECTIVE. The purpose of this article is to compare the performance characteristics of screening mammography alone, standalone artificial intelligence (AI), ultrasound alone, and mammography in combination with AI and/or ultrasound in patients with dense breasts. METHODS. This retrospective study included 1325 women (mean age, 53 years) with dense breasts who underwent both screening mammography and supplementary breast ultrasound within a 1-month interval from January 2017 to December 2017; prior mammography and prior ultrasound examinations were available for comparison in 91.2% and 91.8%, respectively. Mammography and ultrasound examinations were interpreted by one of 15 radiologists (five staff; 10 fellows); clinical reports were used for the present analysis. A commercial AI tool was used to retrospectively evaluate mammographic examinations for presence of cancer. Screening performances were compared among mammography, AI, ultrasound, and test combinations, using generalized estimating equations. Benign diagnoses required 24 months or longer of imaging stability. RESULTS. Twelve cancers (six invasive ductal carcinoma; six ductal carcinoma in situ) were diagnosed. Mammography, standalone AI, and ultrasound showed cancer detection rates (per 1000 patients) of 6.0, 6.8, and 6.0 (all p > .05); recall rates of 4.4%, 11.9%, and 9.2% (all p < .05); sensitivity of 66.7%, 75.0%, and 66.7% (all p > .05); specificity of 96.2%, 88.7%, and 91.3% (all p < .05); and accuracy of 95.9%, 88.5%, and 91.1% (all p < .05). Mammography with AI, mammography with ultrasound, and mammography with both ultrasound and AI showed cancer detection rates of 7.5, 9.1, and 9.1 (all p > .05); recall rates of 14.9, 11.7, and 21.4 (all p < .05); sensitivity of 83.3%, 100.0%, and 100.0% (all p > .05); specificity of 85.8%, 89.1%, and 79.4% (all p < .05); and accuracy of 85.7%, 89.2%, and 79.5% (all p < .05). CONCLUSION. Mammography with supplementary ultrasound showed higher accuracy, higher specificity, and lower recall rate in comparison with mammography with AI and in comparison with mammography with both ultrasound and AI. CLINICAL IMPACT. The findings fail to show benefit of AI with respect to screening mammography performed with supplementary breast ultrasound in patients with dense breasts | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a artificial intelligence | |
| 650 | 4 | |a breast neoplasms | |
| 650 | 4 | |a computer-assisted diagnosis | |
| 650 | 4 | |a digital mammography | |
| 650 | 4 | |a sonography | |
| 700 | 1 | |a Yoon, Jung Hyun |e verfasserin |4 aut | |
| 700 | 1 | |a Son, Nak-Hoon |e verfasserin |4 aut | |
| 700 | 1 | |a Han, Kyunghwa |e verfasserin |4 aut | |
| 700 | 1 | |a Moon, Hee Jung |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t AJR. American journal of roentgenology |d 1981 |g 222(2024), 1 vom: 18. Jan., Seite e2329655 |w (DE-627)NLM000037109 |x 1546-3141 |7 nnns |
| 773 | 1 | 8 | |g volume:222 |g year:2024 |g number:1 |g day:18 |g month:01 |g pages:e2329655 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.2214/AJR.23.29655 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 222 |j 2024 |e 1 |b 18 |c 01 |h e2329655 | ||