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Chiu J, Bova D, Spear G, Ecanow J, Choate A, Besson P, Caluser C. Improving Lesion Location Reproducibility in Handheld Breast Ultrasound. Diagnostics (Basel) 2024; 14:1602. [PMID: 39125478 PMCID: PMC11311286 DOI: 10.3390/diagnostics14151602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2024] [Revised: 07/14/2024] [Accepted: 07/16/2024] [Indexed: 08/12/2024] Open
Abstract
Interoperator variability in the reproducibility of breast lesions found by handheld ultrasound (HHUS) can significantly interfere with clinical care. This study analyzed the features associated with breast mass position differences during HHUS. The ability of operators to reproduce the position of small masses and the time required to generate annotations with and without a computer-assisted scanning device (DEVICE) were also evaluated. This prospective study included 28 patients with 34 benign or probably benign small breast masses. Two operators generated manual and automated position annotations for each mass. The probe and body positions were systematically varied during scanning with the DEVICE, and the features describing mass movement were used in three logistic regression models trained to discriminate small from large breast mass displacements (cutoff: 10 mm). All models successfully discriminated small from large breast mass displacements (areas under the curve: 0.78 to 0.82). The interoperator localization precision was 6.6 ± 2.8 mm with DEVICE guidance and 19.9 ± 16.1 mm with manual annotations. Computer-assisted scanning reduced the time to annotate and reidentify a mass by 33 and 46 s on average, respectively. The results demonstrated that breast mass location reproducibility and exam efficiency improved by controlling operator actionable features with computer-assisted HHUS.
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Affiliation(s)
- James Chiu
- Department of Radiology, Endeavor Health, 2650 Ridge Ave, Evanston, IL 60201, USA
| | - Davide Bova
- Dacia Medical Clinic, 917 S Oak Park Ave, Suite B, Oak Park, IL 60304, USA
- Department of Radiology, Loyola University Medical Center, 2160 S First Ave, Maywood, IL 60153, USA
| | - Georgia Spear
- Department of Radiology, Endeavor Health, 2650 Ridge Ave, Evanston, IL 60201, USA
| | - Jacob Ecanow
- Department of Radiology, Endeavor Health, 2650 Ridge Ave, Evanston, IL 60201, USA
| | - Alyssa Choate
- Department of Radiology, Endeavor Health, 2650 Ridge Ave, Evanston, IL 60201, USA
| | - Pierre Besson
- MetriTrack Inc., 4415 Harrison St., #243, Hillside, IL 60162, USA
| | - Calin Caluser
- MetriTrack Inc., 4415 Harrison St., #243, Hillside, IL 60162, USA
- Midwest Center for Advanced Imaging, Rush University Medical System, 4355 Montgomery Rd, Naperville, IL 60564, USA
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Xu B, Luo W, Chen X, Jia Y, Wang M, Tian L, Liu Y, Lei B, Li J. Evaluation of artificial intelligent breast ultrasound on lesion detection and characterization compared with hand-held ultrasound in asymptomatic women. Front Oncol 2023; 13:1207260. [PMID: 37397384 PMCID: PMC10311017 DOI: 10.3389/fonc.2023.1207260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 06/05/2023] [Indexed: 07/04/2023] Open
Abstract
Introduction To compare the accuracy of Artificial Intelligent Breast Ultrasound (AIBUS) with hand-held breast ultrasound (HHUS) in asymptomatic women and to offer recommendations for screening in regions with limited medical resources. Methods 852 participants who underwent both HHUS and AIBUS were enrolled between December 2020 and June 2021. Two radiologists, who were unaware of the HHUS results, reviewed the AIBUS data and scored the image quality on a separate workstation. Breast imaging reporting and data system (BI-RADS) final recall assessment, breast density category, quantified lesion features, and examination time were evaluated for both devices. The statistical analysis included McNemar's test, paired t-test, and Wilcoxon test. The kappa coefficient and consistency rate were calculated in different subgroups. Results Subjective satisfaction with AIBUS image quality reached 70%. Moderate agreements were found between AIBUS with good quality images and HHUS for the BI-RADS final recall assessment (κ = 0.47, consistency rate = 73.9%) and breast density category (κ = 0.50, consistency rate = 74.8%). The lesions measured by AIBUS were statistically smaller and deeper than those measured by HHUS (P < 0.001), though they were not significant in clinical diagnosis (all < 3 mm). The total time required for the AIBUS examination and image interpretation was 1.03 (95% CI (0.57, 1.50)) minutes shorter than that of HHUS per case. Conclusion Moderate agreement was obtained for the description of the BI-RADS final recall assessment and breast density category. With image quality comparable to that of HHUS, AIBUS was superior for the efficiency of primary screening.
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Affiliation(s)
- Bin Xu
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
- West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Weidong Luo
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
- West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xin Chen
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
- West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yiping Jia
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
- West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Mengyuan Wang
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
- West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Lulu Tian
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
- West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yi Liu
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
- West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Bowen Lei
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
- West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
- West China Fourth Hospital, Sichuan University, Chengdu, China
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Dai C, Bao L, Yan H, Zhu L, Xu X, Tan Y, Yu L, Yang J, Jiang C, Shen Y. Efficiency and impact factors of anatomical intelligence for breast and hand-held ultrasound in lesion detection. JOURNAL OF CLINICAL ULTRASOUND : JCU 2023. [PMID: 37096417 DOI: 10.1002/jcu.23469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 03/20/2023] [Accepted: 04/07/2023] [Indexed: 05/03/2023]
Abstract
PURPOSE To investigate the efficiency and impact factors of anatomical intelligence for breast (AI-Breast) and hand-held ultrasound (HHUS) in lesion detection. METHODS A total of 172 outpatient women were randomly selected, underwent AI-Breast ultrasound (Group AI) once and HHUS twice. HHUS was performed by breast imaging radiologists (Group A) and general radiologists (Group B). For the AI-Breast examination, a trained technician performed the whole-breast scan and data acquisition, while other general radiologists performed image interpretation. The examination time and lesion detection rate were recorded. The impact factors for breast lesion detection, including breast cup size, number of lesions, and benign or malignant lesions were analyzed. RESULTS The detection rates of Group AI, A, and B were 92.8 ± 17.0%, 95.0 ± 13.6%, and 85.0 ± 22.9%, respectively. Comparable lesion detection rates were observed in Group AI and Group A (P > 0.05), but a significantly lower lesion detection rate was observed in Group B compared to the other two (both P < 0.05). Regarding missed diagnosis rates of malignant lesions, comparable performance was observed in Group AI, Group A, and Group B (8% vs. 4% vs. 14%, all P > 0.05). Scan times of Groups AI, A, and B were 262.15 ± 40.4 s, 237.5 ± 110.3 s, 281.2 ± 86.1 s, respectively. The scan time of Group AI was significantly higher than Group A (P < 0.01), but was slightly lower than Group B (P > 0.05). We found a strong linear correlation between scan time and cup size in Group AI (r = 0.745). No impacts of cup size and number of lesions were found on the lesion detection rate in Group AI (P > 0.05). CONCLUSIONS With the assist of AI-Breast system, the lesion detection rate of AI-Breast ultrasound was comparable to that of a breast imaging radiologist and superior to that of the general radiologist. AI-Breast ultrasound may be used as a potential approach for breast lesions surveillance.
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Affiliation(s)
- Chaochao Dai
- Department of Ultrasonography, Affiliated Hangzhou First People's Hosptital, Zhejiang University, School of Medicine, Zhejiang, Hangzhou, China
| | - Lingyun Bao
- Department of Ultrasonography, Affiliated Hangzhou First People's Hosptital, Zhejiang University, School of Medicine, Zhejiang, Hangzhou, China
| | - Hongju Yan
- Department of Ultrasonography, Affiliated Hangzhou First People's Hosptital, Zhejiang University, School of Medicine, Zhejiang, Hangzhou, China
| | - Luoxi Zhu
- Department of Ultrasonography, Affiliated Hangzhou First People's Hosptital, Zhejiang University, School of Medicine, Zhejiang, Hangzhou, China
| | - Xiaojing Xu
- Department of Ultrasonography, Affiliated Hangzhou First People's Hosptital, Zhejiang University, School of Medicine, Zhejiang, Hangzhou, China
| | - Yanjuan Tan
- Department of Ultrasonography, Affiliated Hangzhou First People's Hosptital, Zhejiang University, School of Medicine, Zhejiang, Hangzhou, China
| | - Lifang Yu
- Department of Ultrasonography, Affiliated Hangzhou First People's Hosptital, Zhejiang University, School of Medicine, Zhejiang, Hangzhou, China
| | - Jing Yang
- Department of Ultrasonography, Affiliated Hangzhou First People's Hosptital, Zhejiang University, School of Medicine, Zhejiang, Hangzhou, China
| | - Chenxiang Jiang
- Department of Ultrasonography, Affiliated Hangzhou First People's Hosptital, Zhejiang University, School of Medicine, Zhejiang, Hangzhou, China
| | - Yingzhao Shen
- Department of Ultrasonography, Affiliated Hangzhou First People's Hosptital, Zhejiang University, School of Medicine, Zhejiang, Hangzhou, China
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Long J, Bottenus N, Trahey GE. Frequency-Dependent Spatial Coherence in Conventional and Chirp Transmissions. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2021; 68:1707-1720. [PMID: 33417541 PMCID: PMC8162843 DOI: 10.1109/tuffc.2021.3050120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
The development of adaptive imaging techniques is contingent on the accurate and repeatable characterization of ultrasonic image quality. Adaptive transmit frequency selection, filtering, and frequency compounding all offer the ability to improve target conspicuity by balancing the effects of imaging resolution, the signal-to-clutter ratio, and speckle texture, but these strategies rely on the ability to capture image quality at each desired frequency. We investigate the use of broadband linear frequency-modulated transmissions, also known as chirps, to expedite the interrogation of frequency-dependent tissue spatial coherence for real-time implementations of frequency-based adaptive imaging strategies. Chirp-collected measurements of coherence are compared to those acquired by individually transmitted conventional pulses over a range of fundamental and harmonic frequencies, in order to evaluate the ability of chirps to recreate conventionally acquired coherence. Simulation and measurements in a uniform phantom free of acoustic clutter indicate that chirps replicate not only the mean coherence in a region-of-interest but also the distribution of coherence values over frequency. Results from acquisitions in porcine abdominal and human liver models show that prediction accuracy improves with chirp length. Chirps are also able to predict frequency-dependent decreases in coherence in both porcine abdominal and human liver models for fundamental and pulse inversion harmonic imaging. This work indicates that the use of chirps is a viable strategy to improve the efficiency of variable frequency coherence mapping, thus presenting an avenue for real-time implementations for frequency-based adaptive strategies.
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Flint K, Bottenus N, Bradway D, McNally P, Ellestad S, Trahey G. An Automated ALARA Method for Ultrasound: An Obstetric Ultrasound Feasibility Study. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2020; 40:10.1002/jum.15570. [PMID: 33289152 PMCID: PMC10117178 DOI: 10.1002/jum.15570] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 10/06/2020] [Accepted: 10/28/2020] [Indexed: 05/20/2023]
Abstract
OBJECTIVES Ultrasound users are advised to observe the ALARA (as low as reasonably achievable) principle, but studies have shown that most do not monitor acoustic output metrics. We developed an adaptive ultrasound method that could suggest acoustic output levels based on real-time image quality feedback using lag-one coherence (LOC). METHODS Lag-one coherence as a function of the mechanical index (MI) was assessed in 35 healthy volunteers in their second trimester of pregnancy. While imaging the placenta or the fetal abdomen, the system swept through 16 MI values ranging from 0.15 to 1.20. The LOC-versus-MI data were fit with a sigmoid curve, and the ALARA MI was selected as the point at which the fit reached 98% of its maximum. RESULTS In this study, the ALARA MI values were between 0.35 and 1.03, depending on the acoustic window. Compared to a default MI of 0.8, the pilot acquisitions suggested a lower ALARA MI 80% of the time. The contrast, contrast-to-noise ratio, generalized contrast-to-noise ratio, and LOC all followed sigmoidal trends with an increasing MI. The R2 of the fit was statistically significantly greater for LOC than the other metrics (P < .017). CONCLUSIONS These results suggest that maximum image quality can be achieved with acoustic output levels lower than the US Food and Drug Administration limits in many cases, and an automated tool could be used in real time to find the ALARA MI for specific imaging conditions. Our results support the feasibility of an automated, LOC-based implementation of the ALARA principle for obstetric ultrasound.
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Affiliation(s)
- Katelyn Flint
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA
| | - Nick Bottenus
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA
- Mechanical Engineering, Mechanical Engineering, University of Colorado, Boulder, Boulder, Colorado, USA
| | - David Bradway
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA
| | - Patricia McNally
- Department of Women's and Children's Services, Duke University Hospital, Durham, North Carolina, USA
| | - Sarah Ellestad
- Division of Maternal-Fetal Medicine, Duke University Medical Center, Durham, North Carolina, USA
| | - Gregg Trahey
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA
- Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
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Liu Y, Wu PC, Guo S, Chou PT, Deng C, Chou SW, Yuan Z, Liu TM. Low-toxicity FePt nanoparticles for the targeted and enhanced diagnosis of breast tumors using few centimeters deep whole-body photoacoustic imaging. PHOTOACOUSTICS 2020; 19:100179. [PMID: 32322488 PMCID: PMC7168769 DOI: 10.1016/j.pacs.2020.100179] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Revised: 03/11/2020] [Accepted: 03/29/2020] [Indexed: 05/10/2023]
Abstract
A considerable amount of early breast tumors grown at a depth over 2 cm in breast tissues. With high near-infrared absorption of iron-platinum (FePt) nanoparticles, we achieved few centimeters deep photoacoustic (PA) imaging for the diagnosis of breast tumors. The imaging depth can extend over 5 cm in chicken breast tissues at the low laser energy density of 20 mJ/cm2 (≤ ANSI safety limit). After anti-VEGFR conjugation and the tail-vein injection, we validated their targeting on tumor sites by the confocal microscopy and PA imaging. Using a home-made whole-body in vivo PA imaging, we found that the nanoparticles were rapidly cleared away from the site of the tumor and majorly metabolized through the liver. These results validated the clinical potential of the FePt nanoparticles in the low-toxicity PA theragnosis of early breast cancer and showed the capacity of our whole-body PA imaging technique on monitoring the dynamic biodistribution of nanoparticles in the living body.
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Affiliation(s)
- Yubin Liu
- Cancer Center, Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Pei-Chun Wu
- Cancer Center, Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Sen Guo
- Cancer Center, Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Pi-Tai Chou
- Department of Chemistry, National Taiwan University, Taipei, 10617, Taiwan
| | - Chuxia Deng
- Cancer Center, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Shang-Wei Chou
- Department of Chemistry, National Taiwan University, Taipei, 10617, Taiwan
- Corresponding author at: Department of Chemistry, National Taiwan University, Taipei, 10617, Taiwan.
| | - Zhen Yuan
- Cancer Center, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Corresponding authors.
| | - Tzu-Ming Liu
- Cancer Center, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau SAR, China
- Corresponding authors.
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Zhang E, Seiler S, Chen M, Lu W, Gu X. Boundary-aware Semi-supervised Deep Learning for Breast Ultrasound Computer-Aided Diagnosis. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2019; 2019:947-950. [PMID: 31946050 DOI: 10.1109/embc.2019.8856539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Breast ultrasound (US) is an effective imaging modality for breast cancer diagnosis. US computer-aided diagnosis (CAD) systems have been developed for decades and have employed either conventional handcrafted features or modern automatic deep-learned features, the former relying on clinical experience and the latter demanding large datasets. In this paper, we developed a novel BASDL method that integrates clinical-approved breast lesion boundary characteristics (features) into a semi-supervised deep learning (SDL) to achieve accurate diagnosis with a small training dataset. Original breast US images are converted to boundary-oriented feature maps (BFMs) using a distance-transformation coupled with a Gaussian filter. Then, the converted BFMs are used as the input of SDL network, which is characterized as lesion classification guided unsupervised image reconstruction based on stacked convolutional auto-encode (SCAE). We compared the performance of BASDL with conventional SCAE method and SDL method that used the original images as inputs, as well as SCAE method that used BFMs as inputs. Experimental results on two breast US datasets show that BASDL ranked the best among the four networks, with classification accuracy around 92.00±2.38%, which indicated that BASDL could be promising for effective breast US lesion CAD using small datasets.
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Huppe AI, Inciardi MF, Redick M, Carroll M, Buckley J, Hill JD, Gatewood JB. Automated Breast Ultrasound Interpretation Times: A Reader Performance Study. Acad Radiol 2018; 25:1577-1581. [PMID: 29661602 DOI: 10.1016/j.acra.2018.03.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 03/15/2018] [Accepted: 03/15/2018] [Indexed: 11/19/2022]
Abstract
RATIONALE AND OBJECTIVES This study aimed to determine the average time for breast radiologists of varied experience to interpret automated breast ultrasound (ABUS) examinations. MATERIALS AND METHODS A reader performance study was conducted on female patients, with ACR BI-RADS 4 breast density classifications of C or D, who received both an ABUS screening examination and a digital mammogram from 2013 to 2014 at an academic institution. Three faculty breast radiologists with varied levels of ABUS experience (advanced, intermediate, novice) read all ABUS examinations, with interpretation times and final impressions (categorized as "normal" or "abnormal") recorded for each examination. RESULTS Ninety-nine patients were included, with all readers demonstrating an average ABUS interpretation time of less than 3 minutes. Compared to the other two readers, the intermediate reader had a significantly longer mean interpretation time at 2.6 minutes (95% confidence interval 2.4-2.8; P < .001). In addition to having the shortest mean interpretation time, the novice reader also demonstrated reduced times in subsequent interpretations, with a significant decrease in interpretation times of 3.1 seconds (95% confidence interval 0.4-5.8) for every 10 ABUS examinations interpreted (P < .05). CONCLUSIONS Overall, mean ABUS interpretation time by radiologists of all experience levels was short, at less than 3 minutes per examination, which should not deter radiologists from incorporating ABUS examinations into a busy clinical environment.
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Affiliation(s)
- Ashley I Huppe
- The University of Kansas Medical Center, 3901 Rainbow Boulevard, Mail Stop 4032, Kansas City, KS 66160.
| | - Marc F Inciardi
- The University of Kansas Medical Center, 3901 Rainbow Boulevard, Mail Stop 4032, Kansas City, KS 66160
| | - Mark Redick
- The University of Kansas Medical Center, 3901 Rainbow Boulevard, Mail Stop 4032, Kansas City, KS 66160
| | - Melissa Carroll
- The University of Kansas Medical Center, 3901 Rainbow Boulevard, Mail Stop 4032, Kansas City, KS 66160
| | - Jennifer Buckley
- The University of Kansas Medical Center, 3901 Rainbow Boulevard, Mail Stop 4032, Kansas City, KS 66160
| | - Jacqueline D Hill
- The University of Kansas Medical Center, 3901 Rainbow Boulevard, Mail Stop 4032, Kansas City, KS 66160
| | - Jason B Gatewood
- The University of Kansas Medical Center, 3901 Rainbow Boulevard, Mail Stop 4032, Kansas City, KS 66160
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Moon WK, Chen IL, Chang JM, Shin SU, Lo CM, Chang RF. The adaptive computer-aided diagnosis system based on tumor sizes for the classification of breast tumors detected at screening ultrasound. ULTRASONICS 2017; 76:70-77. [PMID: 28086107 DOI: 10.1016/j.ultras.2016.12.017] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2016] [Revised: 12/06/2016] [Accepted: 12/26/2016] [Indexed: 06/06/2023]
Abstract
Screening ultrasound (US) is increasingly used as a supplement to mammography in women with dense breasts, and more than 80% of cancers detected by US alone are 1cm or smaller. An adaptive computer-aided diagnosis (CAD) system based on tumor size was proposed to classify breast tumors detected at screening US images using quantitative morphological and textural features. In the present study, a database containing 156 tumors (78 benign and 78 malignant) was separated into two subsets of different tumor sizes (<1cm and ⩾1cm) to explore the improvement in the performance of the CAD system. After adaptation, the accuracies, sensitivities, specificities and Az values of the CAD for the entire database increased from 73.1% (114/156), 73.1% (57/78), 73.1% (57/78), and 0.790 to 81.4% (127/156), 83.3% (65/78), 79.5% (62/78), and 0.852, respectively. In the data subset of tumors larger than 1cm, the performance improved from 66.2% (51/77), 68.3% (28/41), 63.9% (23/36), and 0.703 to 81.8% (63/77), 85.4% (35/41), 77.8% (28/36), and 0.855, respectively. The proposed CAD system can be helpful to classify breast tumors detected at screening US.
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Affiliation(s)
- Woo Kyung Moon
- Department of Radiology, Seoul National University College of Medicine and Seoul National University Hospital, Seoul, Republic of Korea
| | - I-Ling Chen
- Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan
| | - Jung Min Chang
- Department of Radiology, Seoul National University College of Medicine and Seoul National University Hospital, Seoul, Republic of Korea
| | - Sung Ui Shin
- Department of Radiology, Seoul National University College of Medicine and Seoul National University Hospital, Seoul, Republic of Korea
| | - Chung-Ming Lo
- Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan; Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
| | - Ruey-Feng Chang
- Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan; Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.
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Mayo RC, Parikh JR. Breast Imaging: The Face of Imaging 3.0. J Am Coll Radiol 2016; 13:1003-7. [DOI: 10.1016/j.jacr.2016.03.010] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2016] [Accepted: 03/09/2016] [Indexed: 01/17/2023]
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12
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Should the hyperechogenic halo around malignant breast lesions be included in the measurement of tumor size? Breast Cancer Res Treat 2016; 156:311-7. [DOI: 10.1007/s10549-016-3758-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2016] [Accepted: 03/14/2016] [Indexed: 11/25/2022]
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Berg WA, Mendelson EB. Technologist-performed handheld screening breast US imaging: how is it performed and what are the outcomes to date? Radiology 2014; 272:12-27. [PMID: 24956046 DOI: 10.1148/radiol.14132628] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Breast density-inform legislation is increasing the need for data on outcomes of tailored screening. Dense parenchyma can mask cancers, and denser tissue is also more likely to develop breast cancer than fatty tissue. Digital mammography is standard for women with dense breasts. Supplemental screening magnetic resonance imaging should be offered to women who meet high-risk criteria. Supplemental screening ultrasonographic (US) imaging may be appropriate in the much larger group of women with dense breasts. Both physician- and technologist-performed screening US imaging increases detection of node-negative invasive breast cancer. To meet anticipated demand in the United States, screening US images will most likely be acquired by trained technologists rather than physicians. While automated US offers standard documentation, there are few data on outcomes. US has been used diagnostically for decades to characterize masses seen by using mammography, but training specific to screening has been lacking. Standard approaches to training and documentation of technologist-performed handheld screening US imaging are needed. This article reviews the current status of technologist-performed handheld screening breast US imaging.
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Affiliation(s)
- Wendie A Berg
- From the Department of Radiology, Magee-Womens Hospital of UPMC, University of Pittsburgh School of Medicine, 300 Halket St, Pittsburgh, PA 15213 (W.A.B.); and Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Ill (E.B.M.)
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Moon WK, Lo CM, Chen RT, Shen YW, Chang JM, Huang CS, Chen JH, Hsu WW, Chang RF. Tumor detection in automated breast ultrasound images using quantitative tissue clustering. Med Phys 2014; 41:042901. [DOI: 10.1118/1.4869264] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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Delmanto A, Nahas-Neto J, Traiman P, Uemura G, Pessoa EC, Nahas EAP. Effects of soy isoflavones on mammographic density and breast parenchyma in postmenopausal women: a randomized, double-blind, placebo-controlled clinical trial. Menopause 2013; 20:1049-54. [PMID: 23481125 DOI: 10.1097/gme.0b013e3182850270] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE This study aims to evaluate the effects of soy isoflavones on breast tissue in postmenopausal women. METHODS In this randomized, double-blind, placebo-controlled study, 80 women (aged ≥ 45 y and with amenorrhea >12 mo) with vasomotor symptoms were randomized to receive either 250 mg of standardized soy extract corresponding to isoflavone 100 mg/day (n = 40) or placebo (n = 40) for 10 months. Breasts were evaluated through mammographic density and breast parenchyma using ultrasound (US) at baseline and 10-month follow-up. Independent t test, analysis of variance, Mann-Whitney U test, and χ2 trend test were used in statistical analysis. RESULTS Baseline clinical characteristics showed no significant differences between the isoflavone group and the placebo group, with mean (SD) age of 55.1 (6.0) and 56.2 (7.7) years, mean (SD) menopause duration of 6.6 (4.8) and 7.1 (4.2) years, and mean (SD) body mass index of 29.7 (5.0) and 28.5 (4.9) kg/m2, respectively (P > 0.05). The study was completed by 32 women on isoflavone and 34 women on placebo. The groups did not differ in mammographic density or breast parenchyma by US (P > 0.05). Within each group, the baseline and final moments did not differ in mammography or US parameters significantly (P > 0.05). CONCLUSIONS The use of soy isoflavone extract for 10 months does not affect breast density, as assessed by mammography and US, in postmenopausal women.
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Affiliation(s)
- Armando Delmanto
- From the Department of Gynecology and Obstetrics, Botucatu Medical School, São Paulo State University (UNESP), São Paulo, Brazil
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Elverici E, Zengin B, Nurdan Barca A, Didem Yilmaz P, Alimli A, Araz L. Interobserver and Intraobserver Agreement of Sonographic BIRADS Lexicon in the Assessment of Breast Masses. IRANIAN JOURNAL OF RADIOLOGY : A QUARTERLY JOURNAL PUBLISHED BY THE IRANIAN RADIOLOGICAL SOCIETY 2013; 10:122-7. [PMID: 24348596 PMCID: PMC3857973 DOI: 10.5812/iranjradiol.10708] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/24/2011] [Revised: 02/13/2013] [Accepted: 03/04/2013] [Indexed: 01/11/2023]
Abstract
BACKGROUND BI-RADS was first developed in 1993 for mammography and in 2003 it was redesigned for ultrasonography (US). If the observer agreement is high, the method used in the classification of lesion would be reproducible. OBJECTIVES The aim of this study is to evaluate the inter- and intraobserver agreement of sonographic BI-RADS lexicon in the categorization and feature characterization of nonpalpable breast lesions. PATIENTS AND METHODS We included 223 patients with 245 nonpalpable breast lesions who underwent ultrasound-guided wire needle localization. Two radiologists retrospectively described each lesion using sonographic BI-RADS descriptors and final assessment. The observers were blinded to mammographic images, medical history and pathologic results. Inter- and intraobserver agreement was assessed using Kappa (κ) agreement coefficient. RESULTS The interobserver agreement for sonographic descriptors changed between fair and substantial. The highest agreement was detected for mass orientation (κ=0.66). The lowest agreement was found in the margin (κ=0.33). The interobserver agreement for BI-RADS final category was found as fair (κ=0.35). The intraobserver agreement for sonographic descriptors changed between substantial and almost perfect. The intraobserver agreement of BI-RADS result category was found as substantial for observer 1 (κ=0.64) and excellent for observer 2 (κ=0.83). CONCLUSION Our results demonstrated that each observer was self-consistent in interpreting US BI-RADS classification, while interobserver agreement was relatively poor. Although it has been ten years since the description of sonographic BI-RADS lexicon, further training and periodic performance evaluations would probably help to achieve better agreement among radiologists.
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Affiliation(s)
- Eda Elverici
- Department of Radiology, Ankara Numune Education and Research Hospital, Ankara, Turkey
| | - Betul Zengin
- Department of Radiology, Yozgat State Hospital, Yozgat, Turkey
| | - Ayse Nurdan Barca
- Department of Radiology, Ankara Numune Education and Research Hospital, Ankara, Turkey
| | | | - Aysegul Alimli
- Department of Radiology, Yozgat State Hospital, Yozgat, Turkey
| | - Levent Araz
- Department of Radiology, Ankara Numune Education and Research Hospital, Ankara, Turkey
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Park CS, Kim SH, Jung NY, Choi JJ, Kang BJ, Jung HS. Interobserver variability of ultrasound elastography and the ultrasound BI-RADS lexicon of breast lesions. Breast Cancer 2013; 22:153-60. [PMID: 23584596 DOI: 10.1007/s12282-013-0465-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2013] [Accepted: 03/18/2013] [Indexed: 12/21/2022]
Abstract
BACKGROUND Elastographpy is a newly developed noninvasive imaging technique that uses ultrasound (US) to evaluate tissue stiffness. The interpretation of the same elastographic images may be variable according to reviewers. Because breast lesions are usually reported according to American College of Radiology Breast Imaging and Data System (ACR BI-RADS) lexicons and final category, we tried to compare observer variability between lexicons and final categorization of US BI-RADS and the elasticity score of US elastography. METHODS From April 2009 to February 2010, 1356 breast lesions in 1330 patients underwent ultrasound-guided core biopsy. Among them, 63 breast lesions in 55 patients (mean age, 45.7 years; range, 21-79 years) underwent both conventional ultrasound and elastography and were included in this study. Two radiologists independently performed conventional ultrasound and elastography, and another three observers reviewed conventional ultrasound images and elastography videos. Observers independently recorded the elasticity score for a 5-point scoring system proposed by Itoh et al., BI-RADS lexicons and final category using ultrasound BI-RADS. The histopathologic results were obtained and used as the reference standard. Interobserver variability was evaluated. RESULTS Of the 63 lesions, 42 (66.7 %) were benign, and 21 (33.3 %) were malignant. The highest value of concordance among all variables was achieved for the elasticity score (k = 0.59), followed by shape (k = 0.54), final category (k = 0.48), posterior acoustic features (k = 0.44), echogenecity and orientation (k = 0.43). The least concordances were margin (k = 0.26), lesion boundary (k = 0.29) and calcification (k = 0.3). CONCLUSION Elasticity score showed a higher level of interobserver agreement for the diagnosis of breast lesions than BI-RADS lexicons and final category.
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Affiliation(s)
- Chang Suk Park
- Department of Radiology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Dongsuro 56, Bupyeong-dong, Bupyeong-gu, Incheon, 403-720, Korea
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A comparison of logistic regression analysis and an artificial neural network using the BI-RADS lexicon for ultrasonography in conjunction with introbserver variability. J Digit Imaging 2013; 25:599-606. [PMID: 22270787 DOI: 10.1007/s10278-012-9457-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
To determine which Breast Imaging Reporting and Data System (BI-RADS) descriptors for ultrasound are predictors for breast cancer using logistic regression (LR) analysis in conjunction with interobserver variability between breast radiologists, and to compare the performance of artificial neural network (ANN) and LR models in differentiation of benign and malignant breast masses. Five breast radiologists retrospectively reviewed 140 breast masses and described each lesion using BI-RADS lexicon and categorized final assessments. Interobserver agreements between the observers were measured by kappa statistics. The radiologists' responses for BI-RADS were pooled. The data were divided randomly into train (n = 70) and test sets (n = 70). Using train set, optimal independent variables were determined by using LR analysis with forward stepwise selection. The LR and ANN models were constructed with the optimal independent variables and the biopsy results as dependent variable. Performances of the models and radiologists were evaluated on the test set using receiver-operating characteristic (ROC) analysis. Among BI-RADS descriptors, margin and boundary were determined as the predictors according to stepwise LR showing moderate interobserver agreement. Area under the ROC curves (AUC) for both of LR and ANN were 0.87 (95% CI, 0.77-0.94). AUCs for the five radiologists ranged 0.79-0.91. There was no significant difference in AUC values among the LR, ANN, and radiologists (p > 0.05). Margin and boundary were found as statistically significant predictors with good interobserver agreement. Use of the LR and ANN showed similar performance to that of the radiologists for differentiation of benign and malignant breast masses.
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An assessment of the performance of elastography for the investigation of BI-RADS 4 and BI-RADS 5 breast lesions: Correlations with pathological anatomy findings. Diagn Interv Imaging 2012; 93:757-66. [DOI: 10.1016/j.diii.2012.03.015] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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Chabi ML, Borget I, Ardiles R, Aboud G, Boussouar S, Vilar V, Dromain C, Balleyguier C. Evaluation of the accuracy of a computer-aided diagnosis (CAD) system in breast ultrasound according to the radiologist's experience. Acad Radiol 2012; 19:311-9. [PMID: 22310523 DOI: 10.1016/j.acra.2011.10.023] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2011] [Revised: 10/01/2011] [Accepted: 10/24/2011] [Indexed: 10/14/2022]
Abstract
RATIONALE AND OBJECTIVES The aim of this study was to evaluate the performance of a computer-aided diagnosis (CAD) system for breast ultrasound to improve the characterization of breast lesions detected on ultrasound by junior and senior radiologists. MATERIALS AND METHODS One hundred sixty ultrasound breast lesions were randomly reviewed blindly by four radiologists with different levels of expertise (from 20 years [radiologist A] to 4 months [radiologist D]), with and without the help of an ultrasound CAD system (B-CAD version 2). All lesions had been biopsied. Sensitivity and specificity with and without CAD were calculated for each radiologist for the following evaluation criteria: Breast Imaging Reporting and Data System category and the final diagnosis (benign or malignant). Intrinsic sensitivity, specificity, and predictive values of CAD alone were also calculated. RESULTS CAD detected all cancers, and its use increased radiologists' sensitivity scores when this was possible (with vs without CAD: radiologist A, 99% vs 99%; radiologist B, 96% vs 87%; radiologist C, 95% vs 88%; radiologist D, 91% vs 88%). Seven additional cancers were diagnosed. However, the low specificity of CAD (48%) decreased the specificity of radiologists, especially of the more experienced among them (with vs without CAD: radiologist A, 46% vs 70%; radiologist B, 58% vs 80%; radiologist C, 57% vs 69%; radiologist D, 71% vs 71%). CONCLUSIONS CAD for breast ultrasound appears to be a useful tool for improving the diagnosis of malignant lesions for junior radiologists. Nevertheless, its low specificity must be taken into account to limit biopsies of benign lesions.
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Calas MJG, Almeida RMVR, Gutfilen B, Pereira WCA. Interobserver concordance in the BI-RADS classification of breast ultrasound exams. Clinics (Sao Paulo) 2012; 67:185-9. [PMID: 22358246 PMCID: PMC3275126 DOI: 10.6061/clinics/2012(02)16] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Affiliation(s)
- Maria Julia G Calas
- Programa de Engenharia Biomédica - COPPE, Universidade Federal do Rio de Janeiro, Brazil.
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Meng K, Lipson JA. Utilizing a PACS-integrated ultrasound-guided breast biopsy simulation exercise to reinforce the ACR practice guideline for ultrasound-guided percutaneous breast interventional procedures during radiology residency. Acad Radiol 2011; 18:1324-8. [PMID: 21893299 DOI: 10.1016/j.acra.2011.06.003] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2011] [Revised: 06/23/2011] [Accepted: 06/27/2011] [Indexed: 12/01/2022]
Abstract
RATIONALE AND OBJECTIVES A picture archiving and communication system (PACS)-integrated ultrasound-guided (USG) breast intervention simulation exercise was designed for radiology residency education. The purpose of this study was to describe the initial experience and determine if resident understanding of the American College of Radiology (ACR) practice guideline for the performance of USG percutaneous breast interventional procedures and procedural confidence is improved with the implementation of this simulation exercise. MATERIALS AND METHODS Radiology residents (n = 11) volunteered to perform percutaneous USG cyst aspiration, 14-gauge automated core biopsy, and 10-gauge vacuum core biopsy on turkey breast phantoms, with an emphasis on capturing ultrasound images demonstrating appropriate documentation of the procedure and image annotation according to the ACR practice guideline for USG percutaneous interventions. The images were transmitted to the PACS for subsequent attending radiologist review. Survey responses regarding procedural confidence and knowledge of the ACR practice guideline were compared between residents with and without the simulator experience. RESULTS Residents with simulation exercise experience showed statistically significant increases in confidence performing USG core biopsies, operating biopsy devices and ultrasound equipment, and knowledge of appropriate needle positioning and image annotation and documentation according to the ACR practice guideline. The increased confidence seen in performing USG cyst aspiration barely missed statistical significance (P = .056), likely because of residents' baseline familiarity with the procedure. CONCLUSIONS A PACS-integrated USG breast intervention simulation exercise increases residents' procedural confidence and understanding of the ACR practice guideline for the performance of USG percutaneous breast interventional procedures.
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Affiliation(s)
- Kenneth Meng
- Department of Radiology, Breast Imaging Section, Stanford University School of Medicine, CA 94305, USA
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Cheng JZ, Chou YH, Huang CS, Chang YC, Tiu CM, Yeh FC, Chen KW, Tsou CH, Chen CM. ACCOMP: Augmented cell competition algorithm for breast lesion demarcation in sonography. Med Phys 2011; 37:6240-52. [PMID: 21302781 DOI: 10.1118/1.3512799] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Fully automatic and high-quality demarcation of sonographical breast lesions remains a far-reaching goal. This article aims to develop an image segmentation algorithm that provides quality delineation of breast lesions in sonography with a simple and friendly semiautomatic scheme. METHODS A data-driven image segmentation algorithm, named as augmented cell competition (ACCOMP) algorithm, is developed to delineate breast lesion boundaries in ultrasound images. Inspired by visual perceptual experience and Gestalt principles, the ACCOMP algorithm is constituted of two major processes, i.e., cell competition and cell-based contour grouping. The cell competition process drives cells, i.e., the catchment basins generated by a two-pass watershed transformation, to merge and split into prominent components. A prominent component is defined as a relatively large and homogeneous region circumscribed by a perceivable boundary. Based on the prominent component tessellation, cell-based contour grouping process seeks the best closed subsets of edges in the prominent component structure as the desirable boundary candidates. Finally, five boundary candidates with respect to five devised boundary cost functions are suggested by the ACCOMP algorithm for user selection. To evaluate the efficacy of the ACCOMP algorithm on breast lesions with complicated echogenicity and shapes, 324 breast sonograms, including 199 benign and 125 malignant lesions, are adopted as testing data. The boundaries generated by the ACCOMP algorithm are compared to manual delineations, which were confirmed by four experienced medical doctors. Four assessment metrics, including the modified Williams index, percentage statistic, overlapping ratio, and difference ratio, are employed to see if the ACCOMP-generated boundaries are comparable to manual delineations. A comparative study is also conducted by implementing two pixel-based segmentation algorithms. The same four assessment metrics are employed to evaluate the boundaries generated by two conventional pixel-based algorithms based on the same set of manual delineations. RESULTS The ACCOMP-generated boundaries are shown to be comparable to the manual delineations. Particularly, the modified Williams indices of the boundaries generated by the ACCOMP algorithm and the first and second pixel-based algorithms are 1.069 +/- 0.024, 0.935 +/- 0.024, and 0.579 +/- 0.013, respectively. If the modified Williams index is greater than or equal to 1, the average distance between the computer-generated boundaries and manual delineations is deemed to be comparable to that between the manual delineations. CONCLUSIONS The boundaries derived by the ACCOMP algorithm are shown to reasonably demarcate sonographic breast lesions, especially for the cases with complicated echogenicity and shapes. It suggests that the ACCOMP-generated boundaries can potentially serve as the basis for further morphological or quantitative analysis.
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Affiliation(s)
- Jie-Zhi Cheng
- Institute of Biomedical Engineering, College of Medicine and College of Engineering, National Taiwan University, Number 1, Section 1, Jen-Ai Road, Taipei 100, Taiwan.
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Intraobserver interpretation of breast ultrasonography following the BI-RADS classification. Eur J Radiol 2010; 74:525-8. [DOI: 10.1016/j.ejrad.2009.04.015] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2009] [Revised: 04/01/2009] [Accepted: 04/03/2009] [Indexed: 11/18/2022]
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Nascimento JHRD, Silva VDD, Maciel AC. Acurácia dos achados ultrassonográficos do câncer de mama: correlação da classificação BI-RADS® e achados histológicos. Radiol Bras 2009. [DOI: 10.1590/s0100-39842009000400009] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
OBJETIVO: O objetivo geral do estudo é avaliar a acurácia da ultrassonografia (BI-RADS) no diagnóstico do câncer de mama, e os objetivos específicos, descrever a frequência de apresentação dos diferentes achados ultrassonográficos e a avaliação da concordância entre observadores. MATERIAIS E MÉTODOS: Exames de 110 pacientes encaminhados para biópsia, com diagnóstico prévio de nódulos, foram reanalisados independentemente por dois médicos especialistas utilizando a nomenclatura do BI-RADS. Os achados histológicos foram utilizados como padrão-ouro. A acurácia dos achados foi determinada. As diferenças nos grupos de comparação foram analisadas com teste qui-quadrado para variáveis categóricas e a concordância entre os médicos foi calculada por meio da estatística kappa (κ). RESULTADOS: Cento e dez massas mamárias foram avaliadas pelo ultrassom, sendo que 76 (69%) foram benignas e 34 (30,9%), malignas. Foram observados, entre os radiologistas, sensibilidade variando entre 70,5% e 82,3%, valor preditivo negativo entre 81,1% e 87,5%, valor preditivo positivo entre 42,1% e 45,1%, especificidade entre 56,58% e 55,2% e acurácia entre 60,9% e 63,6%. Na avaliação entre observadores foi obtida concordância global considerada moderada (κ= 0,50). CONCLUSÃO: O BI-RADS 4ª edição é um acurado sistema para auxiliar os médicos na descrição das lesões mamárias e na tomada de condutas.
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Affiliation(s)
| | | | - Antonio Carlos Maciel
- Santa Casa de Misericórdia de Porto Alegre; Hospital de Clínicas de Porto Alegre, Brasil
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Lévy L. Comment décrire et classer une lésion en échographie du sein en 2009 ? IMAGERIE DE LA FEMME 2009. [DOI: 10.1016/j.femme.2009.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Abstract
The use of ultrasonography in dense breast remains a controversial topic. It is acknowledged that ultrasound as an adjunct to mammography increases the detection rate of breast cancers. However, the main limitation of US, in addition to its operator dependent nature, is its low specificity, leading to a high rate of false positive results. Several techniques can be used to improve the performance of US and cost/effectiveness ratio, such as Doppler imaging, harmonic imaging, spatial and frequency compound imaging, all of which are routinely available, and elastosonography, contrast US and 3D US which are still in development.
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Affiliation(s)
- I Leconte
- Département d'imagerie médicale, Cliniques Universitaires Saint-Luc, Avenue Hippocrate 10, 1200 Bruxelles.
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Clinical application of the BI-RADS final assessment to breast sonography in conjunction with mammography. AJR Am J Roentgenol 2008; 190:1209-15. [PMID: 18430833 DOI: 10.2214/ajr.07.3259] [Citation(s) in RCA: 99] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
OBJECTIVE The objective of our study was to report the results of classification of sonographic findings according to BI-RADS and to calculate the positive predictive value (PPV) for each BI-RADS assessment category. SUBJECTS AND METHODS We prospectively classified 4,668 breast sonograms according to BI-RADS final assessment category. Suspicious sonographic findings were divided into major and minor suspicious findings. Category 1 was normal and category 2 was a benign finding such as cyst or nodule with uniform and intense hyperechogenicity. A nodule neither category 2 nor category 4 or 5 was defined as category 3. A nodule with one or more suspicious findings, not category 5, was defined as category 4. A nodule with two or more major suspicious findings was defined as category 5. RESULTS Of the 4,668 cases, 321 cases failed to undergo follow-up of at least 1 year. The PPV was 0.1% in category 1 (3/2,191), 0% in category 2 (0/773), 0.8% in category 3 (6/737), 31.1% in category 4 (161/519), and 96.9% in category 5 (123/127). In palpable lesions (n = 751), the PPV was 2.2% in category 1 (2/93), 0.9% in category 3 (2/217), 54% in category 4 (107/198), and 98% in category 5 (98/100). In nonpalpable lesions (n = 3,596), the PPV was 0.05% in category 1 (1/2,098), 0.8% in category 3 (4/520), 16.8% in category 4 (54/321), and 92.6% in category 5 (25/27). CONCLUSION As with mammography, placing sonographic lesions into BI-RADS categories is useful for predicting the presence of malignancy.
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Role of sonography in the detection of contralateral metachronous breast cancer in an Asian population. AJR Am J Roentgenol 2008; 190:476-80. [PMID: 18212235 DOI: 10.2214/ajr.07.2683] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
OBJECTIVE This study was undertaken to retrospectively assess the contribution of sonographic surveillance in the early detection of metachronous contralateral breast cancer. MATERIALS AND METHODS We retrospectively reviewed the pathologic, mammographic, and sonographic records of 51 patients with surgically proven metachronous bilateral breast cancer in 2,498 surgically proven breast cancers during 2000-2006. We first evaluated cancer staging according to the method of detection used to identify metachronous breast cancers. The sensitivity of imaging studies to identify the lesions was also assessed. We compared cancer staging on the basis of whether the patient was included in a screened group, which was one in which a mammogram and sonogram were obtained within 12 months of the pathologic diagnosis of metachronous cancer. Within the screened group, we compared cancer staging on the basis of whether a screening sonogram was obtained within 6 months of the diagnosis of metachronous cancer. RESULTS The staging of metachronous cancers showed no statistically significant differences related to detection method. The sensitivity of sonography was 94% and of mammography was 80% in the detection of metachronous cancers. The cancer stage in the screened group was 0 or stage I in 81% and that in the unscreened group was stage II or III in 71% (p < 0.05). Among the screened group, no significant difference was seen in staging regardless of whether a screening sonogram was obtained in the 6 months after diagnosis of metachronous cancer (p = 0.576). CONCLUSION Sonography alone detected 14% of metachronous contralateral breast cancers. The results of this study suggest that annual additional sonography with mammography contributes to the early detection of metachronous cancers. However, sonography every 6 months is unlikely to be helpful for the early detection of metachronous cancer.
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Huang W, Tudorica LA. Detection of Breast Malignancy. Cancer Imaging 2008. [DOI: 10.1016/b978-012374212-4.50058-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
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Shen WC, Chang RF, Moon WK. Computer aided classification system for breast ultrasound based on Breast Imaging Reporting and Data System (BI-RADS). ULTRASOUND IN MEDICINE & BIOLOGY 2007; 33:1688-98. [PMID: 17681678 DOI: 10.1016/j.ultrasmedbio.2007.05.016] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2006] [Revised: 05/07/2007] [Accepted: 05/18/2007] [Indexed: 05/16/2023]
Abstract
Clinically, the ultrasound findings are evaluated by its sonographic characteristics and then assigned to assessment categories according to the definitions of Breast Imaging Reporting and Data System (BI-RADS) developed by the American College of Radiology. In this study, a computer-aided classification (CAC) system was proposed to classify the masses into assessment categories 3, 4 and 5, which simulated the clinical diagnosis of radiologists. Compared with current computer-aided diagnosis systems, the proposed CAC system classifies the indeterminate cases into BI-RADS category 4 for further diagnosis. Six hundred twenty-six cases were collected from three ultrasound systems and confirmed by pathology and retrospectively classified into categories 3, 4 and 5 by radiologists. The multinomial logistic regression model was trained as the CAC system for predicting the assessment category from the computerized BI-RADS features and from a set of machine-dependent factors. By using the machine-dependent factors to indicate the adopted ultrasound systems, the same regression model could be applied for the cases acquired from different ultrasound systems. A basic CAC system was trained by using the classification result of radiologists. A weighted CAC system, to improve the capacity of the basic CAC system in differentiating benign from malignant lesions, was trained by adding the pathologic result. Between the radiologists and the basic CAC system, a substantial agreement was indicated by Cohen's kappa statistic and the differences in either the performance indices or the A(Z) of receiver operating characteristic (ROC) analysis were not statistically significant. For the weighted CAC system, the performance indices accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 73.00% (457 of 626), 98.17% (215 of 219), 59.46% (242 of 407), 56.58% (215 of 380) and 98.37% (242 of 246), respectively; the A(Z) was 0.94; and the correlation with the radiologists was also substantial agreement. The indices accuracy and specificity of weighted CAC system, compared with those of the radiologists, were improved by 5.91% and 8.85%, respectively and the indices of sensitivity and NPV, compared with those of a conventional CAD system, were improved by 10.5% and 5.21%, respectively; all improvements were statistically significant. To classify the mass into BI-RADS assessment categories by the CAC system is feasible. Moreover, the proposed CAC system is flexible because it can be used to diagnose the cases acquired from different ultrasound systems.
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Affiliation(s)
- Wei-Chih Shen
- Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan, R.O.C
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Costantini M, Belli P, Ierardi C, Franceschini G, La Torre G, Bonomo L. Solid breast mass characterisation: use of the sonographic BI-RADS classification. Radiol Med 2007; 112:877-94. [PMID: 17885742 DOI: 10.1007/s11547-007-0189-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2006] [Accepted: 11/20/2006] [Indexed: 11/26/2022]
Abstract
PURPOSE The aim of this study was to assess the reliability of the sonographic Breast Imaging Reporting and Data System (BI-RADS) classification in differentiating benign from malignant breast masses. MATERIALS AND METHODS A total of 292 female patients with breast masses undergoing biopsy between November 2004 and March 2006 in our department were included in this study. All lesions were classified according to the sonographic BI-RADS lexicon. Sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) for the sonographic BI-RADS lexicon and PPV and NPV for each lesion category and each sonographic descriptor were calculated. The chi(2) test and the Fischer exact test were used to evaluate our results. RESULTS Univariate analysis showed a significant difference between malignant and benign groups with regard to morphology (p<0.001), horizontal-vertical diameter ratio<1 (p<0.002), orientation (p<0.001), noncircumscribed margins (p<0.001), echogenic halo (p<0.001), hypoechoic pattern (p=0.035), shadowing (p<0.001) and surrounding tissue alterations (p=0.001). The cumulative risk for malignancy was 64 and 10 times higher, respectively, in categories 5 and 4 than in category 3. CONCLUSIONS The sonographic BI-RADS lexicon is an important system for describing and classifying breast lesions.
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Affiliation(s)
- M Costantini
- Dipartimento di Bio-Immagini e Scienze Radiologiche, Università Cattolica del Sacro Cuore, Largo A. Gemelli 8, Rome, Italy.
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Tardivon A, El Khoury C, Thibault F, Wyler A, Barreau B, Neuenschwander S. [Elastography of the breast: a prospective study of 122 lesions]. ACTA ACUST UNITED AC 2007; 88:657-62. [PMID: 17541358 DOI: 10.1016/s0221-0363(07)89872-6] [Citation(s) in RCA: 58] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
OBJECTIVE To evaluate elastography in the characterization of breast nodules. MATERIAL AND METHODS Elastography (Hitachi, 7.5- to 13-MHz probe; Ueno classification, scores 1-3=benign, 4-5=malignant) was evaluated in 125 subclinical lesions in 114 patients. The results were compared to those of the ACR's BI-RADS sonography categories (benign=2 and 3, malignant=4 and 5) and to the results of the percutaneous samples taken and/or surgery (122 lesions evaluated, 59%<10 mm, 61 cancers, 61 benign lesions). RESULTS There were three technical failures (2.4%). The elastography was in agreement with histology for 101 lesions, with 13 false-negative results and eight false-positive results (sensitivity, 78.7%; specificity, 86.9%; PPV, 85.7%; NPV, 80.3%); versus agreement with the BI-RADS classification for 98 lesions with one false-negative result and 23 false-positive results (sensitivity, 98.4%; specificity, 47.5%; PPV, 65.2%; NPV, 96.7%). CONCLUSION Elastography is a simple and rapid complementary method that can improve the specificity and the PPV of morphological imaging studies of breast nodules with a low level of suspicion (BI-RADS categories 3 and 4a), which should decrease the rate of unnecessary benign biopsies.
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Affiliation(s)
- A Tardivon
- Service de Radiologie, Institut Curie, 26 rue d'Ulm, 75248 Paris cedex 05.
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Mesurolle B, Helou T, El-Khoury M, Edwardes M, Sutton EJ, Kao E. Tissue harmonic imaging, frequency compound imaging, and conventional imaging: use and benefit in breast sonography. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2007; 26:1041-51. [PMID: 17646366 DOI: 10.7863/jum.2007.26.8.1041] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
OBJECTIVE The purpose of this study was to evaluate different sonographic settings (tissue harmonic, frequency compounding, and conventional imaging) and to determine which setting optimizes breast lesion detection and lesion characterization. METHODS Four hundred thirteen consecutive breast lesions (249 benign and 164 malignant) were evaluated by sonography using 4 different modes (conventional imaging at 14 MHz, tissue harmonic imaging at 14 MHz [THI], and frequency compound imaging at 10 MHz [CI10] and 14 MHz [CI14]). The images were reviewed by consensus by 2 breast radiologists. For each image, the lesion was graded for conspicuity, mass margin assessment, echo texture assessment, overall image quality, and posterior acoustic features. RESULTS For lesion conspicuity, THI and CI14 were better than conventional imaging (P < .01) and CI10 (P < .01) particularly against a fatty background (P < .01 for THI versus conventional for a fatty background versus P = .13 for a dense background). Frequency compound imaging at 10 MHz performed the best in echo texture assessment (P < .01), as well as overall image quality (P < .01). For margin assessment, CI10 performed better for deep and large (> or =1.5-cm) lesions, whereas CI14 performed better for small (<1.5-cm) and superficial lesions. Finally, THI and CI14 increased posterior shadowing (P < .01) and posterior enhancement (P < .01). CONCLUSIONS The standard breast examination incorporates 2 distinct processes, lesion detection and lesion characterization. With respect to detection, THI is useful, especially in fatty breasts. With respect to characterization, compound imaging improves lesion echo texture assessment. No single setting in isolation can provide the necessary optimized information for both of these tasks. As such, a combination approach is best.
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Affiliation(s)
- Benoît Mesurolle
- Department of Radiology, McGill University Health Center, Montreal General Hospital, Montreal, QC, Canada.
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Shen WC, Chang RF, Moon WK, Chou YH, Huang CS. Breast ultrasound computer-aided diagnosis using BI-RADS features. Acad Radiol 2007; 14:928-39. [PMID: 17659238 DOI: 10.1016/j.acra.2007.04.016] [Citation(s) in RCA: 70] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2007] [Revised: 04/20/2007] [Accepted: 04/21/2007] [Indexed: 12/29/2022]
Abstract
RATIONALE AND OBJECTIVES Based on the definitions in mass category of Breast Imaging Reporting and Data System developed by American College of Radiology, eight computerized features including shape, orientation, margin, lesion boundary, echo pattern, and posterior acoustic feature classes are proposed. MATERIALS AND METHODS Our experimental database consists of 265 pathology-proven cases including 180 benign and 85 malignant masses. The capacity of each proposed feature in differentiating malignant from benign masses was validated by Student's t test and the correlation between each proposed feature and the pathological result was evaluated by point biserial coefficient. Binary logistic regression model was used to relate all proposed features and pathological result as a computer-aided diagnosis (CAD) system. The diagnostic value of each proposed feature in the CAD system was further evaluated by the feature selection methods. Additionally, the likelihood of malignancy for each individual feature was also estimated by binary logistic regression. RESULTS On each proposed feature, the malignant cases were significantly different from the benign ones. The correlation between the angular characteristic and pathological result was indicated as very high. Three substantial correlations appear in features irregular shape, undulation characteristic, and degree of abrupt interface, but the relationship for orientation feature is low. For the constructed CAD system, the performance indices accuracy, sensitivity, specificity, PPV, and NPV were 91.70% (243 of 265), 90.59% (77 of 85), 92.22% (166 of 180), 84.62% (77 of 91), and 95.40% (166 of 174), respectively, and the area index in the ROC analysis was 0.97. Compared with the significant contribution of angular characteristic, the diagnostic values of posterior acoustic feature and orientation feature were relatively low for the CAD system. When three or more angular characteristics are discovered or the degree of abrupt interface is lower than 18, the likelihood of malignancy could be predicted as greater than 40%. CONCLUSION The computerized BI-RADS sonographic features conform to the sign of malignancy in the clinical experience and efficiently help the CAD system to diagnose the mass.
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Affiliation(s)
- Wei-Chih Shen
- Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan, ROC
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Levy L, Suissa M, Chiche JF, Teman G, Martin B. BIRADS ultrasonography. Eur J Radiol 2007; 61:202-11. [PMID: 17215097 DOI: 10.1016/j.ejrad.2006.08.035] [Citation(s) in RCA: 48] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2006] [Revised: 08/21/2006] [Accepted: 08/24/2006] [Indexed: 11/20/2022]
Abstract
The fourth edition of the BIRADS mammography appeared in 2003 and is now associated with the first editions of the BIRADS ultrasound and MRI. BIRADS is a system of assistance to the drafting of the reports more and more used in the world and soon directly implemented on mammography and ultrasound units. The categories of evaluation of the BIRADS allow a clear synthesis of the descriptive data resulting from the use of the lexicon and invite the radiologist to a reasoned, objective and less intuitive step. They give an action to be taken and responsibility to the radiologist and the referring physicians in the assumption of the patients.
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Affiliation(s)
- L Levy
- Institut de Radiologie, 31 Avenue Hoche, 75008 Paris, France.
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Boisserie-Lacroix M, Lebiez-Michel N, Cavigni P, Bentolila J, Laumonier H, Bouzgarrou M, Trillaud H. [Breast ultrasonography: an overview]. ACTA ACUST UNITED AC 2006; 34:1170-7. [PMID: 17140836 DOI: 10.1016/j.gyobfe.2006.10.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2006] [Accepted: 10/11/2006] [Indexed: 11/18/2022]
Abstract
The most important roles of ultrasound in breast imaging include the diagnosis of cysts and the characterization of masses that have been incompletely assessed by mammography. Ultrasonography techniques such as harmonic and compound imaging have recently been introduced and are more efficient than conventional imaging in terms of lesion conspicuity and the characterization of breast nodule. The BI-RADS classification is an important system for describing and classifying breast lesions. With this approach, a population of benign solid breast lesions that does not require biopsy can be accurately defined. Ultrasonography should be performed as first-line examination in juvenile, in pregnant women and in patients with inflammatory syndrome. Ultrasound can detect mammographically occult breast the way they develop.
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Affiliation(s)
- M Boisserie-Lacroix
- Service de radiologie (Docteur-Trillaud), CHU de Saint-André, 1, rue Jean-Burguet, 33075 Bordeaux cedex, France.
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Berg WA, Blume JD, Cormack JB, Mendelson EB. Operator dependence of physician-performed whole-breast US: lesion detection and characterization. Radiology 2006; 241:355-65. [PMID: 17057064 DOI: 10.1148/radiol.2412051710] [Citation(s) in RCA: 133] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
PURPOSE To prospectively examine operator dependence of lesion detection, description, and interpretation when experienced breast radiologists perform whole-breast ultrasonography (US). MATERIALS AND METHODS Institutional review board approval was obtained for the HIPAA-compliant study. Ten women (aged 19-53 years; mean, 37.4 years; 20 breasts) with numerous known breast lesions consented to participate. Eleven breast radiologists, who passed experience and qualification requirements for a screening breast US trial and consented to participate, scanned both breasts in all participants and documented images of each detected lesion and its size, location, features, palpability, and Breast Imaging Reporting and Data System final assessment. Intraclass correlation coefficients (ICCs) were used to measure agreement on lesion size and location, and kappa statistics were calculated for agreement on features and final assessments compared with consensus. RESULTS Eighty-eight unique lesions were identified by at least two investigators (five to 13 lesions per participant). Mean diameter was 6.7 mm (standard error, 0.4; range, 2-22 mm), and eight lesions (9%) were palpable. Of 968 potential detections (88 lesions, 11 investigators), 536 (55%) detections were made. Individual investigators detected between 43 (49%) and 58 (66%) lesions. Larger lesions were more consistently detected: Detection rates were six of 33 lesions (18%) at 3 mm or smaller; 164 of 374 (43.9%) at 3.1-5 mm; 145 of 275 (52.7%) at 5.1-7 mm; 119 of 176 (67.6%) at 7.1-9 mm; 38 of 44 (86%) at 9.1-11 mm; and 64 of 66 (97%) lesions larger than 11 mm (P < .001). ICCs for clockface, distance from nipple, and individual lesion diameter all exceeded 0.7, indicating high reliability. For shape, margins, and final assessments of solid lesions, kappa values were 0.62, 0.67 (substantial agreement), and 0.52 (moderate agreement), respectively. Of 110 detections of consensus cysts 8 mm and smaller, 15 (14%) detections were considered to be of solid lesions by at least one reader. CONCLUSION Larger lesions (>11 mm) are most consistently detected, with fewer than half of lesions 5 mm or smaller in mean diameter identified; substantial agreement was found for description of lesion size, location, and key features, and moderate agreement was found for lesion management.
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Affiliation(s)
- Wendie A Berg
- American Radiology Services, Johns Hopkins Green Spring, 10755 Falls Rd, Suite 440, Lutherville, MD 21093, USA.
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Costantini M, Belli P, Lombardi R, Franceschini G, Mulè A, Bonomo L. Characterization of solid breast masses: use of the sonographic breast imaging reporting and data system lexicon. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2006; 25:649-59; quiz 661. [PMID: 16632790 DOI: 10.7863/jum.2006.25.5.649] [Citation(s) in RCA: 106] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
OBJECTIVE The purpose of this study was to determine the reliability of sonographic American College of Radiology Breast Imaging Reporting And Data System (BI-RADS) classification in differentiating benign from malignant breast masses. METHODS One hundred seventy-eight breast masses studied by sonography with a known diagnosis were reviewed. All lesions were classified according to the sonographic BI-RADS lexicon. Pathologic results were compared with sonographic features. Sensitivity, specificity, accuracy, and positive predictive value (PPV) and negative predictive value (NPV) for the sonographic BI-RADS lexicon were calculated. RESULTS Twenty-six cases were assigned to class 3, 73 to class 4, and 79 to class 5. Pathologic results revealed 105 malignant and 73 benign lesions. The sonographic BI-RADS lexicon showed 71.3% accuracy, 98.1% sensitivity, 32.9% specificity, 67.8% PPV, and 92.3% NPV. The NPV for class 3 was 92.3%. The PPVs for classes 4 and 5 were 46.6% and 87.3%. Typical signs of malignancy were irregular shape, antiparallel orientation, noncircumscribed margin, echogenic halo, and decreased sound transmission. Typical signs of benignity were oval shape and circumscribed margin. CONCLUSIONS The sonographic BI-RADS lexicon is an important system for describing and classifying breast lesions.
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Jacobs MA, Ouwerkerk R, Wolff AC, Stearns V, Bottomley PA, Barker PB, Argani P, Khouri N, Davidson NE, Bhujwalla ZM, Bluemke DA. Multiparametric and multinuclear magnetic resonance imaging of human breast cancer: current applications. Technol Cancer Res Treat 2005; 3:543-50. [PMID: 15560711 DOI: 10.1177/153303460400300603] [Citation(s) in RCA: 35] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
The exploration of novel imaging methods that have the potential to improve specificity for the identification of malignancy is still critically needed in breast imaging. Changes in physiologic alterations of soft tissue water associated with breast cancer can be visualized by magnetic resonance (MR) imaging. However, it is unlikely that a single MR parameter can characterize the complexity of breast tissue. Techniques such as multiparametric MR imaging, proton magnetic resonance spectroscopic (MRSI) imaging, and 23Na sodium MR imaging when used in combination provide a comprehensive data set with potentially more power to diagnose breast disease than any single measure alone. A combination of MR, MRSI, and 23Na sodium MR parameters may be examined in a single MR imaging examination, potentially resulting in improved specificity for radiologic evaluation of malignancy.
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Affiliation(s)
- Michael A Jacobs
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
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Baez E, Strathmann K, Vetter M, Madjar H, Hackelöer BJ. Likelihood of malignancy in breast lesions characterised by ultrasound with a combined diagnostic score. ULTRASOUND IN MEDICINE & BIOLOGY 2005; 31:179-184. [PMID: 15708456 DOI: 10.1016/j.ultrasmedbio.2004.10.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2004] [Revised: 10/09/2004] [Accepted: 10/14/2004] [Indexed: 05/24/2023]
Abstract
To determine the positive predictive value of breast ultrasound (US) categories and US features, isolated and in combination, 398 consecutive sonographically diagnosed breast tumours with histologic or cytologic diagnosis were reviewed. Tumour characterisation and the sonographer's diagnoses were recorded prospectively using the diagnostic classification of the European Society of Mastology (EUSOMA) (U2 = probably benign lesion, U3 = an abnormality present of indeterminate significance, U4 = features suspicious of malignancy). In addition, based on the likelihood of malignancy of each US characteristic, a diagnostic score was developed. These two measures were compared. US-guided biopsy revealed 338 benign and 60 (55 invasive and 5 noninvasive) malignant lesions. EUSOMA and diagnostic score classifications did not differ significantly. If all breast tumours classified U3 and U4 were to be tested, every second biopsy (48.3%) would have revealed a carcinoma with a negative predictive value of 99.3%. The frequency of carcinoma in sonographically benign lesions (U2 or score 1) was 0.7 and 2.2%, respectively, an incidence similar to that with mammographic lesions classified as BI-RADS 3 (Breast Imaging Reporting and Data System, probably benign, short interval follow-up suggested). Thus, given that clinical symptoms and real-time imaging influence the sonographer's interpretation, the proposed diagnostic score can improve the diagnostic accuracy of the breast sonogram with the result of reducing invasive testing and maintaining a high detection rate.
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Affiliation(s)
- E Baez
- Department of Obstetrics and Gynecology, University of Münster, Münster, Germany.
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Où en est-on de la classification bi-rads en échographie ? IMAGERIE DE LA FEMME 2004. [DOI: 10.1016/s1776-9817(04)94794-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Abstract
Ultrasound is an important imaging modality in evaluating the breast. One of the most common uses of ultrasound is to help distinguish benign from malignant breast disease, primarily with gray-scale ultrasound but also with Doppler ultrasound. Another common use is to provide guidance for interventional procedures. Less common uses include assisting in staging of breast cancer and evaluating patients with implants. Recently there has been an interest in using ultrasound to screen asymptomatic women for breast cancer, as is done with mammography. Further studies must be performed to assess if this reduces mortality from breast cancer. Although primarily used to image the female breast, ultrasound also can be used to evaluate breast-related concerns in men. Uses of contrast-enhanced ultrasound are still experimental and would add an invasive component to an otherwise noninvasive study.
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Affiliation(s)
- Tejas S Mehta
- Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215, USA.
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