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Juliano M, Samreen N, Chacko C, Heller SL. Clinical role of abbreviated and ultrafast MRI in breast imaging. Br J Radiol 2024; 97:1511-1516. [PMID: 38676660 PMCID: PMC11332674 DOI: 10.1093/bjr/tqae079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 03/04/2024] [Accepted: 04/11/2024] [Indexed: 04/29/2024] Open
Abstract
Current breast cancer screening relies on mammography, digital breast tomosynthesis and breast ultrasound. In select populations, breast MRI is also of great utility. However, multiple factors limit widespread use of breast MRI for screening. Efforts have been made to increase the availability of breast MRI for screening, in large part due to the increased cancer detection rate of breast MRI compared to mammography. Techniques include shortening standard breast MRI protocols with the potential for accommodating MRI screening in a higher number of patients. This review will explain the role of abbreviated breast MRI and ultrafast breast MRI in breast imaging, and detail how these approaches differ from standard dynamic contrast-enhanced breast MRI. In addition, limitations and advantages of these techniques will also be discussed.
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Affiliation(s)
- Mario Juliano
- UW Health Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53792, United States
| | - Naziya Samreen
- Department of Radiology, Confluence Health, Wenatchee, WA, 98802, United States
| | - Celin Chacko
- Department of Radiology, Columbia University, New York, NY, 10032, United States
| | - Samantha L Heller
- NYU Langone Department of Radiology, New York University, New York, NY, 10012, United States
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2
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Kuhl CK. Abbreviated Breast MRI: State of the Art. Radiology 2024; 310:e221822. [PMID: 38530181 DOI: 10.1148/radiol.221822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Abbreviated MRI is an umbrella term, defined as a focused MRI examination tailored to answer a single specific clinical question. For abbreviated breast MRI, this question is: "Is there evidence of breast cancer?" Abbreviated MRI of the breast makes maximum use of the fact that the kinetics of breast cancers and of benign tissue differ most in the very early postcontrast phase; therefore, abbreviated breast MRI focuses on this period. The different published approaches to abbreviated MRI include the following three subtypes: (a) short protocols, consisting of a precontrast and either a single postcontrast acquisition (first postcontrast subtracted [FAST]) or a time-resolved series of postcontrast acquisitions with lower spatial resolution (ultrafast [UF]), obtained during the early postcontrast phase immediately after contrast agent injection; (b) abridged protocols, consisting of FAST or UF acquisitions plus selected additional pulse sequences; and (c) noncontrast protocols, where diffusion-weighted imaging replaces the contrast information. Abbreviated MRI was proposed to increase tolerability of and access to breast MRI as a screening tool. But its widening application now includes follow-up after breast cancer and even diagnostic assessment. This review defines the three subtypes of abbreviated MRI, highlighting the differences between the protocols and their clinical implications and summarizing the respective evidence on diagnostic accuracy and clinical utility.
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Affiliation(s)
- Christiane K Kuhl
- From the Department of Diagnostic and Interventional Radiology, University Hospital Aachen, RWTH Pauwelsstr 30, 52074 Aachen, Germany
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3
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Hellgren R, Tolocka E, Saracco A, Wilczek B, Sundbom A, Hall P, Dickman PW. Comparing the diagnostic accuracy, reading time, and inter-rater agreement of breast MRI abbreviated and full protocols: a multi-reader study. Acta Radiol 2024; 65:195-201. [PMID: 38115682 PMCID: PMC10903132 DOI: 10.1177/02841851231216552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 11/02/2023] [Indexed: 12/21/2023]
Abstract
BACKGROUND Earlier studies have shown that abbreviated protocol magnetic resonance imaging (AB-MRI) has similar diagnostic accuracy as the full protocol (Full MRI). PURPOSE To compare the diagnostic accuracy, reading time, and inter-rater agreement of AB-MRI to Full MRI among women without known increased familial risk of breast cancer or prior biopsy. MATERIAL AND METHODS In total, 395 MRI examinations were included in this study. Three readers were blinded to all patient information. The AB-MRI and Full MRI were read separately and in a different random order for each of the readers. Scores 1-2 were considered test negative while scores 3-5 were test positive. A positive reference test was the diagnosis of malignancy; a negative reference test was the absence of a diagnosis of breast cancer within a two-year follow-up. We used a generalized estimating equations approach to compare sensitivity and specificity between the two protocols. We used t-tests to compare the average reading time and Krippendorff's alpha to compare inter-rater agreement. RESULTS MRI examinations of 395 women (median age=56 years) were evaluated. For AB-MRI and Full MRI, respectively, the sensitivity was 93.0% (95% CI=90.6-95.0) vs. 92.0% (95% CI=89.4-94.1), the specificity was 91.7% (95% CI=90.3-92.9) vs. 94.3% (95% CI=93.2-95.3), average reading time was 67 vs. 126 s, and the inter-rater agreement 0.79 vs. 0.83. The difference in sensitivity was not statistically significant (P=0.840), but the difference in specificity was significant (P=0.003). CONCLUSION AB-MRI has similar sensitivity, but somewhat lower specificity. The average reading time for the abbreviated protocol is lower, as is inter-rater agreement.
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Affiliation(s)
- Roxanna Hellgren
- Department of Medical Imaging, Division of Breast Imaging, Södersjukhuset, Stockholm, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ernst Tolocka
- Department of Medical Imaging, Division of Breast Imaging, Södersjukhuset, Stockholm, Sweden
| | - Ariel Saracco
- Department of Mammography, Evidia, Stockholm, Sweden
| | - Brigitte Wilczek
- Department of Medical Imaging, Division of Breast Imaging, Södersjukhuset, Stockholm, Sweden
| | - Ann Sundbom
- Department of Medical Imaging, Division of Breast Imaging, Södersjukhuset, Stockholm, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Paul W Dickman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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4
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Xu Z, Rauch DE, Mohamed RM, Pashapoor S, Zhou Z, Panthi B, Son JB, Hwang KP, Musall BC, Adrada BE, Candelaria RP, Leung JWT, Le-Petross HTC, Lane DL, Perez F, White J, Clayborn A, Reed B, Chen H, Sun J, Wei P, Thompson A, Korkut A, Huo L, Hunt KK, Litton JK, Valero V, Tripathy D, Yang W, Yam C, Ma J. Deep Learning for Fully Automatic Tumor Segmentation on Serially Acquired Dynamic Contrast-Enhanced MRI Images of Triple-Negative Breast Cancer. Cancers (Basel) 2023; 15:4829. [PMID: 37835523 PMCID: PMC10571741 DOI: 10.3390/cancers15194829] [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: 08/09/2023] [Revised: 09/10/2023] [Accepted: 09/22/2023] [Indexed: 10/15/2023] Open
Abstract
Accurate tumor segmentation is required for quantitative image analyses, which are increasingly used for evaluation of tumors. We developed a fully automated and high-performance segmentation model of triple-negative breast cancer using a self-configurable deep learning framework and a large set of dynamic contrast-enhanced MRI images acquired serially over the patients' treatment course. Among all models, the top-performing one that was trained with the images across different time points of a treatment course yielded a Dice similarity coefficient of 93% and a sensitivity of 96% on baseline images. The top-performing model also produced accurate tumor size measurements, which is valuable for practical clinical applications.
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Affiliation(s)
- Zhan Xu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (Z.X.)
| | - David E. Rauch
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (Z.X.)
| | - Rania M. Mohamed
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sanaz Pashapoor
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Zijian Zhou
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (Z.X.)
| | - Bikash Panthi
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (Z.X.)
| | - Jong Bum Son
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (Z.X.)
| | - Ken-Pin Hwang
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (Z.X.)
| | - Benjamin C. Musall
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (Z.X.)
| | - Beatriz E. Adrada
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Rosalind P. Candelaria
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jessica W. T. Leung
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Huong T. C. Le-Petross
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Deanna L. Lane
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Frances Perez
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jason White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Alyson Clayborn
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Brandy Reed
- Department of Clinical Research Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Huiqin Chen
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jia Sun
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Peng Wei
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Alastair Thompson
- Section of Breast Surgery, Baylor College of Medicine, Houston, TX 77030, USA
| | - Anil Korkut
- Department of Bioinformatics & Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Lei Huo
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Kelly K. Hunt
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jennifer K. Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Debu Tripathy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Wei Yang
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Clinton Yam
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (Z.X.)
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Ramli Hamid MT, Ab Mumin N, Wong YV, Chan WY, Rozalli FI, Rahmat K. The effectiveness of an ultrafast breast MRI protocol in the differentiation of benign and malignant breast lesions. Clin Radiol 2023; 78:444-450. [PMID: 37029001 DOI: 10.1016/j.crad.2023.03.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 02/28/2023] [Accepted: 03/08/2023] [Indexed: 04/08/2023]
Abstract
AIM To evaluate the effectiveness of an ultrafast breast magnetic resonance imaging (MRI) protocol in differentiating benign and malignant breast lesions. MATERIALS AND METHODS Fifty-four patients with Breast Imaging Reporting and Data System (BI-RADS) 4 or 5 lesions were recruited between July 2020 to May 2021. A standard breast MRI was performed with the inclusion of the ultrafast protocol between the unenhanced sequence and the first contrast-enhanced sequence. Three radiologists performed image interpretation in consensus. Ultrafast kinetic parameters analysed included the maximum slope (MS), time to enhancement (TTE), and arteriovenous index (AVI). These parameters were compared using receiver operating characteristics with p-values of <0.05 considered to indicate statistical significance. RESULTS Eighty-three histopathological proven lesions from 54 patients (mean age 53.87 years, SD 12.34, range 26-78 years) were analysed. Forty-one per cent (n=34) were benign and 59% (n=49) were malignant. All malignant and 38.2% (n=13) benign lesions were visualised on the ultrafast protocol. Of the malignant lesions, 77.6% (n=53) were invasive ductal carcinoma (IDC) and 18.4% (n=9) were ductal carcinoma in situ (DCIS). The MS for malignant lesions (13.27%/s) were significantly larger than for benign (5.45%/s; p<0.0001). No significant differences were seen for TTE and AVI. The area under the ROC curve (AUC) for the MS, TTE, and AVI were 0.836, 0.647, and 0.684, respectively. Different types of invasive carcinoma had similar MS and TTE. The MS of high-grade DCIS was also similar to that of IDC. Lower MS values were observed for low-grade (5.3%/s) compared to high-grade DCIS (14.8%/s) but the results were not significant statistically. CONCLUSION The ultrafast protocol showed potential to discriminate between malignant and benign breast lesions with high accuracy using MS.
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Affiliation(s)
- M T Ramli Hamid
- Department of Radiology, Faculty of Medicine, University Teknologi MARA, Sungai Buloh, Selangor, Malaysia.
| | - N Ab Mumin
- Department of Radiology, Faculty of Medicine, University Teknologi MARA, Sungai Buloh, Selangor, Malaysia
| | - Y V Wong
- Department of Biomedical Imaging, University Malaya Research Imaging Centre, Kuala Lumpur, Malaysia
| | - W Y Chan
- Department of Biomedical Imaging, University Malaya Research Imaging Centre, Kuala Lumpur, Malaysia; Department of Radiology, Gleneagles Hospital, Kuala Lumpur, Malaysia
| | - F I Rozalli
- Department of Biomedical Imaging, University Malaya Research Imaging Centre, Kuala Lumpur, Malaysia
| | - K Rahmat
- Department of Biomedical Imaging, University Malaya Research Imaging Centre, Kuala Lumpur, Malaysia.
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Milon A, Flament V, Gueniche Y, Kermarrec E, Chabbert-Buffet N, Darai É, Touboul C, Razakamanantsoa L, Thomassin-Naggara I. How to optimize MRI breast protocol? The value of combined analysis of ultrafast and diffusion-weighted MRI sequences. Diagn Interv Imaging 2023; 104:284-291. [PMID: 36801096 DOI: 10.1016/j.diii.2023.01.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 01/27/2023] [Accepted: 01/30/2023] [Indexed: 02/17/2023]
Abstract
PURPOSE The purpose of this retrospective study was to demonstrate the validity of early enhancement criteria on ultrafast magnetic resonance imaging (MRI) sequence to predict malignancy in a large population, and the benefit of diffusion-weighted imaging (DWI) to improve the performance of breast MRI. MATERIAL AND METHODS Women who underwent breast MRI examination between April 2018 and September 2020 and further breast biopsy were retrospectively included. Two readers quoted the different conventional features and classified the lesion according to the BI-RADS classification based on the conventional protocol. Then, the readers checked for the presence of early enhancement (≤ 30 s) on ultrafast sequence and the presence of an apparent diffusion coefficient (ADC) ≥ 1.5 × 10-3 mm2/s to classify the lesions based on morphology and these two functional criteria only. RESULTS Two hundred fifty-seven women (median age: 51 years; range: 16-92 years) with 436 lesions (157 benign, 11 borderline and 268 malignant) were included. A MRI protocol plus two simple functional features, early enhancement (≤ 30 s) and an ADC value ≥ 1.5 × 10-3 mm2/s, had a greater accuracy than the conventional protocol to distinguish benign from malignant breast lesions with or without ADC value (P = 0.01 and P = 0.001, respectively) on MRI, mainly due to better classification of benign lesions (increased specificity) with increasing diagnostic confidence of 3.7% and 7.8% respectively. CONCLUSION BI-RADS analysis based on a simple short MRI protocol plus early enhancement on ultrafast sequence and ADC value has a greaterr diagnostic accuracy than a conventional protocol and may avoid unnecessary biopsy.
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Affiliation(s)
- Audrey Milon
- Department of Radiology, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, 75020, Paris, France.
| | - Vincent Flament
- Department of Radiology, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, 75020, Paris, France
| | - Yoram Gueniche
- Department of Radiology, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, 75020, Paris, France
| | - Edith Kermarrec
- Department of Radiology, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, 75020, Paris, France
| | - Nathalie Chabbert-Buffet
- Sorbonne Université, Institut Universitaire de Cancérologie, 75005, Paris, France; Department of Gynecology and Obstetrics, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, 75020, Paris, France
| | - Émile Darai
- Sorbonne Université, Institut Universitaire de Cancérologie, 75005, Paris, France; Department of Gynecology and Obstetrics, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, 75020, Paris, France
| | - Cyril Touboul
- Sorbonne Université, Institut Universitaire de Cancérologie, 75005, Paris, France; Department of Gynecology and Obstetrics, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, 75020, Paris, France
| | - Leo Razakamanantsoa
- Department of Radiology, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, 75020, Paris, France
| | - Isabelle Thomassin-Naggara
- Department of Radiology, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, 75020, Paris, France; Sorbonne Université, Institut Universitaire de Cancérologie, 75005, Paris, France
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7
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Kim H, Ko EY, Kim KE, Kim MK, Choi JS, Ko ES, Han BK. Assessment of Enhancement Kinetics Improves the Specificity of Abbreviated Breast MRI: Performance in an Enriched Cohort. Diagnostics (Basel) 2022; 13:diagnostics13010136. [PMID: 36611428 PMCID: PMC9818206 DOI: 10.3390/diagnostics13010136] [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: 11/19/2022] [Revised: 12/28/2022] [Accepted: 12/29/2022] [Indexed: 01/04/2023] Open
Abstract
Objective: To investigate the added value of kinetic information for breast lesion evaluation on abbreviated breast MRI (AB-MRI). Methods: This retrospective study analyzed 207 breast lesions with Breast Imaging Reporting and Data System categories 3, 4, or 5 on AB-MRI in 198 consecutive patients who had breast MRI for screening after breast cancer surgery between January 2017 and December 2019. All lesions were pathologically confirmed or stable on follow-up images for 2 years or more. Kinetic information of the lesions regarding the degree and rate of enhancement on the first post-contrast-enhanced image and the enhancement curve type from two post-contrast-enhanced images were analyzed on a commercially available computer-assisted diagnosis system. The diagnostic performances of AB-MRI with morphological analysis alone and with the addition of kinetic information were compared using the McNemar test. Results: Of 207 lesions, 59 (28.5%) were malignant and 148 (71.5%) were benign. The addition of an enhancement degree of ≥90% to the morphological analysis significantly increased the specificity of AB-MRI (29.7% vs. 52.7%, p < 0.001) without significantly reducing the sensitivity (94.9% vs. 89.8%, p = 0.083) compared to morphological analysis alone. Unnecessary biopsy could have been avoided in 34 benign lesions, although three malignant lesions could have been missed. For detecting invasive cancer, adding an enhancement degree ≥107% to the morphological analysis significantly increased the specificity (26.5% vs. 57.6%, p < 0.001) without significantly decreasing the sensitivity (94.6% vs. 86.5%, p = 0.083). Conclusion: Adding the degree of enhancement on the first post-contrast-enhanced image to the morphological analysis resulted in higher AB-MRI specificity without compromising its sensitivity.
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Kataoka M, Iima M, Miyake KK, Matsumoto Y. Multiparametric imaging of breast cancer: An update of current applications. Diagn Interv Imaging 2022; 103:574-583. [DOI: 10.1016/j.diii.2022.10.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 10/26/2022] [Indexed: 11/21/2022]
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Ramtohul T, Tescher C, Vaflard P, Cyrta J, Girard N, Malhaire C, Tardivon A. Prospective Evaluation of Ultrafast Breast MRI for Predicting Pathologic Response after Neoadjuvant Therapies. Radiology 2022; 305:565-574. [PMID: 35880977 DOI: 10.1148/radiol.220389] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Ultrafast dynamic contrast-enhanced (DCE) MRI parameters are associated with breast cancer aggressiveness. However, the role of these parameters as predictive biomarkers for pathologic response after neoadjuvant chemotherapy (NAC) has been poorly investigated. Purpose To assess whether semiquantitative perfusion parameters calculated at initial ultrafast DCE MRI are associated with early prediction for pathologic response after NAC in participants with breast cancer. Materials and Methods This prospective single-center study included consecutive women with nonmetastatic invasive breast cancer treated with NAC followed by surgery who underwent initial ultrafast DCE MRI between December 2020 and August 2021. Six semiquantitative ultrafast DCE MRI parameters were calculated for each participant from the fitted time-signal intensity curve. Multivariable logistic regression was used to identify independent predictors of pathologic complete response (pCR) and residual cancer burden (RCB). Results Fifty women (mean age, 49 years ± 12 [SD]) were included in the study; 20 achieved pCR and 25 achieved low RCB (RCB-0 and I). A wash-in slope (WIS) cutoff value of 1.6% per second had a sensitivity of 94% (17 of 18 participants) and a specificity of 59% (19 of 32 participants) for pCR. A WIS of more than 1.6% per second (odds ratio [OR], 8.4 [95% CI: 1.5, 48.2]; P = .02), human epidermal growth factor receptor 2 (HER2) positivity (OR, 6.3 [95% CI: 1.5, 27.4]; P = .01), and tumor-infiltrating lymphocytes of more than 10% (OR, 6.9 [95% CI: 1.3, 37.7]; P = .03) were independent predictive factors of pCR. The area under the receiver operating characteristic curve of the three-component model, which included WIS, tumor-infiltrating lymphocytes, and HER2 positivity, was 0.92 (95% CI: 0.84, 0.99). A WIS of more than 1.6% per second was associated with higher pCR rates in the HER2-positive (OR, 21.7 [95% CI: 1.8, 260.6]; P = .02) breast cancer subgroup. For luminal HER2-negative and triple-negative breast cancers, a WIS of more than 1.6% per second was associated with low RCB (OR, 11.0 [95% CI: 1.1, 106.4]; P = .04). Conclusion The wash-in slope (WIS) assessment at initial ultrafast dynamic contrast-enhanced MRI may be used to predict pathologic complete response (pCR) in participants with breast cancer. The WIS value was used to identify two subsets of human epidermal growth factor receptor 2-positive cancers with distinct pCR rates. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Lee and Moy in this issue.
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Affiliation(s)
- Toulsie Ramtohul
- From the Departments of Radiology (T.R., C.T., C.M., A.T.), Medical Oncology (P.V.), Diagnostic and Theranostic Medicine - Pathology (J.C.), and Surgical Oncology (N.G.), Institut Curie, PSL Research University, 26 rue d'Ulm, Paris 75005, France
| | - Clara Tescher
- From the Departments of Radiology (T.R., C.T., C.M., A.T.), Medical Oncology (P.V.), Diagnostic and Theranostic Medicine - Pathology (J.C.), and Surgical Oncology (N.G.), Institut Curie, PSL Research University, 26 rue d'Ulm, Paris 75005, France
| | - Pauline Vaflard
- From the Departments of Radiology (T.R., C.T., C.M., A.T.), Medical Oncology (P.V.), Diagnostic and Theranostic Medicine - Pathology (J.C.), and Surgical Oncology (N.G.), Institut Curie, PSL Research University, 26 rue d'Ulm, Paris 75005, France
| | - Joanna Cyrta
- From the Departments of Radiology (T.R., C.T., C.M., A.T.), Medical Oncology (P.V.), Diagnostic and Theranostic Medicine - Pathology (J.C.), and Surgical Oncology (N.G.), Institut Curie, PSL Research University, 26 rue d'Ulm, Paris 75005, France
| | - Noémie Girard
- From the Departments of Radiology (T.R., C.T., C.M., A.T.), Medical Oncology (P.V.), Diagnostic and Theranostic Medicine - Pathology (J.C.), and Surgical Oncology (N.G.), Institut Curie, PSL Research University, 26 rue d'Ulm, Paris 75005, France
| | - Caroline Malhaire
- From the Departments of Radiology (T.R., C.T., C.M., A.T.), Medical Oncology (P.V.), Diagnostic and Theranostic Medicine - Pathology (J.C.), and Surgical Oncology (N.G.), Institut Curie, PSL Research University, 26 rue d'Ulm, Paris 75005, France
| | - Anne Tardivon
- From the Departments of Radiology (T.R., C.T., C.M., A.T.), Medical Oncology (P.V.), Diagnostic and Theranostic Medicine - Pathology (J.C.), and Surgical Oncology (N.G.), Institut Curie, PSL Research University, 26 rue d'Ulm, Paris 75005, France
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10
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Lee CS, Moy L. Ultrafast Breast MRI to Predict Pathologic Response after Neoadjuvant Therapy. Radiology 2022; 305:575-577. [PMID: 35880985 DOI: 10.1148/radiol.221511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Cindy S Lee
- From the Department of Radiology, New York University Langone Medical Center, 550 1st Ave, New York, NY 10016
| | - Linda Moy
- From the Department of Radiology, New York University Langone Medical Center, 550 1st Ave, New York, NY 10016
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11
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Delta-Radiomics Based on Dynamic Contrast-Enhanced MRI Predicts Pathologic Complete Response in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy. Cancers (Basel) 2022; 14:cancers14143515. [PMID: 35884576 PMCID: PMC9316501 DOI: 10.3390/cancers14143515] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 07/06/2022] [Accepted: 07/16/2022] [Indexed: 12/20/2022] Open
Abstract
Simple Summary Neoadjuvant chemotherapy (NAC) followed with surgery is the standard strategy in the treatment of locally advanced breast cancer, but the individual efficacy varies. Early and accurate prediction of complete responders determines the NAC regimens and prognosis. Breast MRI has been recommended to monitor NAC response before, during, and after treatment. Radiomics has been heralded as a breakthrough in medicine and regarded to have changed the landscape of biomedical research in oncology. Delta-radiomics characterizing the change in feature values by applying radiomics to multiple time points, is a promising strategy for predicting response after NAC. In our study, the delta-radiomics model built with the change of radiomic features before and after one cycle NAC could effectively predict pathological complete response (pCR) in breast cancer. The model provides strong support for clinical decision-making at the earliest stage and helps patients benefit the most from NAC. Abstract Objective: To investigate the value of delta-radiomics after the first cycle of neoadjuvant chemotherapy (NAC) using dynamic contrast-enhanced (DCE) MRI for early prediction of pathological complete response (pCR) in patients with breast cancer. Methods: From September 2018 to May 2021, a total of 140 consecutive patients (training, n = 98: validation, n = 42), newly diagnosed with breast cancer who received NAC before surgery, were prospectively enrolled. All patients underwent DCE-MRI at pre-NAC (pre-) and after the first cycle (1st-) of NAC. Radiomic features were extracted from the postcontrast early, peak, and delay phases. Delta-radiomics features were computed in each contrast phases. Least absolute shrinkage and selection operator (LASSO) and a logistic regression model were used to select features and build models. The model performance was assessed by receiver operating characteristic (ROC) analysis and compared by DeLong test. Results: The delta-radiomics model based on the early phases of DCE-MRI showed a highest AUC (0.917/0.842 for training/validation cohort) compared with that using the peak and delay phases images. The delta-radiomics model outperformed the pre-radiomics model (AUC = 0.759/0.617, p = 0.011/0.047 for training/validation cohort) in early phase. Based on the optimal model, longitudinal fusion radiomic models achieved an AUC of 0.871/0.869 in training/validation cohort. Clinical-radiomics model generated good calibration and discrimination capacity with AUC 0.934 (95%CI: 0.882, 0.986)/0.864 (95%CI: 0.746, 0.982) for training and validation cohort. Delta-radiomics based on early contrast phases of DCE-MRI combined clinicopathology information could predict pCR after one cycle of NAC in patients with breast cancer.
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Cover KS. Kim et al. report the first ultrafast MR imaging results applicable to breast cancer screening as their study does not suffer from selection bias towards large lesions. Eur J Radiol 2022; 154:110440. [PMID: 35843013 DOI: 10.1016/j.ejrad.2022.110440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/06/2022] [Accepted: 07/09/2022] [Indexed: 11/03/2022]
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Kim ES, Cho N, Kim SY, Lee SH, Chang JM, Kim YS, Ha SM, Moon WK. Added value of ultrafast sequence in abbreviated breast MRI surveillance in women with a personal history of breast cancer: A multireader study. Eur J Radiol 2022; 151:110322. [DOI: 10.1016/j.ejrad.2022.110322] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 03/31/2022] [Accepted: 04/12/2022] [Indexed: 12/15/2022]
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Al Ewaidat H, Ayasrah M. A Concise Review on the Utilization of Abbreviated Protocol Breast MRI over Full Diagnostic Protocol in Breast Cancer Detection. Int J Biomed Imaging 2022; 2022:8705531. [PMID: 35528224 PMCID: PMC9071885 DOI: 10.1155/2022/8705531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 04/12/2022] [Indexed: 11/21/2022] Open
Abstract
Breast MRI possesses high sensitivity for detecting breast cancer among the current clinical modalities and is an indispensable imaging practice. Breast MRI comprises diffusion-weighted imaging, ultrafast, and T2 weighted and T1 weighted CE (contrast-enhanced) imaging that may be utilized for improving the characterization of the lesions. This multimodal evaluation of breast lesions enables outstanding discrimination between the malignant and benign and malignant lesions. The expanding indications of breast MRI confirm the far superiority of MRI in preoperative staging, especially in the estimation of tumour size and identifying tumour foci in the contralateral and ipsilateral breast. Recent studies depicted that experts can meritoriously utilize this tool for improving breast cancer surgery despite their existence of no significant long term outcomes. For managing the, directly and indirectly, associated screening cost, abbreviated protocols are found to be more beneficial. Further, in some of the patients who were treated with neoadjuvant chemotherapy, breast MRI is utilized for documenting response. It is therefore essential to realise that oncological screening must be easily available, cost-effective, and time-consuming. Earlier detection of this short sequence protocol leads to prior and early breast cancer disease in high risky female populations like women with dense breasts, prehistoric evidence, etc. This proper utilization of AP reduces unnecessary mastectomies. Hence, this review focused on the explorative information for strongly suggesting the benefits of AP breast MRI compared to full diagnostic protocol MRI.
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Affiliation(s)
- Haytham Al Ewaidat
- Department of Allied Medical Sciences-Radiologic Technology, Faculty of Applied Medical Sciences, Jordan University of Science and Technology, Jordan
| | - Mohammad Ayasrah
- Jordan University of Science and Technology, Department of Allied Medical Sciences-Radiologic Technology, Faculty of Applied Medical Sciences, Jordan University of Science and Technology, Jordan
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Liu Z, Liang K, Zhang L, Lai C, Li R, Yi L, Li R, Zhang L, Long W. Small lesion classification on abbreviated breast MRI: training can improve diagnostic performance and inter-reader agreement. Eur Radiol 2022; 32:5742-5751. [PMID: 35212772 DOI: 10.1007/s00330-022-08622-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 12/25/2021] [Accepted: 01/29/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVE To determine whether the diagnostic performance and inter-reader agreement for small lesion classification on abbreviated breast MRI (AB-MRI) can be improved by training, and can achieve the level of full diagnostic protocol MRI (FDP-MRI). METHODS This retrospective study enrolled 1165 breast lesions (≤ 2 cm; 409 malignant and 756 benign) from 1165 MRI examinations for reading test. Twelve radiologists were assigned into a trained group and a non-trained group. They interpreted each AB-MRI twice, which was extracted from FDP-MRI. After the first read, the trained group received a structured training for AB-MRI interpretation while the non-trained group did not. FDP-MRIs were interpreted by the trained group after the second read. BI-RADS category for each lesion was compared to the standard of reference (histopathological examination or follow-up) to calculate diagnostic accuracy. Inter-reader agreement was assessed using multirater k analysis. Diagnostic accuracy and inter-reader agreement were compared between the trained and non-trained groups, between the first and second reads, and between AB-MRI and FDP-MRI. RESULTS After training, the diagnostic accuracy of AB-MRI increased from 77.6 to 84.4%, and inter-reader agreement improved from 0.410 to 0.579 (both p < 0.001), which were higher than those of the non-trained group (accuracy, 84.4% vs 78.0%; weighted k, 0.579 vs 0.461; both p < 0.001). The post-training accuracy and inter-reader agreement of AB-MRI were lower than those of FDP-MRI (accuracy, 84.4% vs 92.8%; weighted k, 0.579 vs 0.602; both p < 0.001). CONCLUSIONS Training can improve the diagnostic performance and inter-reader agreement for small lesion classification on AB-MRI; however, it remains inferior to those of FDP-MRI. KEY POINTS • Training can improve the diagnostic performance for small breast lesions on AB-MRI. • Training can reduce inter-observer variation for breast lesion classification on AB-MRI, especially among junior radiologists. • The post-training diagnostic performance and inter-reader agreement of AB-MRI remained inferior to those of FDP-MRI.
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Affiliation(s)
- Zhuangsheng Liu
- Department of Medical Imaging Center, The First Affiliated Hospital, Jinan University, 601 West Huangpu Street, Tianhe District, Guangzhou, 510630, Guangdong, China.,Department of Radiology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Sun Yat-Sen University, Jiangmen, 529000, China
| | - Keming Liang
- Department of Radiology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Sun Yat-Sen University, Jiangmen, 529000, China
| | - Ling Zhang
- Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Chan Lai
- Department of Radiology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Sun Yat-Sen University, Jiangmen, 529000, China
| | - Ruqiong Li
- Department of Radiology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Sun Yat-Sen University, Jiangmen, 529000, China
| | - Lilei Yi
- Department of Radiology, Foshan Hospital of Traditional Chinese Medicine, Foshan, 528000, China
| | - Ronggang Li
- Department of Pathology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Sun Yat-Sen University, Jiangmen, 529000, China
| | - Ling Zhang
- Department of Radiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng East Road, Guangzhou, 510060, China.
| | - Wansheng Long
- Department of Medical Imaging Center, The First Affiliated Hospital, Jinan University, 601 West Huangpu Street, Tianhe District, Guangzhou, 510630, Guangdong, China. .,Department of Radiology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Sun Yat-Sen University, Jiangmen, 529000, China.
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Cover KS. Is It Possible for MRI Screening of Breast Cancer to be Available to Many More Women by Greatly Reducing its False Positive Detections via Ultrafast Time to Enhancement Measurements? J Magn Reson Imaging 2021; 55:1633-1635. [PMID: 34676937 DOI: 10.1002/jmri.27969] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 10/11/2021] [Accepted: 10/14/2021] [Indexed: 12/14/2022] Open
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Implementation of Abbreviated Breast MRI for Screening: AJR Expert Panel Narrative Review. AJR Am J Roentgenol 2021; 218:202-212. [PMID: 34378397 DOI: 10.2214/ajr.21.26349] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Abbreviated breast MRI (AB-MRI) is being rapidly adopted to harness the high sensitivity of screening MRI while addressing issues related to access, cost, and workflow. The successful implementation of an ABI-MRI program requires collaboration across administrative, operational, financial, technical, and clinical providers. Institutions must be thoughtful in defining AB-MRI patient eligibility and providing recommendations for screening intervals, as existing practices are heterogeneous. Similarly, there is no universally accepted AB-MRI protocol, though guiding principles should harmonize abbreviated and full protocols while being mindful of scan duration and table time. The interpretation of AB-MRI will be a new experience for many radiologists and may require a phased rollout as well as a careful audit of performance metrics over time to ensure benchmark metrics are achieved. AB-MRI finances, which are driven by patient self-payment, will require buy-in from hospital administration with the recognition that downstream revenues will be needed to support initial costs. Finally, successful startup of an AB-MRI program requires active engagement with the larger community of patients and referring providers. As AB-MRI becomes more widely accepted and available, best practices and community standards will continue to evolve to ensure high quality patient care.
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Pelissier M, Ambarki K, Salleron J, Henrot P. Maximum slope using ultrafast breast DCE-MRI at 1.5 Tesla: a potential tool for predicting breast lesion aggressiveness. Eur Radiol 2021; 31:9556-9566. [PMID: 34117556 DOI: 10.1007/s00330-021-08089-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 04/09/2021] [Accepted: 05/21/2021] [Indexed: 01/01/2023]
Abstract
OBJECTIVES We evaluated the relationship between the maximum slope (MS) based on ultrafast breast DCE-MRI sequences, and the clinical parameters and routine prognostic factors of breast cancer. METHODS 210 lesions were retrospectively evaluated: 150 malignant (30 each of luminal A invasive carcinoma, luminal B invasive carcinoma, HER2 overexpression (HER2), triple negative (TN), invasive lobular carcinoma (ILC)), and 60 benign. For each lesion, the MS was obtained with an ultrafast sequence and semi-quantitative curves were classified into three types with a conventional DCE sequence. The correlation between MS and age, body mass index (BMI), menopause, and routine prognostic factors were analyzed. RESULTS A MS cut-off at 6.5%/s could discriminate benign from malignant lesions, with sensitivity and specificity of 84% and 90%, respectively, whereas analysis of semi-quantitative curves showed sensitivity and specificity of 89.3% and 55%, respectively. In multivariate analysis, MS values decreased with BMI increasing (p = 0.035), postmenopausal status (p < 0.001), and positive ER status (p < 0.001) and increased with tumor size (p < 0.001). The MS was significantly lower for the pooled luminal A + ILC group than for the pooled luminal B + HER2 + TN group featuring tumors with poorer prognoses (p < 0.001). With a threshold of 11%/s, the sensitivity and specificity to identify invasive carcinoma subtypes with poorer prognoses were 71% and 68%, respectively. CONCLUSION The MS allows better tumor characterization and identifies factors of poor prognosis for breast cancer. KEY POINTS • Maximum slope calculated from ultrafast breast DCE-MRI differentiates benign from malignant breast lesions better than semi-quantitative curves of conventional DCE-MRI. • Maximum slope calculated from ultrafast breast DCE-MRI identifies breast cancers with poor prognoses. • In the case of multiple lesions, the most aggressive may be identified and targeted by measuring the maximum slope.
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Affiliation(s)
- Margaux Pelissier
- Department of Radiology, Institut de Cancérologie de Lorraine, 6 avenue de Bourgogne, 54 519, Vandoeuvre-les-Nancy, France
| | - Khalid Ambarki
- Siemens Healthcare GmbH, Siemens Healthcare SAS, Saint Denis, France
| | - Julia Salleron
- Department of Biostatistics, Institut de Cancérologie de Lorraine, 6 avenue de Bourgogne, 54 519, Vandoeuvre-les-Nancy, France
| | - Philippe Henrot
- Department of Radiology, Institut de Cancérologie de Lorraine, 6 avenue de Bourgogne, 54 519, Vandoeuvre-les-Nancy, France.
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Samreen N, Mercado C, Heacock L, Chacko C, Partridge SC, Chhor C. Screening Breast MRI Primer: Indications, Current Protocols, and Emerging Techniques. JOURNAL OF BREAST IMAGING 2021; 3:387-398. [PMID: 38424773 DOI: 10.1093/jbi/wbaa116] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Indexed: 03/02/2024]
Abstract
Breast dynamic contrast-enhanced MRI (DCE-MRI) is the most sensitive imaging modality for the detection of breast cancer. Screening MRI is currently performed predominantly in patients at high risk for breast cancer, but it could be of benefit in patients at intermediate risk for breast cancer and patients with dense breasts. Decreasing scan time and image interpretation time could increase cost-effectiveness, making screening MRI accessible to a larger group of patients. Abbreviated breast MRI (Ab-MRI) reduces scan time by decreasing the number of sequences obtained, but as multiple delayed contrast enhanced sequences are not obtained, no kinetic information is available. Ultrafast techniques rapidly acquire multiple sequences during the first minute of gadolinium contrast injection and provide information about both lesion morphology and vascular kinetics. Diffusion-weighted imaging is a noncontrast MRI technique with the potential to detect mammographically occult cancers. This review article aims to discuss the current indications of breast MRI as a screening tool, examine the standard breast DCE-MRI technique, and explore alternate screening MRI protocols, including Ab-MRI, ultrafast MRI, and noncontrast diffusion-weighted MRI, which can decrease scan time and interpretation time.
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Affiliation(s)
- Naziya Samreen
- New York University, Department of Radiology, Garden City, NY, USA
| | - Cecilia Mercado
- NYU School of Medicine, Department of Radiology, New York, NY, USA
| | - Laura Heacock
- NYU School of Medicine, Department of Radiology, New York, NY, USA
| | - Celin Chacko
- New York University, Department of Radiology, Garden City, NY, USA
| | | | - Chloe Chhor
- NYU School of Medicine, Department of Radiology, New York, NY, USA
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Ultrafast Dynamic Contrast-Enhanced MRI Using Compressed Sensing: Associations of Early Kinetic Parameters With Prognostic Factors of Breast Cancer. AJR Am J Roentgenol 2021; 217:56-63. [PMID: 33909465 DOI: 10.2214/ajr.20.23457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
OBJECTIVE. The purpose of this study was to investigate whether early kinetic parameters derived from ultrafast dynamic contrast-enhanced MRI (DCE-MRI) using compressed sensing are associated with prognostic factors for breast cancer. MATERIALS AND METHODS. We evaluated 201 consecutive women (mean age, 54.6 years) with breast cancer (168 invasive, 33 ductal carcinoma in situ) who underwent both ultrafast DCE-MRI using compressed sensing (temporal resolution, 4.7 seconds; spatial resolution, 0.8 × 1.1 × 0.9 mm) and surgery between 2018 and 2019. Early kinetic parameters (time to enhancement [TTE] and maximum slope [MS]) were measured in breast lesions by two radiologists using a software program and were correlated with histopathologic prognostic factors. The Mann-Whitney U test and linear regression analysis were used. RESULTS. The median TTE and MS values for breast cancer were 11.9 seconds and 7.7%/s, respectively. The median MS was significantly larger in invasive cancer lesions than in ductal carcinoma in situ lesions (8.4%/s vs 4.7%/s, p < .001). In women with invasive cancer, multivariate linear regression analyses showed that a larger tumor size (> 2 cm) (p = .048) and estrogen receptor-negative status (p < .001) were significantly associated with a shorter TTE. A higher histologic grade (grade 3) (p = .01) was significantly associated with a larger MS. We observed excellent interobserver agreement between two readers in the measurements of TTE and MS (intraclass correlation coefficients, 0.943 and 0.890, respectively). CONCLUSION. Ultrafast MRI-derived early enhancement parameters, such as TTE and MS, are associated with histopathologic prognostic factors in women with breast cancer.
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Radiomic analysis of HTR-DCE MR sequences improves diagnostic performance compared to BI-RADS analysis of breast MR lesions. Eur Radiol 2021; 31:4848-4859. [PMID: 33404696 DOI: 10.1007/s00330-020-07519-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Revised: 09/27/2020] [Accepted: 11/13/2020] [Indexed: 10/22/2022]
Abstract
PURPOSE To assess the diagnostic performance of radiomic analysis using high temporal resolution (HTR)-dynamic contrast enhancement (DCE) MR sequences compared to BI-RADS analysis to distinguish benign from malignant breast lesions. MATERIALS AND METHODS We retrospectively analyzed data from consecutive women who underwent breast MRI including HTR-DCE MR sequencing for abnormal enhancing lesions and who had subsequent pathological analysis at our tertiary center. Semi-quantitative enhancement parameters and textural features were extracted. Temporal change across each phase of textural features in HTR-DCE MR sequences was calculated and called "kinetic textural parameters." Statistical analysis by LASSO logistic regression and cross validation was performed to build a model. The diagnostic performance of the radiomic model was compared to the results of BI-RADS MR score analysis. RESULTS We included 117 women with a mean age of 54 years (28-88). Of the 174 lesions analyzed, 75 were benign and 99 malignant. Seven semi-quantitative enhancement parameters and 57 textural features were extracted. Regression analysis selected 15 significant variables in a radiomic model (called "malignant probability score") which displayed an AUC = 0.876 (sensitivity = 0.98, specificity = 0.52, accuracy = 0.78). The performance of the malignant probability score to distinguish benign from malignant breast lesions (AUC = 0.876, 95%CI 0.825-0.925) was significantly better than that of BI-RADS analysis (AUC = 0.831, 95%CI 0.769-0.892). The radiomic model significantly reduced false positives (42%) with the same number of missed cancers (n = 2). CONCLUSION A radiomic model including kinetic textural features extracted from an HTR-DCE MR sequence improves diagnostic performance over BI-RADS analysis. KEY POINTS • Radiomic analysis using HTR-DCE is of better diagnostic performance (AUC = 0.876) than conventional breast MRI reading with BI-RADS (AUC = 0.831) (p < 0.001). • A radiomic malignant probability score under 19.5% gives a negative predictive value of 100% while a malignant probability score over 81% gives a positive predictive value of 100%. • Kinetic textural features extracted from HTR-DCE-MRI have a major role to play in distinguishing benign from malignant breast lesions.
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Hernández ML, Osorio S, Florez K, Ospino A, Díaz GM. Abbreviated magnetic resonance imaging in breast cancer: A systematic review of literature. Eur J Radiol Open 2020; 8:100307. [PMID: 33364260 PMCID: PMC7750142 DOI: 10.1016/j.ejro.2020.100307] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 12/02/2020] [Accepted: 12/03/2020] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND : magnetic resonance imaging (MRI) has been increasingly used to study breast cancer for screening high-risk cases, pre-operative staging, and problem-solving because of its high sensitivity. However, its cost-effectiveness is still debated. Thus, the concept of abbreviated MRI (ABB-MRI) protocols was proposed as a possible solution for reducing MRI costs. PURPOSE : to investigate the role of the abbreviated MRI protocols in detecting and staging breast cancer. METHODS : a systematic search of the literature was carried out in the bibliographic databases: Scopus, PubMed, Medline, and Science Direct. RESULTS : forty-one articles were included, which described results of the assessment of fifty-three abbreviated protocols for screening, staging, recurrence assessing, and problem-solving or clarification. CONCLUSIONS : the use of ABB-MRI protocols allows reducing the acquisition and reading times, maintaining a high concordance with the final interpretation, in comparison to a complete protocol. However, larger prospective and multicentre trials are necessary to validate the performance in specific clinical environments.
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Affiliation(s)
- María Liliana Hernández
- Grupo de Investigación del Instituto de Alta Tecnología Médica (IATM), Ayudas Diagnósticas Sura, Medellín, Colombia
| | - Santiago Osorio
- Grupo de Investigación del Instituto de Alta Tecnología Médica (IATM), Ayudas Diagnósticas Sura, Medellín, Colombia
- Especialización en Radiología, Universidad CES, Medellín, Colombia
| | - Katherine Florez
- Grupo de Investigación del Instituto de Alta Tecnología Médica (IATM), Ayudas Diagnósticas Sura, Medellín, Colombia
- Especialización en Radiología, Universidad CES, Medellín, Colombia
| | - Alejandra Ospino
- Grupo de Investigación del Instituto de Alta Tecnología Médica (IATM), Ayudas Diagnósticas Sura, Medellín, Colombia
| | - Gloria M. Díaz
- MIRP Lab–Parque i, Instituto Tecnológico Metropolitano (ITM), Medellín, Colombia
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Honda M, Kataoka M, Iima M, Miyake KK, Ohashi A, Kishimoto AO, Ota R, Nickel MD, Toi M, Togashi K. Background parenchymal enhancement and its effect on lesion detectability in ultrafast dynamic contrast-enhanced MRI. Eur J Radiol 2020; 129:108984. [PMID: 32534350 DOI: 10.1016/j.ejrad.2020.108984] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 03/25/2020] [Accepted: 03/30/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE Background parenchymal enhancement (BPE) often affects interpretation of dynamic contrast-enhanced (DCE) MRI. There is limited evidence that reduced BPE is a feature of ultrafast DCE (UF-DCE) MRI. We aimed to evaluate the effect of BPE levels on lesion detectability on UF-DCE MRI in comparison with conventional DCE MRI. METHOD MRIs of 70 patients with histologically proven breast lesions were retrospectively evaluated. The total number of analyzed lesions was 84 (56 malignant and 28 benign). Using 3 T MRI, 20 phases of UF-DCE MRI based on the three-dimensional gradient-echo VIBE sequence combined with a compressed sensing reconstruction were acquired followed by conventional DCE MRI. Three maximum intensity projection (MIP) images were generated from the 12th phase, the 20th phase of UF-DCE MRI and the initial phase of conventional DCE MRI. Two radiologists independently evaluated the degree of BPE and lesion detectability of the three MIP images for each breast with histologically confirmed lesions. The degree of BPE was scored on a four-point scale and lesion detectability (conspicuity and confidence levels) was scored on a three-point scale. Data were analyzed using the Wilcoxon signed-rank test with Bonferroni correction. RESULTS BPE was lower on UF-DCE MRI than on conventional DCE MRI. Lesion detectability was higher on UF-DCE MRI among patients with higher BPE on conventional DCE MRI or premenopausal women. CONCLUSIONS Images with lower BPE can be achieved using UF-DCE MRI and may be advantageous when assessing breast lesions among patients with higher BPE or premenopausal women.
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Affiliation(s)
- Maya Honda
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Masako Kataoka
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto, 606-8507, Japan.
| | - Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto, 606-8507, Japan; Institute for Advancement of Clinical and Translational Science (iACT), Kyoto University Hospital, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto, 606-7507, Japan
| | - Kanae Kawai Miyake
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Akane Ohashi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Ayami Ohno Kishimoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Rie Ota
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Marcel Dominik Nickel
- MR Application Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052, Erlangen, Germany
| | - Masakazu Toi
- Department of Breast Surgery, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Kaori Togashi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto, 606-8507, Japan
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Abstract
OBJECTIVE. Fast breast MRI protocols have the same sensitivity as conventional protocols, but their specificity is variable and can be inadequate. An ultrafast sequence provides early enhancement of lesion characteristics that optimize the characterization of the fast protocol, increasing positive predictive values without increasing time. CONCLUSION. These new abbreviated protocols could constitute a viable screening tool both for women at high risk of breast cancer and for those at intermediate risk with high breast density.
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