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Musall BC, Rauch DE, Mohamed RM, Panthi B, Boge M, Candelaria RP, Chen H, Guirguis MS, Hunt KK, Huo L, Hwang KP, Korkut A, Litton JK, Moseley TW, Pashapoor S, Patel MM, Reed BJ, Scoggins ME, Son JB, Tripathy D, Valero V, Wei P, White JB, Whitman GJ, Xu Z, Yang WT, Yam C, Adrada BE, Ma J. Diffusion Tensor Imaging for Characterizing Changes in Triple-Negative Breast Cancer During Neoadjuvant Systemic Therapy. J Magn Reson Imaging 2024:10.1002/jmri.29267. [PMID: 38294179 PMCID: PMC11289164 DOI: 10.1002/jmri.29267] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 01/18/2024] [Accepted: 01/18/2024] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND Assessment of treatment response in triple-negative breast cancer (TNBC) may guide individualized care for improved patient outcomes. Diffusion tensor imaging (DTI) measures tissue anisotropy and could be useful for characterizing changes in the tumors and adjacent fibroglandular tissue (FGT) of TNBC patients undergoing neoadjuvant systemic treatment (NAST). PURPOSE To evaluate the potential of DTI parameters for prediction of treatment response in TNBC patients undergoing NAST. STUDY TYPE Prospective. POPULATION Eighty-six women (average age: 51 ± 11 years) with biopsy-proven clinical stage I-III TNBC who underwent NAST followed by definitive surgery. 47% of patients (40/86) had pathologic complete response (pCR). FIELD STRENGTH/SEQUENCE 3.0 T/reduced field of view single-shot echo-planar DTI sequence. ASSESSMENT Three MRI scans were acquired longitudinally (pre-treatment, after 2 cycles of NAST, and after 4 cycles of NAST). Eleven histogram features were extracted from DTI parameter maps of tumors, a peritumoral region (PTR), and FGT in the ipsilateral breast. DTI parameters included apparent diffusion coefficients and relative diffusion anisotropies. pCR status was determined at surgery. STATISTICAL TESTS Longitudinal changes of DTI features were tested for discrimination of pCR using Mann-Whitney U test and area under the receiver operating characteristic curve (AUC). A P value <0.05 was considered statistically significant. RESULTS 47% of patients (40/86) had pCR. DTI parameters assessed after 2 and 4 cycles of NAST were significantly different between pCR and non-pCR patients when compared between tumors, PTRs, and FGTs. The median surface/average anisotropy of the PTR, measured after 2 and 4 cycles of NAST, increased in pCR patients and decreased in non-pCR patients (AUC: 0.78; 0.027 ± 0.043 vs. -0.017 ± 0.042 mm2 /s). DATA CONCLUSION Quantitative DTI features from breast tumors and the peritumoral tissue may be useful for predicting the response to NAST in TNBC. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 4.
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Affiliation(s)
- Benjamin C. Musall
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - David E. Rauch
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Rania M.M. Mohamed
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Bikash Panthi
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Medine Boge
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Rosalind P. Candelaria
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Huiqin Chen
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Mary S. Guirguis
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Kelly K. Hunt
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Lei Huo
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Ken-Pin Hwang
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Anil Korkut
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jennifer K. Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Tanya W. Moseley
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Sanaz Pashapoor
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Miral M. Patel
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Brandy J. Reed
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Marion E. Scoggins
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jong Bum Son
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Debu Tripathy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Peng Wei
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jason B. White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Gary J. Whitman
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Zhan Xu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Wei T. Yang
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Clinton Yam
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Beatriz E. Adrada
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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Nissan N, Anaby D, Mahameed G, Bauer E, Moss Massasa EE, Menes T, Agassi R, Brodsky A, Grimm R, Nickel MD, Roccia E, Sklair-Levy M. Ultrafast DCE-MRI for discriminating pregnancy-associated breast cancer lesions from lactation related background parenchymal enhancement. Eur Radiol 2023; 33:8122-8131. [PMID: 37278853 DOI: 10.1007/s00330-023-09805-8] [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: 09/22/2022] [Revised: 03/31/2023] [Accepted: 04/27/2023] [Indexed: 06/07/2023]
Abstract
OBJECTIVE To investigate the utility of ultrafast dynamic-contrast-enhanced (DCE) MRI in visualization and quantitative characterization of pregnancy-associated breast cancer (PABC) and its differentiation from background-parenchymal-enhancement (BPE) among lactating patients. MATERIALS AND METHODS Twenty-nine lactating participants, including 10 PABC patients and 19 healthy controls, were scanned on 3-T MRI using a conventional DCE protocol interleaved with a golden-angle radial sparse parallel (GRASP) ultrafast sequence for the initial phase. The timing of the visualization of PABC lesions was compared to lactational BPE. Contrast-noise ratio (CNR) was compared between the ultrafast and conventional DCE sequences. The differences in each group's ultrafast-derived kinetic parameters including maximal slope (MS), time to enhancement (TTE), and area under the curve (AUC) were statistically examined using the Mann-Whitney test and receiver operator characteristic (ROC) curve analysis. RESULTS On ultrafast MRI, breast cancer lesions enhanced earlier than BPE (p < 0.0001), enabling breast cancer visualization freed from lactation BPE. A higher CNR was found for ultrafast acquisitions vs. conventional DCE (p < 0.05). Significant differences in AUC, MS, and TTE values were found between the tumor and BPE (p < 0.05), with ROC-derived AUC of 0.86 ± 0.06, 0.82 ± 0.07, and 0.68 ± 0.08, respectively. The BPE grades of the lactating PABC patients were reduced as compared with the healthy lactating controls (p < 0.005). CONCLUSION Ultrafast DCE MRI allows BPE-free visualization of lesions, improved tumor conspicuity, and kinetic quantification of breast cancer during lactation. Implementation of this method may assist in the utilization of breast MRI for lactating patients. CLINICAL RELEVANCE The ultrafast sequence appears to be superior to conventional DCE MRI in the challenging evaluation of the lactating breast. Thus, supporting its possible utilization in the setting of high-risk screening during lactation and the diagnostic workup of PABC. KEY POINTS • Differences in the enhancement slope of cancer relative to BPE allowed the optimal visualization of PABC lesions on mid-acquisitions of ultrafast DCE, in which the tumor enhanced prior to the background parenchyma. • The conspicuity of PABC lesions on top of the lactation-related BPE was increased using an ultrafast sequence as compared with conventional DCE MRI. • Ultrafast-derived maps provided further characterization and parametric contrast between PABC lesions and lactation-related BPE.
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Affiliation(s)
- Noam Nissan
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 St. Tel Hashomer, 5265601, Ramat Gan, Israel.
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
| | - Debbie Anaby
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 St. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Gazal Mahameed
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 St. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Ethan Bauer
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Efi Efraim Moss Massasa
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 St. Tel Hashomer, 5265601, Ramat Gan, Israel
| | - Tehillah Menes
- Department of General Surgery, Sheba Medical Center, Ramat Gan, Israel
| | - Ravit Agassi
- Department of General Surgery, Soroka Medical Center, Beersheba, Israel
| | - Asia Brodsky
- Department of General Surgery, Bnei Zion Medical Center, Haifa, Israel
| | - Robert Grimm
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | | | - Elisa Roccia
- MR Scientific Marketing, Siemens Healthcare GmbH, Erlangen, Germany
| | - Miri Sklair-Levy
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 St. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
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Tsarouchi MI, Hoxhaj A, Mann RM. New Approaches and Recommendations for Risk-Adapted Breast Cancer Screening. J Magn Reson Imaging 2023; 58:987-1010. [PMID: 37040474 DOI: 10.1002/jmri.28731] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 03/23/2023] [Accepted: 03/24/2023] [Indexed: 04/13/2023] Open
Abstract
Population-based breast cancer screening using mammography as the gold standard imaging modality has been in clinical practice for over 40 years. However, the limitations of mammography in terms of sensitivity and high false-positive rates, particularly in high-risk women, challenge the indiscriminate nature of population-based screening. Additionally, in light of expanding research on new breast cancer risk factors, there is a growing consensus that breast cancer screening should move toward a risk-adapted approach. Recent advancements in breast imaging technology, including contrast material-enhanced mammography (CEM), ultrasound (US) (automated-breast US, Doppler, elastography US), and especially magnetic resonance imaging (MRI) (abbreviated, ultrafast, and contrast-agent free), may provide new opportunities for risk-adapted personalized screening strategies. Moreover, the integration of artificial intelligence and radiomics techniques has the potential to enhance the performance of risk-adapted screening. This review article summarizes the current evidence and challenges in breast cancer screening and highlights potential future perspectives for various imaging techniques in a risk-adapted breast cancer screening approach. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 5.
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Affiliation(s)
- Marialena I Tsarouchi
- Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Alma Hoxhaj
- Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Ritse M Mann
- Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
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Ecanow JS, Ecanow DB, Hack B, Leloudas N, Prasad PV. Feasibility of Diffusion Tensor Imaging for Decreasing Biopsy Rates in Breast Imaging: Interim Analysis of a Prospective Study. Diagnostics (Basel) 2023; 13:2226. [PMID: 37443620 DOI: 10.3390/diagnostics13132226] [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: 05/22/2023] [Revised: 06/28/2023] [Accepted: 06/28/2023] [Indexed: 07/15/2023] Open
Abstract
Because of the limited specificity of diagnostic imaging, many breast lesions referred for biopsy turn out to be benign. The objective of this study was to evaluate whether diffusion tensor MRI (DTI) parametric maps can be used to safely avoid biopsy of breast lesions. Individuals referred for breast biopsy based on mammogram (MG), ultrasound (US), and/or contrast enhanced (CE)-MRI were recruited. Scans consisting of T2-weighted and DTI sequences were performed. Multiple DTI-derived parametric color maps were evaluated semi-quantitatively to characterize lesions as "definitely benign," "not definitely benign," or "suspicious." All patients subsequently underwent biopsy. In this moderately-sized prospective study, 21 out of 47 pathologically proven benign lesions were characterized by both readers as "definitely benign," which would have precluded the need for biopsy. Biopsy was recommended for 11 out of 13 cancers that were characterized as "suspicious." In the remaining two cancers and 26 of 47 benign lesions, the scans were characterized as "not definitely benign" and hence required biopsy. The main causes for "not definitely benign" scans were small lesion sizes and noise. The results suggest that in appropriately selected patients, DTI may be used to safely reduce the number of unnecessary breast biopsies.
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Affiliation(s)
- Jacob S Ecanow
- Department of Radiology, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - David B Ecanow
- Department of Radiology, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Bradley Hack
- Department of Radiology, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Nondas Leloudas
- Department of Radiology, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Pottumarthi V Prasad
- Department of Radiology, NorthShore University HealthSystem, Evanston, IL 60201, USA
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Nissan N, Massasa EEM, Bauer E, Halshtok-Neiman O, Shalmon A, Gotlieb M, Faermann R, Samoocha D, Yagil Y, Ziv-Baran T, Anaby D, Sklair-Levy M. MRI can accurately diagnose breast cancer during lactation. Eur Radiol 2023; 33:2935-2944. [PMID: 36348090 DOI: 10.1007/s00330-022-09234-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 08/27/2022] [Accepted: 10/10/2022] [Indexed: 11/09/2022]
Abstract
OBJECTIVE To test the diagnostic performance of breast dynamic contrast-enhanced (DCE) MRI during lactation. MATERIALS AND METHODS Datasets of 198 lactating patients, including 66 pregnancy-associated breast cancer (PABC) patients and 132 controls, who were scanned by DCE on 1.5-T MRI, were retrospectively evaluated. Six blinded, expert radiologists independently read a single DCE maximal intensity projection (MIP) image for each case and were asked to determine whether malignancy was suspected and the background-parenchymal-enhancement (BPE) grade. Likewise, computer-aided diagnosis CAD MIP images were independently read by the readers. Contrast-to-noise ratio (CNR) analysis was measured and compared among four consecutive acquisitions of DCE subtraction images. RESULTS For MIP-DCE images, the readers achieved the following means: sensitivity 93.3%, specificity 80.3%, positive-predictive-value 70.4, negative-predictive-value 96.2, and diagnostic accuracy of 84.6%, with a substantial inter-rater agreement (Kappa = 0.673, p value < 0.001). Most false-positive interpretations were attributed to either the MIP presentation, an underlying benign lesion, or an asymmetric appearance due to prior treatments. CAD's derived diagnostic accuracy was similar (p = 0.41). BPE grades were significantly increased in the healthy controls compared to the PABC cohort (p < 0.001). CNR significantly decreased by 11-13% in each of the four post-contrast images (p < 0.001). CONCLUSION Breast DCE MRI maintains its high efficiency among the lactating population, probably due to a vascular-steal phenomenon, which causes a significant reduction of BPE in cancer cases. Upon validation by prospective, multicenter trials, this study could open up the opportunity for breast MRI to be indicated in the screening and diagnosis of lactating patients, with the aim of facilitating an earlier diagnosis of PABC. KEY POINTS • A single DCE MIP image was sufficient to reach a mean sensitivity of 93.3% and NPV of 96.2%, to stress the high efficiency of breast MRI during lactation. • Reduction in BPE among PABC patients compared to the lactating controls suggests that several factors, including a possible vascular steal phenomenon, may affect cancer patients. • Reduction in CNR along four consecutive post-contrast acquisitions highlights the differences in breast carcinoma and BPE kinetics and explains the sufficient conspicuity on the first subtracted image.
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Affiliation(s)
- Noam Nissan
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel.
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
| | - Efi Efraim Moss Massasa
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
| | - Ethan Bauer
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Osnat Halshtok-Neiman
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Anat Shalmon
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Michael Gotlieb
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Renata Faermann
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - David Samoocha
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Yael Yagil
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Tomer Ziv-Baran
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Debbie Anaby
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Miri Sklair-Levy
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
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Karam R, Elmokadem AH, El-Rakhawy MM, Soliman N, Elnahas W, Abdel-Khalek AM. Clinical utility of abbreviated breast MRI based on diffusion tensor imaging in patients underwent breast conservative therapy. LA RADIOLOGIA MEDICA 2023; 128:289-298. [PMID: 36763315 DOI: 10.1007/s11547-023-01600-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 01/24/2023] [Indexed: 02/11/2023]
Abstract
PURPOSE To evaluate the added value of the diffusion tensor imaging (DTI) parameters to abbreviated breast MRI protocol in differentiating recurrent breast cancer from post-operative changes in cases of breast conservative surgery (BCS). METHODS This prospective study was approved by our institutional review board. Written informed consent was obtained in all patients. 47 female patients (mean age, 49 years; range, 32-66 years) that previously underwent breast conservative surgery with a palpable mass were included in this study (62 breast lesions). Two abbreviated MRI protocols were compared using 1.5 Tesla MRI, AB-MRI 1 (axial T1, T2, pre-contrast T1, 1st post-contrast and subtracted images) and AB-MRI 2 (same sequences plus adding DTI). In both protocols, the wash-in rate was calculated. Histopathology was used as the standard of reference. Appropriate statistical tests were used to assess sensitivity, specificity, and diagnostic accuracy for each protocol. RESULTS The mean total acquisition time was of 6 min for AB-MRI 1 and 10 min for AB-MRI 2 protocols while the mean interpretation time was of 57.5 and 75 s, respectively. Among analyzed DTI parameters, MD (mean diffusivity) showed the highest sensitivity (96.43%) and specificity (91.18%) (P value = < 0.001). FA (fractional anisotropy), AD (axial diffusivity) and RD (radial diffusivity) showed sensitivity = (78.57%, 82.14% and 85.71%), specificity = (88.24, 85.29% and 79.41%), respectively, P value (< 0.001). CONCLUSION DTI may be included in abbreviated MRI protocols without a significant increase in acquisition time and with the advantage of increasing specificity and clinical utility in the characterization of post-conservative breast lesions.
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Affiliation(s)
- Rasha Karam
- Department of Radiology, Mansoura University, Elgomhoria St. 35516, Mansoura, Egypt
| | - Ali H Elmokadem
- Department of Radiology, Mansoura University, Elgomhoria St. 35516, Mansoura, Egypt.
| | | | - Nermin Soliman
- Department of Radiology, Mansoura University, Elgomhoria St. 35516, Mansoura, Egypt
| | - Waleed Elnahas
- Department of Surgical Oncology, Oncology Center, Mansoura University, Mansoura, Egypt
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Iima M, Le Bihan D. The road to breast cancer screening with diffusion MRI. Front Oncol 2023; 13:993540. [PMID: 36895474 PMCID: PMC9989267 DOI: 10.3389/fonc.2023.993540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 01/10/2023] [Indexed: 02/23/2023] Open
Abstract
Breast cancer is the leading cause of cancer in women with a huge medical, social and economic impact. Mammography (MMG) has been the gold standard method until now because it is relatively inexpensive and widely available. However, MMG suffers from certain limitations, such as exposure to X-rays and difficulty of interpretation in dense breasts. Among other imaging methods, MRI has clearly the highest sensitivity and specificity, and breast MRI is the gold standard for the investigation and management of suspicious lesions revealed by MMG. Despite this performance, MRI, which does not rely on X-rays, is not used for screening except for a well-defined category of women at risk, because of its high cost and limited availability. In addition, the standard approach to breast MRI relies on Dynamic Contrast Enhanced (DCE) MRI with the injection of Gadolinium based contrast agents (GBCA), which have their own contraindications and can lead to deposit of gadolinium in tissues, including the brain, when examinations are repeated. On the other hand, diffusion MRI of breast, which provides information on tissue microstructure and tumor perfusion without the use of contrast agents, has been shown to offer higher specificity than DCE MRI with similar sensitivity, superior to MMG. Diffusion MRI thus appears to be a promising alternative approach to breast cancer screening, with the primary goal of eliminating with a very high probability the existence of a life-threatening lesion. To achieve this goal, it is first necessary to standardize the protocols for acquisition and analysis of diffusion MRI data, which have been found to vary largely in the literature. Second, the accessibility and cost-effectiveness of MRI examinations must be significantly improved, which may become possible with the development of dedicated low-field MRI units for breast cancer screening. In this article, we will first review the principles and current status of diffusion MRI, comparing its clinical performance with MMG and DCE MRI. We will then look at how breast diffusion MRI could be implemented and standardized to optimize accuracy of results. Finally, we will discuss how a dedicated, low-cost prototype of breast MRI system could be implemented and introduced to the healthcare market.
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Affiliation(s)
- Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.,Department of Clinical Innovative Medicine, Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, Kyoto, Japan
| | - Denis Le Bihan
- NeuroSpin, Joliot Institute, Department of Fundamental Research, Commissariat á l'Energie Atomique (CEA)-Saclay, Gif-sur-Yvette, France
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Mendez AM, Fang LK, Meriwether CH, Batasin SJ, Loubrie S, Rodríguez-Soto AE, Rakow-Penner RA. Diffusion Breast MRI: Current Standard and Emerging Techniques. Front Oncol 2022; 12:844790. [PMID: 35880168 PMCID: PMC9307963 DOI: 10.3389/fonc.2022.844790] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 05/11/2022] [Indexed: 11/13/2022] Open
Abstract
The role of diffusion weighted imaging (DWI) as a biomarker has been the subject of active investigation in the field of breast radiology. By quantifying the random motion of water within a voxel of tissue, DWI provides indirect metrics that reveal cellularity and architectural features. Studies show that data obtained from DWI may provide information related to the characterization, prognosis, and treatment response of breast cancer. The incorporation of DWI in breast imaging demonstrates its potential to serve as a non-invasive tool to help guide diagnosis and treatment. In this review, current technical literature of diffusion-weighted breast imaging will be discussed, in addition to clinical applications, advanced techniques, and emerging use in the field of radiomics.
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Affiliation(s)
- Ashley M. Mendez
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Lauren K. Fang
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Claire H. Meriwether
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Summer J. Batasin
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Stéphane Loubrie
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Ana E. Rodríguez-Soto
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Rebecca A. Rakow-Penner
- Department of Radiology, University of California San Diego, La Jolla, CA, United States,Department of Bioengineering, University of California San Diego, La Jolla, CA, United States,*Correspondence: Rebecca A. Rakow-Penner,
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Leng X, Japaer R, Zhang H, Yeerlan M, Ma F, Ding J. Relationship of shear wave elastography anisotropy with tumor stem cells and epithelial-mesenchymal transition in breast cancer. BMC Med Imaging 2021; 21:171. [PMID: 34789199 PMCID: PMC8600915 DOI: 10.1186/s12880-021-00707-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 11/03/2021] [Indexed: 12/15/2022] Open
Abstract
Background This study is to examine the feasibility of shear wave elastography (SWE) anisotropy in assessing the prognosis of breast cancer. Methods We enrolled 119 breast cancer patients from January 2017 to October 2019. SWE was performed before operation. Emax (maximum elasticity value), Emean (average elasticity value), Esd (standard deviation of the lesion elasticity value), Eratio (elasticity value of adipose tissue), anisotropy coefficient and difference were recorded. After operation, we collected clinical pathological data, and performed immunohistochemistry and real-time PCR tests on CD44, CD24, E-cadherin, β-catenin, vimentin and N-cadherin. Finally, we analyzed the correlation among parameters of SWE, anisotropy and clinicopathology, and markers of CSCs (cancer stem cells) and EMT (epithelial-mesenchymal transition). Results Emax, Emean and Esd of the cross section were higher than those of the longitudinal section. Breast cancer with a higher elastic modulus was often accompanied by a hyperechoic halo, which was manifested as mixed echo and post-echo attenuation, and was accompanied by a higher BI-RADS (breast imaging reporting and data system) classification. When breast cancer had hyperechoic halo and weakened posterior echo, SWE of the lesion showed more obvious anisotropy. In addition, larger diameter of the longitudinal section indicated higher stiffness of the cross section. Correlation analysis showed that E-cadherin was negatively correlated with SWE in longitudinal section. CD44, N-cadherin, β-catenin were positively correlated with SWE in longitudinal and cross sections. Vimentin and CD24 had no correlation with SWE parameters. Conclusion SWE of breast cancer is anisotropic. The cross-sectional SWE is better than the longitudinal SWE, Emax is better than Emean, the anisotropy of SWE is better than SWE, and the anisotropy factor is better than the anisotropy difference.
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Affiliation(s)
- Xiaoling Leng
- Department of Ultrasound, Affiliated Tumor Hospital of Xinjiang Medical University, No. 789 Suzhou East Road, Xinshi District, Urumqi, 830011, People's Republic of China
| | - Rexida Japaer
- Department of Ultrasound, Affiliated Tumor Hospital of Xinjiang Medical University, No. 789 Suzhou East Road, Xinshi District, Urumqi, 830011, People's Republic of China
| | - Haijian Zhang
- Department of Ultrasound, Affiliated Tumor Hospital of Xinjiang Medical University, No. 789 Suzhou East Road, Xinshi District, Urumqi, 830011, People's Republic of China
| | - Mila Yeerlan
- Department of Ultrasound, Affiliated Tumor Hospital of Xinjiang Medical University, No. 789 Suzhou East Road, Xinshi District, Urumqi, 830011, People's Republic of China
| | - Fucheng Ma
- Department of Ultrasound, Affiliated Tumor Hospital of Xinjiang Medical University, No. 789 Suzhou East Road, Xinshi District, Urumqi, 830011, People's Republic of China.
| | - Jianbing Ding
- Department of Ultrasound, Affiliated Tumor Hospital of Xinjiang Medical University, No. 789 Suzhou East Road, Xinshi District, Urumqi, 830011, People's Republic of China. .,School of Basic Medicine, Xinjiang Medical University, No. 567 Shangde North Road, Urumqi, 830017, Xinjiang, People's Republic of China.
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10
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Otikovs M, Nissan N, Furman-Haran E, Anaby D, Allweis TM, Agassi R, Sklair-Levy M, Frydman L. Diffusivity in breast malignancies analyzed for b > 1000 s/mm 2 at 1 mm in-plane resolutions: Insight from Gaussian and non-Gaussian behaviors. J Magn Reson Imaging 2020; 53:1913-1925. [PMID: 33368734 DOI: 10.1002/jmri.27489] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 12/10/2020] [Accepted: 12/10/2020] [Indexed: 12/20/2022] Open
Abstract
Diffusion-weighted imaging (DWI) can improve breast cancer characterizations, but often suffers from low image quality -particularly at informative b > 1000 s/mm2 values. The aim of this study was to evaluate multishot approaches characterizing Gaussian and non-Gaussian diffusivities in breast cancer. This was a prospective study, in which 15 subjects, including 13 patients with biopsy-confirmed breast cancers, were enrolled. DWI was acquired at 3 T using echo planar imaging (EPI) with and without zoomed excitations, readout-segmented EPI (RESOLVE), and spatiotemporal encoding (SPEN); dynamic contrast-enhanced (DCE) data were collected using three-dimensional gradient-echo T1 weighting; anatomies were evaluated with T2 -weighted two-dimensional turbo spin-echo. Congruence between malignancies delineated by DCE was assessed against high-resolution DWI scans with b-values in the 0-1800 s/mm2 range, as well as against apparent diffusion coefficient (ADC) and kurtosis maps. Data were evaluated by independent magnetic resonance scientists with 3-20 years of experience, and radiologists with 6 and 20 years of experience in breast MRI. Malignancies were assessed from ADC and kurtosis maps, using paired t tests after confirming that these values had a Gaussian distribution. Agreements between DWI and DCE datasets were also evaluated using Sorensen-Dice similarity coefficients. Cancerous and normal tissues were clearly separable by ADCs: by SPEN their average values were (1.03 ± 0.17) × 10-3 and (1.69 ± 0.19) × 10-3 mm2 /s (p < 0.0001); by RESOLVE these values were (1.16 ± 0.16) × 10-3 and (1.52 ± 0.14) × 10-3 (p = 0.00026). Kurtosis also distinguished lesions (K = 0.64 ± 0.15) from normal tissues (K = 0.45 ± 0.05), but only when measured by SPEN (p = 0.0008). The best statistical agreement with DCE-highlighted regions arose for SPEN-based DWIs recorded with b = 1800 s/mm2 (Sorensen-Dice coefficient = 0.67); DWI data recorded with b = 850 and 1200 s/mm2 , led to lower coefficients. Both ADC and kurtosis maps highlighted the breast malignancies, with ADCs providing a more significant separation. The most promising alternative for contrast-free delineations of the cancerous lesions arose from b = 1800 s/mm2 DWI. LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 3.
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Affiliation(s)
- Martins Otikovs
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel
| | - Noam Nissan
- Department of Radiology, Sheba-Medical-Center, Ramat-Gan, Israel
| | - Edna Furman-Haran
- Life Sciences Core Facilities, Weizmann Institute of Science, Rehovot, Israel.,Azrieli National Center for Brain Imaging, Weizmann Institute of Science, Rehovot, Israel
| | - Debbie Anaby
- Department of Radiology, Sheba-Medical-Center, Ramat-Gan, Israel
| | - Tanir M Allweis
- Department of Surgery, Kaplan Medical Center, Rehovot, Israel
| | - Ravit Agassi
- Department of Surgery, Ben Gurion University Hospital, Beer Sheba, Israel
| | - Miri Sklair-Levy
- Department of Radiology, Sheba-Medical-Center, Ramat-Gan, Israel.,Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Lucio Frydman
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel.,Azrieli National Center for Brain Imaging, Weizmann Institute of Science, Rehovot, Israel
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11
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Fusco R, Granata V, Pariante P, Cerciello V, Siani C, Di Bonito M, Valentino M, Sansone M, Botti G, Petrillo A. Blood oxygenation level dependent magnetic resonance imaging and diffusion weighted MRI imaging for benign and malignant breast cancer discrimination. Magn Reson Imaging 2020; 75:51-59. [PMID: 33080334 DOI: 10.1016/j.mri.2020.10.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 10/14/2020] [Accepted: 10/15/2020] [Indexed: 12/19/2022]
Abstract
PURPOSE The purpose of this study is to assess Blood oxygenation level dependent Magnetic Resonance Imaging (BOLD-MRI) and Diffusion Weighted Magnetic Resonance Imaging (DW-MRI) in the differentiation of benign and malignant breast lesions. METHODS Fifty-nine breast lesions (26 benign and 33 malignant lesions) pathologically proven in 59 patients were included in this retrospective study. As BOLD parameters were estimated basal signal S0 and the relaxation rate R2*, diffusion and perfusion parameters were derived by DWI (pseudo-diffusion coefficient (Dp), perfusion fraction (fp) and tissue diffusivity (Dt)). Wilcoxon-Mann-Whitney U test and Receiver operating characteristic (ROC) analyses were calculated and area under ROC curve (AUC) was obtained. Moreover, pattern recognition approaches (linear discrimination analysis (LDA), support vector machine, k-nearest neighbours, decision tree) with least absolute shrinkage and selection operator (LASSO) method and leave one out cross validation approach were considered. RESULTS A significant discrimination was obtained by the standard deviation value of S0, as BOLD parameter, that reached an AUC of 0.76 with a sensitivity of 65%, a specificity of 85% and an accuracy of 76%. No significant discrimination was obtained considering diffusion and perfusion parameters. Considering LASSO results, the features to use as predictors were all extracted parameters except that the mean value of R2* and the best result was obtained by a LDA that obtained an AUC = 0.83, with a sensitivity of 88%, a specificity of 77% and an accuracy of 83%. CONCLUSIONS Good performance to discriminate benign and malignant lesions could be obtained using BOLD and DWI derived parameters with a LDA classification approach. However, these findings should be proven on larger and several dataset with different MR scanners.
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Affiliation(s)
- Roberta Fusco
- Radiology Division, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy
| | - Vincenza Granata
- Radiology Division, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy.
| | - Paolo Pariante
- Radiology Division, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy
| | - Vincenzo Cerciello
- Health Physics Unit, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy
| | - Claudio Siani
- Senology Surgical Division, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy
| | - Maurizio Di Bonito
- Pathology Division, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy
| | - Marika Valentino
- Department, Electrical Engineering and Information Technologies, UNIVERSITA' DEGLI STUDI DI NAPOLI FEDERICO II, Naples, Italy
| | - Mario Sansone
- Department, Electrical Engineering and Information Technologies, UNIVERSITA' DEGLI STUDI DI NAPOLI FEDERICO II, Naples, Italy
| | - Gerardo Botti
- Scientific Director, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy
| | - Antonella Petrillo
- Radiology Division, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy
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12
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El Ameen NF, Abdel Gawad EA, Abdel Ghany HS. Diffusion-weighted imaging versus dynamic contrast-enhanced MRI: a new horizon for characterisation of suspicious breast lesions. Clin Radiol 2020; 76:80.e1-80.e8. [PMID: 33077159 DOI: 10.1016/j.crad.2020.08.031] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Accepted: 08/21/2020] [Indexed: 11/19/2022]
Abstract
AIM To investigate the value of new diffusion-weighted imaging applications in the characterisation of suspicious breast lesions with emphasis on diffusion tensor imaging (DTI) and fibre tractography (FT). MATERIALS AND METHODS The present prospective study included 40 female patients with suspicious breast lesions according to sono-mammography American College of Radiologists' classification. All patients underwent conventional magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), DTI, and FT after meeting the inclusion criteria. Dynamic contrast-enhanced MRI was performed as the reference standard for radiological evaluation. The study was conducted between August 2018 and January 2019. The final diagnosis was confirmed histopathologically. RESULTS Malignant lesions were diagnosed in 32/40 (80%) patients and 8/40 (20%) patients had benign lesions. Apparent diffusion coefficient (ADC) values of malignant lesions were statistically lower than that of benign lesions (p<0.001) using a cut-off value of 0.99±0.07×10-3 mm2/s. Fractional anisotropy (FA) values were lower in malignant lesions than in benign lesions with a cut-off value for malignancy of 0.19±0.05 and were statistically significant (p<0.005). The sensitivity, specificity, and accuracy of combined DTI and FT were similar to DCE MRI (p<0.001). CONCLUSION DTI and FT are new applications of DWI. They show promising results for the evaluation of suspicious breast masses and can distinguish between benign and malignant breast lesions with statistical significance approaching contrast-enhanced MRI, which is considered the imaging reference standard for characterising breast lesions.
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Affiliation(s)
- N F El Ameen
- Department of Radiology, Faculty of Medicine, Minia University, Minia, Egypt.
| | - E A Abdel Gawad
- Department of Radiology, Faculty of Medicine, Minia University, Minia, Egypt
| | - H S Abdel Ghany
- Department of Radiology, Faculty of Medicine, Minia University, Minia, Egypt
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13
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Effect of IV Administration of a Gadolinium-Based Contrast Agent on Breast Diffusion-Tensor Imaging. AJR Am J Roentgenol 2020; 215:1030-1036. [PMID: 32755227 DOI: 10.2214/ajr.19.22085] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [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 quantify changes in diffusion-tensor imaging (DTI) parameters before and after IV administration of a gadolinium-based contrast agent (GBCA) and explore the influence of those parameters on breast cancer diagnosis. SUBJECTS AND METHODS. A prospective cohort of 26 women with BI-RADS categories 0, 4, 5, or 6 underwent 3-T breast MRI with sequential DTI before GBCA administration and immediately after. Quantitative image analysis using dedicated DTI software yielded parametric DTI maps of each directional diffusion coefficient (DDC), mean diffusivity, and maximal anisotropy of the lesions and normal tissue. The color maps were evaluated and the lesion DTI parameters were compared before and after GBCA administration using appropriate statistical tests. RESULTS. Of the cohort, 58% had cancer (13 infiltrating ductal carcinoma, two ductal carcinoma in situ) and 42% had benign or normal results. All breast cancers were visually detected in the DDC λ1 maps before and after GBCA administration. Mean cancer size derived from λ1 maps before GBCA administration was 15.3 mm (range, 3.3-72.3 mm), and was not statistically significantly different from the size derived after GBCA administration of 17.3 mm (range, 3.9-71.0 mm). After GBCA administration, the cancers exhibited statistically significantly lower DDCs, mean diffusivity, and b0 intensity (p < 0.05), and no change in maximal anisotropy compared with before GBCA administration, whereas these parameters in normal and benign lesions did not change significantly after GBCA administration. The mean AUC values before and after GBCA administration, ranging from 0.735 to 0.985 and from 0.867 to 0.990, respectively, were not statistically significantly different for all parameters aside from λ3. CONCLUSION. Diagnostic accuracy using DTI was equivalent before and after GBCA administration, despite a change in the values of the DTI parameters. However, the limitations in standardization of contrast enhancement implies that unenhanced diffusion measurements should be preferred.
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14
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Chhetri A, Li X, Rispoli JV. Current and Emerging Magnetic Resonance-Based Techniques for Breast Cancer. Front Med (Lausanne) 2020; 7:175. [PMID: 32478083 PMCID: PMC7235971 DOI: 10.3389/fmed.2020.00175] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 04/15/2020] [Indexed: 01/10/2023] Open
Abstract
Breast cancer is the most commonly diagnosed cancer among women worldwide, and early detection remains a principal factor for improved patient outcomes and reduced mortality. Clinically, magnetic resonance imaging (MRI) techniques are routinely used in determining benign and malignant tumor phenotypes and for monitoring treatment outcomes. Static MRI techniques enable superior structural contrast between adipose and fibroglandular tissues, while dynamic MRI techniques can elucidate functional characteristics of malignant tumors. The preferred clinical procedure-dynamic contrast-enhanced MRI-illuminates the hypervascularity of breast tumors through a gadolinium-based contrast agent; however, accumulation of the potentially toxic contrast agent remains a major limitation of the technique, propelling MRI research toward finding an alternative, noninvasive method. Three such techniques are magnetic resonance spectroscopy, chemical exchange saturation transfer, and non-contrast diffusion weighted imaging. These methods shed light on underlying chemical composition, provide snapshots of tissue metabolism, and more pronouncedly characterize microstructural heterogeneity. This review article outlines the present state of clinical MRI for breast cancer and examines several research techniques that demonstrate capacity for clinical translation. Ultimately, multi-parametric MRI-incorporating one or more of these emerging methods-presently holds the best potential to afford improved specificity and deliver excellent accuracy to clinics for the prediction, detection, and monitoring of breast cancer.
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Affiliation(s)
- Apekshya Chhetri
- Magnetic Resonance Biomedical Engineering Laboratory, Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States
- Basic Medical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, IN, United States
| | - Xin Li
- Magnetic Resonance Biomedical Engineering Laboratory, Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States
| | - Joseph V. Rispoli
- Magnetic Resonance Biomedical Engineering Laboratory, Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States
- Center for Cancer Research, Purdue University, West Lafayette, IN, United States
- School of Electrical & Computer Engineering, Purdue University, West Lafayette, IN, United States
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15
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Amornsiripanitch N, Bickelhaupt S, Shin HJ, Dang M, Rahbar H, Pinker K, Partridge SC. Diffusion-weighted MRI for Unenhanced Breast Cancer Screening. Radiology 2019; 293:504-520. [PMID: 31592734 PMCID: PMC6884069 DOI: 10.1148/radiol.2019182789] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Revised: 06/18/2019] [Accepted: 07/10/2019] [Indexed: 01/12/2023]
Abstract
Diffusion-weighted (DW) MRI is a rapid technique that measures the mobility of water molecules within tissue, reflecting the cellular microenvironment. At DW MRI, breast cancers typically exhibit reduced diffusivity and appear hyperintense to surrounding tissues. On the basis of this characteristic, DW MRI may offer an unenhanced method to detect breast cancer without the costs and safety concerns associated with dynamic contrast material-enhanced MRI, the current reference standard in the setting of high-risk screening. This application of DW MRI has not been widely explored but is particularly timely given the growing health concerns related to the long-term use of gadolinium-based contrast material. Moreover, increasing breast density notification legislation across the United States is raising awareness of the limitations of mammography in women with dense breasts, emphasizing the need for additional cost-effective supplemental screening examinations. Preliminary studies suggest unenhanced MRI with DW MRI may provide higher sensitivity than screening mammography for the detection of breast malignancies. Larger prospective multicenter trials are needed to validate single-center findings and assess the performance of DW MRI for generalized breast cancer screening. Standardization of DW MRI acquisition and interpretation is essential to ensure reliable sensitivity and specificity, and an optimal approach for screening using readily available techniques is proposed here.
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Affiliation(s)
- Nita Amornsiripanitch
- From the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology–Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.)
| | - Sebastian Bickelhaupt
- From the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology–Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.)
| | - Hee Jung Shin
- From the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology–Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.)
| | - Madeline Dang
- From the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology–Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.)
| | - Habib Rahbar
- From the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology–Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.)
| | - Katja Pinker
- From the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology–Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.)
| | - Savannah C. Partridge
- From the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology–Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.)
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16
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Wang K, Li Z, Wu Z, Zheng Y, Zeng S, E L, Liang J. Diagnostic Performance of Diffusion Tensor Imaging for Characterizing Breast Tumors: A Comprehensive Meta-Analysis. Front Oncol 2019; 9:1229. [PMID: 31803615 PMCID: PMC6876668 DOI: 10.3389/fonc.2019.01229] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Accepted: 10/28/2019] [Indexed: 12/24/2022] Open
Abstract
Rationale and Objectives: Controversy still exists on the diagnosability of diffusion tensor imaging (DTI) for breast lesions characterization across published studies. The clinical guideline of DTI used in the breast has not been established. This meta-analysis aims to pool relevant evidences and evaluate the diagnostic performance of DTI in the differential diagnosis of malignant and benign breast lesions. Materials and Methods: The studies that assessed the diagnostic performance of DTI parameters in the breast were searched in Embase, PubMed, and Cochrane Library between January 2010 and September 2019. Standardized mean differences and 95% confidence intervals of fractional anisotropy (FA), mean diffusivity (MD), and three diffusion eigenvalues (λ1, λ2, and λ3) were calculated using Review Manager 5.2. The pooled sensitivity, specificity, and area under the curve (AUC) were calculated with a bivariate model. Publication bias and heterogeneity between studies were also assessed using Stata 12.0. Results: Sixteen eligible studies incorporating 1,636 patients were included. The standardized mean differences indicated that breast cancers had a significantly higher FA but lower MD, λ1, λ2, and λ3 than those of benign lesions (all P < 0.05). Subgroup analysis indicated that invasive breast carcinoma (IBC) had a significantly lower MD value than that of ductal carcinoma in situ (DCIS) (P = 0.02). λ1 showed the best diagnostic accuracy with pooled sensitivity, specificity, and AUC of 93%, 92%, and 0.97, followed by MD (AUC = 0.92, sensitivity = 87%, specificity = 83%) and FA (AUC = 0.76, sensitivity = 70%, specificity = 70%) in the differential diagnosis of breast lesions. Conclusion: DTI with multiple quantitative parameters was adequate to differentiate breast cancers from benign lesions based on their biological characteristics. MD can further distinguish IBC from DCIS. The parameters, especially λ1 and MD, should attract our attention in clinical practice.
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Affiliation(s)
- Kai Wang
- Department of Medical Imaging, Shanxi DAYI Hospital, Taiyuan, China
| | - Zhipeng Li
- Department of Medical Imaging, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Zhifeng Wu
- Department of Medical Imaging, Shanxi DAYI Hospital, Taiyuan, China
| | - Yucong Zheng
- Department of Medical Imaging, Shanxi DAYI Hospital, Taiyuan, China
| | - Sihui Zeng
- Department of Medical Imaging, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Linning E
- Department of Medical Imaging, Shanxi DAYI Hospital, Taiyuan, China
| | - Jianye Liang
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
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17
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Nissan N, Allweis T, Menes T, Brodsky A, Paluch-Shimon S, Haas I, Golan O, Miller Y, Barlev H, Carmon E, Brodsky M, Anaby D, Lawson P, Halshtok-Neiman O, Shalmon A, Gotlieb M, Faermann R, Konen E, Sklair-Levy M. Breast MRI during lactation: effects on tumor conspicuity using dynamic contrast-enhanced (DCE) in comparison with diffusion tensor imaging (DTI) parametric maps. Eur Radiol 2019; 30:767-777. [DOI: 10.1007/s00330-019-06435-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Revised: 07/12/2019] [Accepted: 08/27/2019] [Indexed: 12/18/2022]
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18
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Iima M, Honda M, Sigmund EE, Ohno Kishimoto A, Kataoka M, Togashi K. Diffusion MRI of the breast: Current status and future directions. J Magn Reson Imaging 2019; 52:70-90. [PMID: 31520518 DOI: 10.1002/jmri.26908] [Citation(s) in RCA: 88] [Impact Index Per Article: 17.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 08/12/2019] [Indexed: 12/30/2022] Open
Abstract
Diffusion-weighted imaging (DWI) is increasingly being incorporated into routine breast MRI protocols in many institutions worldwide, and there are abundant breast DWI indications ranging from lesion detection and distinguishing malignant from benign tumors to assessing prognostic biomarkers of breast cancer and predicting treatment response. DWI has the potential to serve as a noncontrast MR screening method. Beyond apparent diffusion coefficient (ADC) mapping, which is a commonly used quantitative DWI measure, advanced DWI models such as intravoxel incoherent motion (IVIM), non-Gaussian diffusion MRI, and diffusion tensor imaging (DTI) are extensively exploited in this field, allowing the characterization of tissue perfusion and architecture and improving diagnostic accuracy without the use of contrast agents. This review will give a summary of the clinical literature along with future directions. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;52:70-90.
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Affiliation(s)
- Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.,Department of Clinical Innovative Medicine, Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, Kyoto, Japan
| | - Maya Honda
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Eric E Sigmund
- Department of Radiology, NYU Langone Health, New York, New York, USA.,Center for Advanced Imaging and Innovation (CAI2R), New York, New York, USA
| | - Ayami Ohno Kishimoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Masako Kataoka
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Kaori Togashi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
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19
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Luo J, Hippe DS, Rahbar H, Parsian S, Rendi MH, Partridge SC. Diffusion tensor imaging for characterizing tumor microstructure and improving diagnostic performance on breast MRI: a prospective observational study. Breast Cancer Res 2019; 21:102. [PMID: 31484577 PMCID: PMC6727336 DOI: 10.1186/s13058-019-1183-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Accepted: 08/09/2019] [Indexed: 11/24/2022] Open
Abstract
Background Diffusion-weighted imaging (DWI) can increase breast MRI diagnostic specificity due to the tendency of malignancies to restrict diffusion. Diffusion tensor imaging (DTI) provides further information over conventional DWI regarding diffusion directionality and anisotropy. Our study evaluates DTI features of suspicious breast lesions detected on MRI to determine the added diagnostic value of DTI for breast imaging. Methods With IRB approval, we prospectively enrolled patients over a 3-year period who had suspicious (BI-RADS category 4 or 5) MRI-detected breast lesions with histopathological results. Patients underwent multiparametric 3 T MRI with dynamic contrast-enhanced (DCE) and DTI sequences. Clinical factors (age, menopausal status, breast density, clinical indication, background parenchymal enhancement) and DCE-MRI lesion parameters (size, type, presence of washout, BI-RADS category) were recorded prospectively by interpreting radiologists. DTI parameters (apparent diffusion coefficient [ADC], fractional anisotropy [FA], axial diffusivity [λ1], radial diffusivity [(λ2 + λ3)/2], and empirical difference [λ1 − λ3]) were measured retrospectively. Generalized estimating equations (GEE) and least absolute shrinkage and selection operator (LASSO) methods were used for univariate and multivariate logistic regression, respectively. Diagnostic performance was internally validated using the area under the curve (AUC) with bootstrap adjustment. Results The study included 238 suspicious breast lesions (95 malignant, 143 benign) in 194 women. In univariate analysis, lower ADC, axial diffusivity, and radial diffusivity were associated with malignancy (OR = 0.37–0.42 per 1-SD increase, p < 0.001 for each), as was higher FA (OR = 1.45, p = 0.007). In multivariate analysis, LASSO selected only ADC (OR = 0.41) as a predictor for a DTI-only model, while both ADC (OR = 0.41) and FA (OR = 0.88) were selected for a model combining clinical and imaging parameters. Post-hoc analysis revealed varying association of FA with malignancy depending on the lesion type. The combined model (AUC = 0.81) had a significantly better performance than Clinical/DCE-MRI-only (AUC = 0.76, p < 0.001) and DTI-only (AUC = 0.75, p = 0.002) models. Conclusions DTI significantly improves diagnostic performance in multivariate modeling. ADC is the most important diffusion parameter for distinguishing benign and malignant breast lesions, while anisotropy measures may help further characterize tumor microstructure and microenvironment.
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Affiliation(s)
- Jing Luo
- Department of Radiology, University of Washington School of Medicine, 825 Eastlake Avenue East, Seattle, WA, 98109, USA
| | - Daniel S Hippe
- Department of Radiology, University of Washington School of Medicine, 825 Eastlake Avenue East, Seattle, WA, 98109, USA
| | - Habib Rahbar
- Department of Radiology, University of Washington School of Medicine, 825 Eastlake Avenue East, Seattle, WA, 98109, USA
| | - Sana Parsian
- Department of Radiology, University of Washington School of Medicine, 825 Eastlake Avenue East, Seattle, WA, 98109, USA
| | - Mara H Rendi
- Department of Pathology, University of Washington School of Medicine, 1959 NE Pacific St. Box 356100, Seattle, WA, 98195, USA
| | - Savannah C Partridge
- Department of Radiology, University of Washington School of Medicine, 825 Eastlake Avenue East, Seattle, WA, 98109, USA. .,Department of Radiology, Seattle Cancer Care Alliance, 1144 Eastlake Ave E, LG2-200, PO Box 19023, Seattle, WA, 98109, USA.
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20
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Simultaneous Multislice Echo Planar Imaging for Accelerated Diffusion-Weighted Imaging of Malignant and Benign Breast Lesions. Invest Radiol 2019; 54:524-530. [DOI: 10.1097/rli.0000000000000560] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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21
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Park VY, Kim SG, Kim EK, Moon HJ, Yoon JH, Kim MJ. Diffusional kurtosis imaging for differentiation of additional suspicious lesions on preoperative breast MRI of patients with known breast cancer. Magn Reson Imaging 2019; 62:199-208. [PMID: 31323316 DOI: 10.1016/j.mri.2019.07.011] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Revised: 07/02/2019] [Accepted: 07/14/2019] [Indexed: 01/10/2023]
Abstract
PURPOSE To investigate the potential of diffusional kurtosis imaging (DKI) and conventional diffusion-weighted imaging (DWI) in the evaluation of additional suspicious lesions at preoperative breast magnetic resonance imaging (MRI) in patients with breast cancer. MATERIALS AND METHODS Fifty-three additional suspicious lesions in 45 patients with breast cancer, which were detected on preoperative breast MRI, were examined with a 3-T MR system. DKI and DWI data were obtained using a spin-echo single-shot echo-planar imaging sequence with b-values of 0, 50, 600, 1000, and 3000 s/mm2. Histogram parameters (mean, standard deviation, minimum, maximum, 10th, 25th, 50th, 75th, 90th percentiles, kurtosis, skewness and entropy) of ADC from DWI and diffusivity (D), kurtosis (K) from DKI were calculated after postprocessing. Parameters were compared between benign vs. ductal carcinoma in situ (DCIS) vs. invasive breast lesions and diagnostic performances were evaluated by receiver operating characteristic (ROC) analysis. Correlation between the mean values of D and K was analyzed according to lesion type. RESULTS Multiple histogram parameters of D (mean, 25th, 50th percentile, 75th percentile, and entropy) differed between benign and invasive breast lesions (all P < 0.005), but none differed between benign vs. DCIS. D-90th percentile differed between DCIS vs. invasive cancer (P = 0.040). K-10th percentile differed between benign vs. DCIS (P = 0.015). ADC-75th percentile differed between benign vs. invasive cancer and ADC-75th percentile, ADC-90th percentile differed between DCIS vs. invasive cancer, respectively (all P < 0.005). ROC curve analysis showed high specificity for discrimination between benign and invasive cancer. D-mean and K-mean showed strong correlation in benign (rs = -0.813) and invasive lesions (rs = -0.853), but no significant correlation in DCIS. CONCLUSION DKI may aid in the differentiation of additional suspicious lesions at preoperative breast MRI. Both ADC and DKI may have lower potential in differentiating DCIS from benign lesions.
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Affiliation(s)
- Vivian Youngjean Park
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, South Korea
| | - Sungheon G Kim
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY 10016, United States
| | - Eun-Kyung Kim
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, South Korea
| | - Hee Jung Moon
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, South Korea
| | - Jung Hyun Yoon
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, South Korea
| | - Min Jung Kim
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, South Korea.
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22
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Tsougos I, Bakosis M, Tsivaka D, Athanassiou E, Fezoulidis I, Arvanitis D, Vassiou K. Diagnostic performance of quantitative diffusion tensor imaging for the differentiation of breast lesions at 3 T MRI. Clin Imaging 2019; 53:25-31. [DOI: 10.1016/j.clinimag.2018.10.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Revised: 09/19/2018] [Accepted: 10/01/2018] [Indexed: 12/22/2022]
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23
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Abdel Razek AAK, Zaky M, Bayoumi D, Taman S, Abdelwahab K, Alghandour R. Diffusion tensor imaging parameters in differentiation recurrent breast cancer from post-operative changes in patients with breast-conserving surgery. Eur J Radiol 2018; 111:76-80. [PMID: 30691669 DOI: 10.1016/j.ejrad.2018.12.022] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Revised: 12/12/2018] [Accepted: 12/29/2018] [Indexed: 12/12/2022]
Abstract
AIM OF THE WORK To investigate mean diffusivity (MD) and fractional anisotropy (FA) measured by diffusion tensor imaging (DTI) as complementary tools to differentiate recurrent breast cancer from post-operative changes in patients with breast-conserving surgery (BCS). PATIENTS AND METHODS Prospective study was conducted upon 30 patients with BCS that underwent DTI and dynamic contrast MR imaging. DTI was performed using an axial two-dimensional spin-echo echo-planar imaging sequence. The MD and FA of the lesions were calculated by 2 observers. A single pixel seed isotropic region of interest was placed in the solid part of the tumor on the axial color FA map guided by an enhanced part of the tumor. The final diagnosis was done by biopsy for all patients. RESULTS /s) used for differentiation between entities revealed sensitivity (76.9%, 92.3%), specificity (82.4%, 64.7%) and accuracy (80%, 76.7%) of both observers respectively. At ROC curve analysis of FA, the AUC was 0.82 and 0.75 by both observers. The threshold FA (0.82, 0.75) was used for differentiation between entities revealed sensitivity (92.3%, 76.9%), specificity (70.6%, 70.6%) and accuracy of (80.0%, 73.3%) of both observers respectively. There was a strong positive correlation of MD (r = 0.86) and FA (r = 0.73) of both observers. Combined analysis of FA and MD used for differentiation between entities had AUC (0.90, 0.88) revealed sensitivity (92.3%, 92.3%), specificity (82.4%, 70.6%) and accuracy of (86.7%, 80.0%) for both observers respectively. CONCLUSIONS Combined analysis of MD and FA of DTI may play an important role as a non-invasive method for differentiation recurrent breast cancer from post-operative changes in patients with BCS.
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Affiliation(s)
| | - Mona Zaky
- Department of Diagnostic Radiology, Mansoura Faculty of Medicine, Mansoura, 13551, Egypt.
| | - Dalia Bayoumi
- Department of Diagnostic Radiology, Mansoura Faculty of Medicine, Mansoura, 13551, Egypt.
| | - Saher Taman
- Department of Diagnostic Radiology, Mansoura Faculty of Medicine, Mansoura, 13551, Egypt.
| | - Khaled Abdelwahab
- Department of Oncology Surgery, Mansoura faculty of Medicine, Mansoura, 13551, Egypt.
| | - Reham Alghandour
- Department of Medical Oncology, Mansoura Faculty of Medicine, Mansoura, 13551, Egypt.
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24
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Nissan N, Furman-Haran E, Allweis T, Menes T, Golan O, Kent V, Barsuk D, Paluch-Shimon S, Haas I, Brodsky M, Bordsky A, Granot LF, Halshtok-Neiman O, Faermann R, Shalmon A, Gotlieb M, Konen E, Sklair-Levy M. Noncontrast Breast MRI During Pregnancy Using Diffusion Tensor Imaging: A Feasibility Study. J Magn Reson Imaging 2018; 49:508-517. [DOI: 10.1002/jmri.26228] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Accepted: 06/01/2018] [Indexed: 01/09/2023] Open
Affiliation(s)
- Noam Nissan
- Department of Radiology; Sheba Medical Center; Israel
- Sackler School of Medicine; Tel Aviv University; Israel
| | - Edna Furman-Haran
- Department of Biological Services; Weizmann Institute of Science; Israel
| | - Tanir Allweis
- Department of General Surgery; Kaplan Medical Center; Israel
| | - Tehillah Menes
- Department of General Surgery; Souraski Medical Center; Israel
| | - Orit Golan
- Department of Radiology; Souraski Medical Center; Israel
| | - Varda Kent
- Department of Radiology; Assaf Harofeh Medical Center; Israel
| | - Daphna Barsuk
- Department of General Surgery; Assuta Medical Center; Israel
| | | | - Ilana Haas
- Department of General Surgery; Meir Medical Center; Israel
| | - Malka Brodsky
- Meirav Center of Breast Care, Sheba Medical Center; Israel
| | - Asia Bordsky
- Department of General Surgery; Bnai Zion Medical Center; Israel
| | | | - Osnat Halshtok-Neiman
- Department of Radiology; Sheba Medical Center; Israel
- Sackler School of Medicine; Tel Aviv University; Israel
| | - Renata Faermann
- Department of Radiology; Sheba Medical Center; Israel
- Sackler School of Medicine; Tel Aviv University; Israel
| | - Anat Shalmon
- Department of Radiology; Sheba Medical Center; Israel
- Sackler School of Medicine; Tel Aviv University; Israel
| | - Michael Gotlieb
- Department of Radiology; Sheba Medical Center; Israel
- Sackler School of Medicine; Tel Aviv University; Israel
| | - Eli Konen
- Department of Radiology; Sheba Medical Center; Israel
- Sackler School of Medicine; Tel Aviv University; Israel
| | - Miri Sklair-Levy
- Department of Radiology; Sheba Medical Center; Israel
- Sackler School of Medicine; Tel Aviv University; Israel
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25
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Lair M, Renaux-Petel M, Hassani A, Cruypeninck Y, Vasies I, Liard A, Dacher JN, Vivier PH. Diffusion tensor imaging in acute pyelonephritis in children. Pediatr Radiol 2018; 48:1081-1085. [PMID: 29789888 DOI: 10.1007/s00247-018-4146-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2017] [Revised: 04/19/2018] [Accepted: 04/23/2018] [Indexed: 12/22/2022]
Abstract
BACKGROUND Diffusion-weighted imaging plays a key role in the imaging of acute pyelonephritis by MRI. However the use of respiratory triggering is challenging and time-consuming in children. Diffusion tensor imaging without respiratory triggering might provide satisfying images of the moving kidneys. OBJECTIVE To compare mean diffusivity diffusion tensor images obtained with free breathing with diffusion-weighted images obtained with respiratory triggering. MATERIALS AND METHODS Thirty-one children with suspected acute pyelonephritis underwent axial diffusion tensor imaging acquisition with free breathing and axial and coronal diffusion-weighted imaging acquisitions with respiratory triggering. We compared image quality and detection of nephritis between the two sequences. RESULTS Diffusion tensor imaging demonstrated agreement with diffusion-weighted imaging in all cases, with no difference in the detection of nephritis areas. The image quality was significantly better with diffusion tensor imaging (P<0.01). CONCLUSION Diffusion tensor imaging could replace diffusion-weighted imaging for diagnosis of acute pyelonephritis.
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Affiliation(s)
- Mickaël Lair
- CHU C. Nicolle, Service de radiopédiatrie, Rouen University Hospital, Cedex, Rouen, France
| | - Mariette Renaux-Petel
- CHU C. Nicolle, Service de chirurgie pédiatrique, Rouen University Hospital, Cedex, Rouen, France
| | - Adnan Hassani
- CHU C. Nicolle, Service de radiopédiatrie, Rouen University Hospital, Cedex, Rouen, France
| | - Yohann Cruypeninck
- CHU C. Nicolle, Service de radiopédiatrie, Rouen University Hospital, Cedex, Rouen, France
| | - Ioana Vasies
- CHU C. Nicolle, Service de radiopédiatrie, Rouen University Hospital, Cedex, Rouen, France
| | - Agnès Liard
- CHU C. Nicolle, Service de chirurgie pédiatrique, Rouen University Hospital, Cedex, Rouen, France
| | - Jean-Nicolas Dacher
- CHU C. Nicolle, Service de radiopédiatrie, Rouen University Hospital, Cedex, Rouen, France
| | - Pierre-Hugues Vivier
- CHU C. Nicolle, Service de radiopédiatrie, Rouen University Hospital, Cedex, Rouen, France. .,Ramsay - Générale de Santé, Hôpital Privé de l'Estuaire, Radiology, Le Havre, France.
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26
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Kim JY, Kim JJ, Kim S, Choo KS, Kim A, Kang T, Park H. Diffusion tensor magnetic resonance imaging of breast cancer: associations between diffusion metrics and histological prognostic factors. Eur Radiol 2018; 28:3185-3193. [DOI: 10.1007/s00330-018-5429-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Revised: 02/23/2018] [Accepted: 03/16/2018] [Indexed: 01/06/2023]
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27
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Cancer Metabolism and Tumor Heterogeneity: Imaging Perspectives Using MR Imaging and Spectroscopy. CONTRAST MEDIA & MOLECULAR IMAGING 2017; 2017:6053879. [PMID: 29114178 PMCID: PMC5654284 DOI: 10.1155/2017/6053879] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/15/2017] [Revised: 07/31/2017] [Accepted: 08/27/2017] [Indexed: 12/26/2022]
Abstract
Cancer cells reprogram their metabolism to maintain viability via genetic mutations and epigenetic alterations, expressing overall dynamic heterogeneity. The complex relaxation mechanisms of nuclear spins provide unique and convertible tissue contrasts, making magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) pertinent imaging tools in both clinics and research. In this review, we summarized MR methods that visualize tumor characteristics and its metabolic phenotypes on an anatomical, microvascular, microstructural, microenvironmental, and metabolomics scale. The review will progress from the utilities of basic spin-relaxation contrasts in cancer imaging to more advanced imaging methods that measure tumor-distinctive parameters such as perfusion, water diffusion, magnetic susceptibility, oxygenation, acidosis, redox state, and cell death. Analytical methods to assess tumor heterogeneity are also reviewed in brief. Although the clinical utility of tumor heterogeneity from imaging is debatable, the quantification of tumor heterogeneity using functional and metabolic MR images with development of robust analytical methods and improved MR methods may offer more critical roles of tumor heterogeneity data in clinics. MRI/MRS can also provide insightful information on pharmacometabolomics, biomarker discovery, disease diagnosis and prognosis, and treatment response. With these future directions in mind, we anticipate the widespread utilization of these MR-based techniques in studying in vivo cancer biology to better address significant clinical needs.
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28
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Nissan N, Furman-Haran E, Shapiro-Feinberg M, Grobgeld D, Degani H. Monitoring In-Vivo the Mammary Gland Microstructure during Morphogenesis from Lactation to Post-Weaning Using Diffusion Tensor MRI. J Mammary Gland Biol Neoplasia 2017; 22:193-202. [PMID: 28707256 DOI: 10.1007/s10911-017-9383-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Accepted: 07/03/2017] [Indexed: 12/30/2022] Open
Abstract
Lactation and the return to the pre-conception state during post-weaning are regulated by hormonal induced processes that modify the microstructure of the mammary gland, leading to changes in the features of the ductal / glandular tissue, the stroma and the fat tissue. These changes create a challenge in the radiological workup of breast disorder during lactation and early post-weaning. Here we present non-invasive MRI protocols designed to record in vivo high spatial resolution, T2-weighted images and diffusion tensor images of the entire mammary gland. Advanced imaging processing tools enabled tracking the changes in the anatomical and microstructural features of the mammary gland from the time of lactation to post-weaning. Specifically, by using diffusion tensor imaging (DTI) it was possible to quantitatively distinguish between the ductal / glandular tissue distention during lactation and the post-weaning involution. The application of the T2-weighted imaging and DTI is completely safe, non-invasive and uses intrinsic contrast based on differences in transverse relaxation rates and water diffusion rates in various directions, respectively. This study provides a basis for further in-vivo monitoring of changes during the mammary developmental stages, as well as identifying changes due to malignant transformation in patients with pregnancy associated breast cancer (PABC).
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Affiliation(s)
- Noam Nissan
- Department of Biological Regulation, Weizmann Institute of Science, P.O. Box 26, 7610001, Rehovot, Israel
- Diagnostic Imaging Department, Sheba Medical Center, Tel Hashomer, Israel
| | - Edna Furman-Haran
- Life Sciences Core Facilities, Weizmann Institute of Science, Rehovot, Israel
| | | | - Dov Grobgeld
- Department of Biological Regulation, Weizmann Institute of Science, P.O. Box 26, 7610001, Rehovot, Israel
| | - Hadassa Degani
- Department of Biological Regulation, Weizmann Institute of Science, P.O. Box 26, 7610001, Rehovot, Israel.
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29
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Nissan N. Modifications of pancreatic diffusion MRI by tissue characteristics: what are we weighting for? NMR IN BIOMEDICINE 2017; 30:e3728. [PMID: 28470823 DOI: 10.1002/nbm.3728] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2017] [Revised: 02/10/2017] [Accepted: 03/13/2017] [Indexed: 06/07/2023]
Abstract
Diffusion-weighted imaging holds the potential to improve the diagnosis and biological characterization of pancreatic disease, and in particular pancreatic cancer, which exhibits decreased values of the apparent diffusion coefficient (ADC). Yet, variable and overlapping ADC values have been reported for the healthy and the pathological pancreas, including for cancer and other benign conditions. This controversy reflects the complexity of probing the water-diffusion process in the pancreas, which is dependent upon multiple biological factors within this organ's unique physiological environment. In recent years, extensive studies have investigated the correlation between tissue properties including cellularity, vascularity, fibrosis, secretion and microstructure and pancreatic diffusivity. Understanding how the various physiological and pathological features and the underlying functional processes affect the diffusion measurement may serve to optimize the method for improved diagnostic gain. Therefore, the aim of the present review article is to elucidate the relationship between pancreatic tissue characteristics and diffusion MRI measurement.
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Affiliation(s)
- Noam Nissan
- Department of Diagnostic Imaging, Chaim Sheba Medical Center, Tel HaShomer 5265601, Israel
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30
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Bailey C, Siow B, Panagiotaki E, Hipwell JH, Mertzanidou T, Owen J, Gazinska P, Pinder SE, Alexander DC, Hawkes DJ. Microstructural models for diffusion MRI in breast cancer and surrounding stroma: an ex vivo study. NMR IN BIOMEDICINE 2017; 30:e3679. [PMID: 28000292 PMCID: PMC5244665 DOI: 10.1002/nbm.3679] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Revised: 11/06/2016] [Accepted: 11/07/2016] [Indexed: 05/17/2023]
Abstract
The diffusion signal in breast tissue has primarily been modelled using apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion tensor (DT) models, which may be too simplistic to describe the underlying tissue microstructure. Formalin-fixed breast cancer samples were scanned using a wide range of gradient strengths, durations, separations and orientations. A variety of one- and two-compartment models were tested to determine which best described the data. Models with restricted diffusion components and anisotropy were selected in most cancerous regions and there were no regions in which conventional ADC or DT models were selected. Maps of ADC generally related to cellularity on histology, but maps of parameters from more complex models suggest that both overall cell volume fraction and individual cell size can contribute to the diffusion signal, affecting the specificity of ADC to the tissue microstructure. The areas of coherence in diffusion anisotropy images were small, approximately 1 mm, but the orientation corresponded to stromal orientation patterns on histology.
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Affiliation(s)
- Colleen Bailey
- University College LondonCentre for Medical Image ComputingLondonUK
| | - Bernard Siow
- University College LondonCentre for Advanced Biomedical ImagingLondonUK
| | | | - John H. Hipwell
- University College LondonCentre for Medical Image ComputingLondonUK
| | | | - Julie Owen
- King's College LondonGuy's Hospital, Breast ResearchPathologyLondonUK
| | - Patrycja Gazinska
- King's College LondonGuy's Hospital, Breast ResearchPathologyLondonUK
| | - Sarah E. Pinder
- King's College LondonGuy's Hospital, Breast ResearchPathologyLondonUK
| | | | - David J. Hawkes
- University College LondonCentre for Medical Image ComputingLondonUK
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31
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Partridge SC, Nissan N, Rahbar H, Kitsch AE, Sigmund EE. Diffusion-weighted breast MRI: Clinical applications and emerging techniques. J Magn Reson Imaging 2016; 45:337-355. [PMID: 27690173 DOI: 10.1002/jmri.25479] [Citation(s) in RCA: 215] [Impact Index Per Article: 26.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2016] [Accepted: 08/29/2016] [Indexed: 12/28/2022] Open
Abstract
Diffusion-weighted MRI (DWI) holds potential to improve the detection and biological characterization of breast cancer. DWI is increasingly being incorporated into breast MRI protocols to address some of the shortcomings of routine clinical breast MRI. Potential benefits include improved differentiation of benign and malignant breast lesions, assessment and prediction of therapeutic efficacy, and noncontrast detection of breast cancer. The breast presents a unique imaging environment with significant physiologic and inter-subject variations, as well as specific challenges to achieving reliable high quality diffusion-weighted MR images. Technical innovations are helping to overcome many of the image quality issues that have limited widespread use of DWI for breast imaging. Advanced modeling approaches to further characterize tissue perfusion, complexity, and glandular organization may expand knowledge and yield improved diagnostic tools. LEVEL OF EVIDENCE 5 J. Magn. Reson. Imaging 2016 J. Magn. Reson. Imaging 2017;45:337-355.
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Affiliation(s)
- Savannah C Partridge
- Department of Radiology, University of Washington School of Medicine, Seattle, Washington, USA.,Breast Imaging, Seattle Cancer Care Alliance, Seattle, Washington, USA
| | - Noam Nissan
- Department of Biological Regulation, Weizmann Institute of Science, Rehovot, Israel
| | - Habib Rahbar
- Department of Radiology, University of Washington School of Medicine, Seattle, Washington, USA.,Breast Imaging, Seattle Cancer Care Alliance, Seattle, Washington, USA
| | - Averi E Kitsch
- Department of Radiology, University of Washington School of Medicine, Seattle, Washington, USA.,Breast Imaging, Seattle Cancer Care Alliance, Seattle, Washington, USA
| | - Eric E Sigmund
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
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