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Rakhawy MMME, Soliman N, Elnahas W, Karam R, Abdel-Khalek AM. Prediction of local breast cancer recurrence after surgery: the added value of diffusion tensor imaging. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2022. [DOI: 10.1186/s43055-022-00831-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
There is considerable overlap between benign postoperative changes and recurrent breast cancer imaging features in patients surgically treated for breast cancer. This study aims to evaluate the value of adding multiple diffusion tensor imaging (DTI) parameters, including mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity, (AD), and relative anisotropy (RA) in differentiating breast cancer recurrence from postoperative changes in patients who were surgically treated for breast cancer and to also evaluate the role of these parameters in characterizing the different pathologies seen in the postoperative breast.
Results
This is a prospective study that was performed on female patients who were surgically treated for breast cancer. The study was done on 60 cases having 77 breast lesions. (Sixty-two of them were described as mass lesions and 15 of them were described as non-mass enhancement on MRI.) Among analyzed DTI parameters, MD showed the highest sensitivity (97.1%), specificity (88.1%), and accuracy (92.2%) in predicting recurrent breast cancer. FA, AD, and RD showed sensitivity (77.1%, 85.7%, and 88.6%) and specificity (83.3%, 83.3%, and 73.8%) in predicting recurrent breast cancer, respectively. The median MD values were lower in grade III recurrent breast cancers when compared to its values in recurrent grade II breast cancers and recurrent DCIS (0.6 × 10–3 mm2/s vs. 0.8 × 10–3 mm2/s and 0.9 × 10–3 mm2/s), respectively. FA also showed median values in grade III recurrent breast cancer higher than its values in grade II recurrent breast cancer and recurrent DCIS (0.6 vs. 0.5 and 0.39), respectively. The sensitivity, specificity, PPV, NPV, accuracy, F1 score, and MCC of DCE-MRI alone versus DCE-MRI plus combined DTI parameters were 88.6% versus 100%, 88.1% versus 90.5%, 86.1% versus 89.7%, 90.2% versus 100%, 88.3% versus 94.6%, 87.3% versus 94.6%, and 76.5% versus 90.1%, respectively.
Conclusions
DTI may play an important role as a complementary method to discriminate recurrent breast cancer from postoperative changes in patients surgically treated for previous breast cancer.
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Cho E, Baek HJ, Szczepankiewicz F, An HJ, Jung EJ, Lee HJ, Lee J, Gho SM. Clinical experience of tensor-valued diffusion encoding for microstructure imaging by diffusional variance decomposition in patients with breast cancer. Quant Imaging Med Surg 2022; 12:2002-2017. [PMID: 35284250 PMCID: PMC8899958 DOI: 10.21037/qims-21-870] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 12/13/2021] [Indexed: 08/28/2023]
Abstract
BACKGROUND Diffusion-weighted imaging plays a key role in magnetic resonance imaging (MRI) of breast tumors. However, it remains unclear how to interpret single diffusion encoding with respect to its link with tissue microstructure. The purpose of this retrospective cross-sectional study was to use tensor-valued diffusion encoding to investigate the underlying microstructure of invasive ductal carcinoma (IDC) and evaluate its potential value in a clinical setting. METHODS We retrospectively reviewed biopsy-proven breast cancer patients who underwent preoperative breast MRI examination from July 2020 to March 2021. We reviewed the MRI of 29 patients with 30 IDCs, including analysis by diffusional variance decomposition enabled by tensor-valued diffusion encoding. The diffusion parameters of mean diffusivity (MD), total mean kurtosis (MKT), anisotropic mean kurtosis (MKA), isotropic mean kurtosis (MKI), macroscopic fractional anisotropy (FA), and microscopic fractional anisotropy (µFA) were estimated. The parameter differences were compared between IDC and normal fibroglandular breast tissue (FGBT), as well as the association between the diffusion parameters and histopathologic items. RESULTS The mean value of MD in IDCs was significantly lower than that of normal FGBT (1.07±0.27 vs. 1.34±0.29, P<0.001); however, MKT, MKA, MKI, FA, and µFA were significantly higher (P<0.005). Among all the diffusion parameters, MKI was positively correlated with the tumor size on both MRI and pathological specimen (rs=0.38, P<0.05 vs. rs=0.54, P<0.01), whereas MKT had a positive correlation with the tumor size in the pathological specimen only (rs=0.47, P<0.02). In addition, the lymph node (LN) metastasis group had significantly higher MKT, MKA, and µFA compared to the metastasis negative group (P<0.05). CONCLUSIONS Tensor-valued diffusion encoding enables a useful non-invasive method for characterizing breast cancers with information on tissue microstructures. Particularly, µFA could be a potential imaging biomarker for evaluating breast cancers prior to surgery or chemotherapy.
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Affiliation(s)
- Eun Cho
- Department of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Seongsan-gu, Changwon, Republic of Korea
| | - Hye Jin Baek
- Department of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Seongsan-gu, Changwon, Republic of Korea
- Department of Radiology, Institute of Health Sciences, Gyeongsang National University School of Medicine, Jinju-daero, Jinju, Republic of Korea
| | - Filip Szczepankiewicz
- Department of Diagnostic Radiology, Clinical Sciences Lund, Lund University, Lund, Klinikgatan, Sweden
| | - Hyo Jung An
- Department of Pathology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Seongsan-gu, Changwon, Republic of Korea
| | - Eun Jung Jung
- Department of Surgery, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea
| | - Ho-Joon Lee
- Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-gu, Busan, Republic of Korea
| | | | - Sung-Min Gho
- MR Clinical Solutions & Research Collaborations, GE Healthcare, Seoul, Republic of Korea
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Diffusion tensor imaging on 3-T MRI breast: diagnostic performance in comparison to diffusion-weighted imaging. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2021. [DOI: 10.1186/s43055-021-00473-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Abstract
Background
Breast cancer is the most prevalent cancer among females. Dynamic contrast-enhanced MRI (DCE-MRI) breast is highly sensitive (90%) in the detection of breast cancer. Despite its high sensitivity in detecting breast cancer, its specificity (72%) is moderate. Owing to 3-T breast MRI which has the advantage of a higher signal to noise ratio and shorter scanning time rather than the 1.5-T MRI, the adding of new techniques as diffusion tensor imaging (DTI) to breast MRI became more feasible.
Diffusion-weighted imaging (DWI) which tracks the diffusion of the tissue water molecule as well as providing data about the integrity of the cell membrane has been used as a valuable additional tool of DCE-MRI to increase its specificity.
Based on DWI, more details about the microstructure could be detected using diffusion tensor imaging. The DTI applies diffusion in many directions so apparent diffusion coefficient (ADC) will vary according to the measured direction raising its sensitivity to microstructure elements and cellular density. This study aimed to investigate the diagnostic accuracy of DTI in the assessment of breast lesions in comparison to DWI.
Results
By analyzing the data of the 50 cases (31 malignant cases and 19 benign cases), the sensitivity and specificity of DWI in differentiation between benign and malignant lesions were about 90% and 63% respectively with PPV 90% and NPV 62%, while the DTI showed lower sensitivity and specificity about 81% and 51.7%, respectively, with PPV 78.9% and NPV 54.8% (P-value ≤ 0.05).
Conclusion
While the DWI is still the most established diffusion parameter, DTI may be helpful in the further characterization of tumor microstructure and differentiation between benign and malignant breast lesions.
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Smith HJ. The history of magnetic resonance imaging and its reflections in Acta Radiologica. Acta Radiol 2021; 62:1481-1498. [PMID: 34657480 DOI: 10.1177/02841851211050857] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The first reports in Acta Radiologica on magnetic resonance imaging (MRI) were published in 1984, four years after the first commercial MR scanners became available. For the first two years, all MR papers originated from the USA. Nordic contributions started in 1986, and until 2020, authors from 44 different countries have published MR papers in Acta Radiologica. Papers on MRI have constituted, on average, 30%-40% of all published original articles in Acta Radiologica, with a high of 49% in 2019. The MR papers published since 1984 document tremendous progress in several areas such as magnet and coil design, motion compensation techniques, faster image acquisitions, new image contrast, contrast-enhanced MRI, functional MRI, and image analysis. In this historical review, all of these aspects of MRI are discussed and related to Acta Radiologica papers.
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Affiliation(s)
- Hans-Jørgen Smith
- Department of Radiology and Nuclear Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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Usefulness of readout-segmented EPI-based diffusion tensor imaging of lacrimal gland for detection and disease staging in thyroid-associated ophthalmopathy. BMC Ophthalmol 2021; 21:281. [PMID: 34284740 PMCID: PMC8290601 DOI: 10.1186/s12886-021-02044-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 07/09/2021] [Indexed: 11/19/2022] Open
Abstract
Background Dysfunction of lacrimal gland (LG) gains increasing attention in patients with thyroid-associated ophthalmopathy (TAO), while the underlying pathological change is still not fully established. This study aimed to evaluate the utility of readout-segmented echo-planar imaging (rs-EPI)-based diffusion tensor imaging (DTI) in non-invasively detecting microstructural alterations of LG in patients with TAO, as well as in discriminating disease activity. Methods Thirty TAO patients and 15 age- and sex- matched healthy controls, who underwent rs-EPI-based DTI, were retrospectively enrolled. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) of LG, and clinical-endocrinological variables were collected and compared. The correlations between FA and ADC values of LG and serum thyroid biochemical markers were also assessed. Results TAO group showed significantly lower FA (P < 0.001) and higher ADC (P = 0.014) of LG than healthy group. Active subgroup had significantly lower FA (P < 0.001) and higher ADC (P < 0.001) than inactive subgroup. In TAO group, FA of LG was significantly and negatively correlated with TRAb (r=-0.475, P = 0.008), while ADC of LG showed no significant correlation (P > 0.05). The area under receiver operating characteristic curve of FA was significantly greater than that under curve of ADC for discriminating disease activity (0.832 vs. 0.570, P = 0.009). Conclusions rs-EPI-based DTI is a useful tool to characterize the microstructural change of LG in patients with TAO. The derived metrics, particularly FA, can help to reveal disease activity.
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Tsougos I. Letter to the Editor. Acta Radiol 2021; 62:585. [PMID: 32795084 DOI: 10.1177/0284185120938050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
- Ioannis Tsougos
- Department of Medicine, University of Thessaly, Larissa, Greece
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7
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Zhu CR, Zhu J. The usefulness of proton magnetic resonance spectroscopy for the differential diagnosis of breast lesions. Acta Radiol 2021; 62:584. [PMID: 32795102 DOI: 10.1177/0284185120936259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
- Chun-Rong Zhu
- Sichuan Key Laboratory of Medical Imaging, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, PR China
| | - Jiang Zhu
- Sichuan Key Laboratory of Medical Imaging, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, PR China
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Irimia A, Van Horn JD. Mapping the rest of the human connectome: Atlasing the spinal cord and peripheral nervous system. Neuroimage 2021; 225:117478. [PMID: 33160086 PMCID: PMC8485987 DOI: 10.1016/j.neuroimage.2020.117478] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 09/15/2020] [Accepted: 10/13/2020] [Indexed: 12/13/2022] Open
Abstract
The emergence of diffusion, structural, and functional neuroimaging methods has enabled major multi-site efforts to map the human connectome, which has heretofore been defined as containing all neural connections in the central nervous system (CNS). However, these efforts are not structured to examine the richness and complexity of the peripheral nervous system (PNS), which arguably forms the (neglected) rest of the connectome. Despite increasing interest in an atlas of the spinal cord (SC) and PNS which is simultaneously stereotactic, interactive, electronically dissectible, scalable, population-based and deformable, little attention has thus far been devoted to this task of critical importance. Nevertheless, the atlasing of these complete neural structures is essential for neurosurgical planning, neurological localization, and for mapping those components of the human connectome located outside of the CNS. Here we recommend a modification to the definition of the human connectome to include the SC and PNS, and argue for the creation of an inclusive atlas to complement current efforts to map the brain's human connectome, to enhance clinical education, and to assist progress in neuroscience research. In addition to providing a critical overview of existing neuroimaging techniques, image processing methodologies and algorithmic advances which can be combined for the creation of a full connectome atlas, we outline a blueprint for ultimately mapping the entire human nervous system and, thereby, for filling a critical gap in our scientific knowledge of neural connectivity.
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Affiliation(s)
- Andrei Irimia
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, 3715 McClintock Avenue, Los Angeles CA 90089, United States; Corwin D. Denney Research Center, Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, 1042 Downey Way, Los Angeles, CA 90089, United States.
| | - John Darrell Van Horn
- Department of Psychology, University of Virginia, 485 McCormick Road, Gilmer Hall, Room 102, Charlottesville, Virginia 22903, United States; School of Data Science, University of Virginia, Dell 1, Charlottesville, Virginia 22903, United States.
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Jagannathan NR. Application of in vivo MR methods in the study of breast cancer metabolism. NMR IN BIOMEDICINE 2019; 32:e4032. [PMID: 30456917 DOI: 10.1002/nbm.4032] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2018] [Revised: 08/25/2018] [Accepted: 09/26/2018] [Indexed: 06/09/2023]
Abstract
In the last two decades, various in vivo MR methodologies have been evaluated for their potential in the study of cancer metabolism. During malignant transformation, metabolic alterations occur, leading to morphological and functional changes. Among various MR methods, in vivo MRS has been extensively used in breast cancer to study the metabolism of cells, tissues or whole organs. It provides biochemical information at the metabolite level. Altered choline, phospholipid and energy metabolism has been documented using proton (1 H), phosphorus (31 P) and carbon (13 C) isotopes. Increased levels of choline-containing compounds, phosphomonoesters and phosphodiesters in breast cancer, which are indicative of altered choline and phospholipid metabolism, have been reported using in vivo, in vitro and ex vivo NMR studies. These changes are reversed on successful therapy, which depends on the treatment regimen given. Monitoring the various tumor intermediary metabolic pathways using nuclear spin hyperpolarization of 13 C-labeled substrates by dynamic nuclear polarization has also been recently reported. Furthermore, the utility of various methods such as diffusion, dynamic contrast and perfusion MRI have also been evaluated to study breast tumor metabolism. Parameters such as tumor volume, apparent diffusion coefficient, volume transfer coefficient and extracellular volume ratio are estimated. These parameters provide information on the changes in tumor microstructure, microenvironment, abnormal vasculature, permeability and grade of the tumor. Such changes seen during cancer progression are due to alterations in the tumor metabolism, leading to changes in cell architecture. Due to architectural changes, the tissue mechanical properties are altered; this can be studied using magnetic resonance elastography, which measures the elastic properties of tissues. Moreover, these structural MRI methods can be used to investigate the effect of therapy-induced changes in tumor characteristics. This review discusses the potential of various in vivo MR methodologies in the study of breast cancer metabolism.
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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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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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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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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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Application of Radiomics and Decision Support Systems for Breast MR Differential Diagnosis. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2018; 2018:7417126. [PMID: 30344618 PMCID: PMC6174735 DOI: 10.1155/2018/7417126] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Revised: 07/24/2018] [Accepted: 09/04/2018] [Indexed: 01/17/2023]
Abstract
Over the years, MR systems have evolved from imaging modalities to advanced computational systems producing a variety of numerical parameters that can be used for the noninvasive preoperative assessment of breast pathology. Furthermore, the combination with state-of-the-art image analysis methods provides a plethora of quantifiable imaging features, termed radiomics that increases diagnostic accuracy towards individualized therapy planning. More importantly, radiomics can now be complemented by the emerging deep learning techniques for further process automation and correlation with other clinical data which facilitate the monitoring of treatment response, as well as the prediction of patient's outcome, by means of unravelling of the complex underlying pathophysiological mechanisms which are reflected in tissue phenotype. The scope of this review is to provide applications and limitations of radiomics towards the development of clinical decision support systems for breast cancer diagnosis and prognosis.
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Mohamed RE, Zytoon HA, Amin MA. Diagnostic interplay of proton magnetic resonance spectroscopy and diffusion weighted images with apparent diffusion coefficient values in suspicious breast lesions. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2018. [DOI: 10.1016/j.ejrnm.2018.01.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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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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Abstract
Diffusion-weighted imaging (DWI) holds promise to address some of the shortcomings of routine clinical breast magnetic resonance imaging (MRI) and to expand the capabilities of imaging in breast cancer management. DWI reflects tissue microstructure, and provides unique information to aid in characterization of breast lesions. Potential benefits under investigation include improving diagnostic accuracy and guiding treatment decisions. As a result, DWI is increasingly being incorporated into breast MRI protocols and multicenter trials are underway to validate single-institution findings and to establish clinical guidelines. Advancements in DWI acquisition and modeling approaches are helping to improve image quality and extract additional biologic information from breast DWI scans, which may extend diagnostic and prognostic value.
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Affiliation(s)
- Savannah C Partridge
- *Department of Radiology, Breast Imaging Section, Seattle Cancer Care Alliance, University of Washington, Seattle, WA †University of Massachusetts Memorial Medical Center, Worcester, MA
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Takumi K, Fukukura Y, Hakamada H, Ideue J, Kumagae Y, Yoshiura T. Value of diffusion tensor imaging in differentiating malignant from benign parotid gland tumors. Eur J Radiol 2017; 95:249-256. [DOI: 10.1016/j.ejrad.2017.08.013] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Revised: 08/09/2017] [Accepted: 08/12/2017] [Indexed: 02/07/2023]
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19
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Furman‐Haran E, Nissan N, Ricart‐Selma V, Martinez‐Rubio C, Degani H, Camps‐Herrero J. Quantitative evaluation of breast cancer response to neoadjuvant chemotherapy by diffusion tensor imaging: Initial results. J Magn Reson Imaging 2017; 47:1080-1090. [DOI: 10.1002/jmri.25855] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Accepted: 08/25/2017] [Indexed: 12/31/2022] Open
Affiliation(s)
- Edna Furman‐Haran
- Weizmann Institute of Science, Department of Biological ServicesRehovot Israel
| | - Noam Nissan
- Sheba Medical Center, Radiology DepartmentTel Hashomer Israel
| | | | | | - Hadassa Degani
- Weizmann Institute of Science, Department of Biological RegulationRehovot Israel
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20
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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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21
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Wilmes LJ, Li W, Shin HJ, Newitt DC, Proctor E, Harnish R, Hylton NM. Diffusion Tensor Imaging for Assessment of Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer. ACTA ACUST UNITED AC 2016. [PMID: 29527574 PMCID: PMC5844277 DOI: 10.18383/j.tom.2016.00271] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
In this study, the prognostic significance of tumor metrics derived from diffusion tensor imaging (DTI) was evaluated in patients with locally advanced breast cancer undergoing neoadjuvant therapy. DTI and contrast-enhanced magnetic resonance imaging were acquired at 1.5 T in 34 patients before treatment and after 3 cycles of taxane-based therapy (early treatment). Tumor fractional anisotropy (FA), principal eigenvalues (λ1, λ2, and λ3), and apparent diffusion coefficient (ADC) were estimated for tumor regions of interest drawn on DTI data. The association between DTI metrics and final tumor volume change was evaluated with Spearman rank correlation. DTI metrics were investigated as predictors of pathological complete response (pCR) by calculating the area under the receiver operating characteristic curve (AUC). Early changes in tumor FA and ADC significantly correlated with final tumor volume change post therapy (ρ = -0.38, P = .03 and ρ = -0.71, P < .001, respectively). Pretreatment tumor ADC was significantly lower in the pCR than in the non-pCR group (P = .04). At early treatment, patients with pCR had significantly higher percent changes of tumor λ1, λ2, λ3, and ADC than those without pCR. The AUCs for early percent changes in tumor FA and ADC were 0.60 and 0.83, respectively. The early percent changes in tumor eigenvalues and ADC were the strongest DTI-derived predictors of pCR. Although early percent change in tumor FA had a weak association with pCR, the significant correlation with final tumor volume change suggests that this metric changes with therapy and may merit further evaluation.
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Affiliation(s)
- Lisa J Wilmes
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
| | - Wen Li
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
| | - Hee Jung Shin
- Department of Radiology and Research Institute of Radiology, Medical Imaging Laboratory, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - David C Newitt
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
| | - Evelyn Proctor
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
| | - Roy Harnish
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
| | - Nola M Hylton
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
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22
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Yamaguchi K, Nakazono T, Egashira R, Komori Y, Nakamura J, Noguchi T, Irie H. Diagnostic Performance of Diffusion Tensor Imaging with Readout-segmented Echo-planar Imaging for Invasive Breast Cancer: Correlation of ADC and FA with Pathological Prognostic Markers. Magn Reson Med Sci 2016; 16:245-252. [PMID: 27853053 PMCID: PMC5600032 DOI: 10.2463/mrms.mp.2016-0037] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Purpose: To assess the diagnostic performance of readout-segmented echo-planar diffusion tensor imaging (DTI based on rs-EPI) for breast cancer and to determine the correlation between the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values obtained from DTI based on rs-EPI with prognostic markers of invasive breast cancer. Materials and Methods: This retrospective study examined 80 pathologically proven breast lesions (22 benign and 58 malignant lesions) of 80 patients who underwent both diffusion-weighted imaging based on single-shot echo-planar imaging (DWI based on ss-EPI) and DTI based on rs-EPI with b-values of 0 and 1000. We identified and compared the diagnostic performances of the DWI based on ss-EPI and the DTI based on rs-EPI using ADCs by conducting a receiver-operating-characteristics (ROC) analysis. We determined the correlations between the ADCs and the prognostic markers and those of the FA values and the same markers. Results: The median ADCs of the benign and malignant lesions based on the ss-EPI were 1.57 and 1.2 × 10−3 mm2/sec, and those based on the rs-EPI were 1.53 and 1.09 × 10−3 mm2/sec, respectively. The area under the curve on the ROC analysis based on rs-EPI (0.924) was greater than that based on ss-EPI (0.897). There were no significant correlations between the ADCs and the prognostic markers, but there were significant correlations between the FA values and the estrogen receptor status, a proliferative marker, the nuclear grade and the intrinsic subtype. Conclusion: For breast cancer, DTI based on rs-EPI had superior diagnostic performance compared to DWI based on ss-EPI. Compared with the ADCs, the FA values were more closely correlated with prognostic markers of invasive breast cancer.
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Affiliation(s)
- Ken Yamaguchi
- Department of Radiology, Faculty of Medicine, Saga University
| | | | - Ryoko Egashira
- Department of Radiology, Faculty of Medicine, Saga University
| | | | - Jun Nakamura
- Department of Surgery, Faculty of Medicine, Saga University
| | - Tomoyuki Noguchi
- Department of Radiology, Faculty of Medicine, Saga University.,Department of Radiology, National Center for Global Health and Medicine (NCGM)
| | - Hiroyuki Irie
- Department of Radiology, Faculty of Medicine, Saga University
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23
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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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24
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Onaygil C, Kaya H, Ugurlu MU, Aribal E. Diagnostic performance of diffusion tensor imaging parameters in breast cancer and correlation with the prognostic factors. J Magn Reson Imaging 2016; 45:660-672. [DOI: 10.1002/jmri.25481] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2016] [Accepted: 08/30/2016] [Indexed: 11/11/2022] Open
Affiliation(s)
- Can Onaygil
- Oberlausitz-Kliniken gGmbH, Institute of Diagnostic and Interventional Radiology; Bautzen Germany
| | - Handan Kaya
- Marmara University School of Medicine, Department of Pathology; Pendik Istanbul Turkey
| | - Mustafa Umit Ugurlu
- Marmara University School of Medicine, Department of General Surgery; Pendik Istanbul Turkey
| | - Erkin Aribal
- Marmara University School of Medicine, Department of Radiology; Pendik Istanbul Turkey
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25
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Mirza SM, O’Brien J, Aitken J. Reliability of MRI in measuring the response to neoadjuvant chemotherapy in breast cancer patients and its therapeutic implications. BREAST CANCER MANAGEMENT 2016. [DOI: 10.2217/bmt-2016-0011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: Neoadjuvant chemotherapy (NAC) has recently been applied in treatment of operable breast cancers to enable breast conservation. We aimed to evaluate the accuracy of MRI in delineating residual tumor and pathological complete response (pCR). Patients & methods: 69 cases treated with NAC were monitored using breast MRI, findings were recorded and compared with histopathology. Results: MRI showed radiological complete response in 19 (27.5%), which correlated with pCR in 12 (63%) cases. However, five (7.3%) patients who achieved pCR were missed. Overall, the sensitivity was 70.6%, specificity 86.5%, positive predictive value 63.2% and negative predictive value of 90.0%. Conclusion: MRI showed promising results for evaluating response to NAC and predicting pCR, results need validation in larger trial.
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Affiliation(s)
- Shaukat Mahmood Mirza
- Department of Breast Surgery, Hinchingbrooke Hospital & NHS Trust, Huntingdon, Cambridgeshire, PE29 6NT, UK
| | - James O’Brien
- Department of Breast Surgery, Hinchingbrooke Hospital & NHS Trust, Huntingdon, Cambridgeshire, PE29 6NT, UK
| | - Jane Aitken
- Department of Breast Surgery, West Suffolk Hospital, NHS Foundation Trust, Bury St Edmunds, Suffolk, IP33 2QZ, UK
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26
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Yu J, Du Y, Lu Y, Zhang W, Zhang D, Wang G, Li C. Application of DTI and ARFI imaging in differential diagnosis of parotid tumours. Dentomaxillofac Radiol 2016; 45:20160100. [PMID: 27351345 DOI: 10.1259/dmfr.20160100] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
OBJECTIVES To explore the utility of diffusion tensor imaging (DTI) and acoustic radiation force impulse (ARFI) imaging in the diagnosis of parotid tumours. METHODS 51 patients with parotid tumours were examined with DTI on 3.0-T MRI and ARFI imaging on an ultrasound scanner before surgery. Values of apparent diffusion coefficient (ADC), fractional anisotropy (FA) and shear-wave velocity (SWV) were calculated and analyzed with independent samples Wilcoxon-Mann-Whitney test. Cut-off values, sensitivity and specificity were calculated with receiver-operating characteristic (ROC) curve analysis. The value of combination was calculated through parallel test for the cut-off value of ADC, FA and SWV (combination = 0 or 1); then, ROC analysis was performed with pathological results as the gold standard to calculate the sensitivity and specificity for the combination of the three parameters distinguishing benign and malignant parotid tumours. Pathological diagnosis for every patient was made post-operatively from the tumour tissue taken during operation. RESULTS There was a significant difference between benign and malignant tumours in the values of ADC, FA and SWV (p = 0.032, p = 0.011 and p < 0.0001); a significant difference in the values was also found between pleomorphic adenoma and malignant tumour (p = 0.0012, p < 0.0001 and p = 0.0002). The diagnosis cut-off points between benign and malignant tumours for ADC, FA and SWV were 1.02 × 10(-3) mm(2) s(-1), 0.24 and 2.76 m s(-1), respectively; the sensitivity for ADC, FA and SWV was 87.50, 62.50 and 68.75%; the specificity was 45.71, 82.86 and 97.14%. Analysis of the combination of the three parameters increased the sensitivity, specificity, Youden index and area under the ROC curve compared with analysis of each parameter alone for distinguishing benign and malignant tumours. CONCLUSIONS The diagnostic value of the combination of the three parameters for distinguishing benign and malignant parotid tumours is the best; SWV is the preferred indicator. Parameters of DTI and ARFI may reflect the histological characteristics of parotid tumours and predict benignancy and malignancy and could provide quantitative information about the tumour. Combination of DTI with ARFI imaging had obvious advantage for the diagnosis of parotid tumours than each alone.
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Affiliation(s)
- Jinfen Yu
- 1 Shandong Medical Imaging Research Institute, Shandong University, Jinan, Shandong, China.,2 Traditional Chinese Medical Hospital, Zhangqiu, Shandong, China
| | - Yanfei Du
- 3 Liaocheng People's Hospital, Liaocheng, Shandong, China
| | - Yong Lu
- 2 Traditional Chinese Medical Hospital, Zhangqiu, Shandong, China
| | - Weidong Zhang
- 4 Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Dongsheng Zhang
- 4 Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Guangbin Wang
- 1 Shandong Medical Imaging Research Institute, Shandong University, Jinan, Shandong, China
| | - Chuanting Li
- 1 Shandong Medical Imaging Research Institute, Shandong University, Jinan, Shandong, China
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27
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Jiang R, Ma Z, Dong H, Sun S, Zeng X, Li X. Diffusion tensor imaging of breast lesions: evaluation of apparent diffusion coefficient and fractional anisotropy and tissue cellularity. Br J Radiol 2016; 89:20160076. [PMID: 27302492 DOI: 10.1259/bjr.20160076] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE To investigate the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) measured by diffusion tensor imaging (DTI), tissue cellularity and their relationship in breast malignant/benign lesions. METHODS 88 patients with 88 breast lesions who underwent DTI and dynamic contrast-enhanced MR scanning between November 2013 and December 2014 were retrospectively analyzed. The diagnosis was confirmed pathologically. ADC and FA values as well as histopathological cellularity of different pathological types of lesions were analyzed and compared statistically. The Pearson's correlation between cellularity and ADC and FA was calculated. RESULTS There were 59 cases of breast cancer and 29 cases of benign lesions included in the study. ADC values of breast cancers were statistically lower than that of benign lesions (p < 0.001). FA and cellularity were higher in cancers than in benign lesions with statistical significance (p < 0.05 and p < 0.001, respectively). The mean FA values in the patients with invasive ductal carcinoma (IDC) were higher than that in the patients with ductal carcinoma in situ (DCIS) without statistical difference (p > 0.05). The ADC and the cellularity in the IDC of grade III were statistically lower (p < 0.05) and higher (p < 0.05) than that in the DCIS and IDC of grade I-II, respectively. ADC was negatively correlated to cellularity (r = -0.8319, p < 0.001) and FA was positively correlated to cellularity (r = 0.4231, p < 0.001). CONCLUSION ADC and FA values were statistically different between benign and malignant breast lesions and were significantly correlated to tissue cellularity. ADC and FA may help to discriminate malignant from benign breast lesions and to predict cellularity. ADC is helpful in the prediction of the grade of breast cancer. ADVANCES IN KNOWLEDGE ADC and FA values were statistically different between benign and malignant breast lesions and were significantly correlated to tissue cellularity.
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Affiliation(s)
- Ruisheng Jiang
- 1 Department of Computer Tomography and Magnetic Resonance Imaging, Weifang Medical College Affiliated Yidu Central Hospital, Weifang, China
| | - Zhijun Ma
- 1 Department of Computer Tomography and Magnetic Resonance Imaging, Weifang Medical College Affiliated Yidu Central Hospital, Weifang, China
| | - Haixia Dong
- 1 Department of Computer Tomography and Magnetic Resonance Imaging, Weifang Medical College Affiliated Yidu Central Hospital, Weifang, China
| | - Shihang Sun
- 1 Department of Computer Tomography and Magnetic Resonance Imaging, Weifang Medical College Affiliated Yidu Central Hospital, Weifang, China
| | - Xiangmin Zeng
- 1 Department of Computer Tomography and Magnetic Resonance Imaging, Weifang Medical College Affiliated Yidu Central Hospital, Weifang, China
| | - Xiao Li
- 2 Medical Imaging Center, Linyi People's Hospital, Linyi, China
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28
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Jiang R, Zeng X, Sun S, Ma Z, Wang X. Assessing Detection, Discrimination, and Risk of Breast Cancer According to Anisotropy Parameters of Diffusion Tensor Imaging. Med Sci Monit 2016; 22:1318-28. [PMID: 27094307 PMCID: PMC4841361 DOI: 10.12659/msm.895755] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND The aim of this study was to investigate whether the anisotropy parameters are helpful in the detection and discrimination of breast cancers, and to determine its value in predicting the risk of cancers. MATERIAL AND METHODS There were 56 patients with 56 lesions (34 malignant, 22 benign) included in the study. DTI was performed in every patient and apparent diffusion coefficient (ADC), fractional anisotropy (FA), and eigenvalues E1, E2, and E3 were measured in every lesion and the normal breast tissue. RESULTS ADC, FA, and eigenvalues of E1, E2, E3, and E1-E3 in breast cancers were all significantly lower than in normal tissue (P<0.001 for all) with mean reduction of (32 ± 17)%, (24 ± 13)%, (33 ± 19)%, (32 ± 17)%, (31 ± 18)%, and (37 ± 20)% for ADC, FA, E1, E2, E3, and E1-E3, respectively. These parameters were also statistically lower in cancers than in benign lesions (P<0.01 for all), except FA (P>0.05). ADC, E1, E2, and E3 were very similar in discriminating breast cancers and benign lesions, with area under the curve (AUC) 0.885-0.898, sensitivity 73.5-85.3%, and specificity 90.9-100%. CONCLUSIONS ADC, E1, E2, E3, and E1-E3 are much lower in breast cancers than in normal tissue and benign lesions. The reduction of ADC, E1, E2, E3, and E1-E3 of a mass in the breast is highly associated with the risk of breast cancer, but the FA has no utility in breast cancer risk prediction.
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Affiliation(s)
- Ruisheng Jiang
- Diagnostic Room of Computer Tomography, Shandong Medical Imaging Research Institute, Shandong University, Jinan, Shandong, China (mainland)
| | - Xiangmin Zeng
- Department of Computer Tomography and Magnetic Resonance Imaging, Weifang Medical College Affiliated Yidu Central Hospital, Qingzhou, Shandong, China (mainland)
| | - Shihang Sun
- Department of Computer Tomography and Magnetic Resonance Imaging, Weifang Medical College Affiliated Yidu Central Hospital, Qingzhou, Shandong, China (mainland)
| | - Zhijun Ma
- Department of Computer Tomography and Magnetic Resonance Imaging, Weifang Medical College Affiliated Yidu Central Hospital, Qingzhou, Shandong, China (mainland)
| | - Ximing Wang
- Diagnostic Room of Computer Tomography, Shandong Medical Imaging Research Institute, Shandong University, Jinan, Shandong, China (mainland)
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29
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Furman-Haran E, Grobgeld D, Nissan N, Shapiro-Feinberg M, Degani H. Can diffusion tensor anisotropy indices assist in breast cancer detection? J Magn Reson Imaging 2016; 44:1624-1632. [DOI: 10.1002/jmri.25292] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2016] [Accepted: 04/06/2016] [Indexed: 12/21/2022] Open
Affiliation(s)
- Edna Furman-Haran
- Departmentof Biological Services; Weizmann Institute of Science; Rehovot Israel
| | - Dov Grobgeld
- Department of Biological Regulation; Weizmann Institute of Science; Rehovot Israel
| | - Noam Nissan
- Department of Biological Regulation; Weizmann Institute of Science; Rehovot Israel
| | | | - Hadassa Degani
- Department of Biological Regulation; Weizmann Institute of Science; Rehovot Israel
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30
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El Fiki IM, Abdel-Rahman HM, Morsy MM. Assessment of breast mass: Utility of diffusion-weighted MR and MR spectroscopy imaging. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2015. [DOI: 10.1016/j.ejrnm.2015.08.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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31
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Teama AH, Hassanien OA, Hashish AAE, Shaarawy HA. The role of conventional and functional MRI in diagnosis of breast masses. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2015. [DOI: 10.1016/j.ejrnm.2015.05.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
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32
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Nissan N. The usefulness of diffusion-tensor imaging for the differential diagnosis of breast lesions. Acta Radiol 2015; 56:NP43-4. [PMID: 26475310 DOI: 10.1177/0284185115600917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Noam Nissan
- Department of Biological Regulation Weizmann Institute of Science. PO Box 26, Rehovot 76100, Israel
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33
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Tsougos I. Reply to: The usefulness of diffusion-tensor imaging for the differential diagnosis of breast lesions. Acta Radiol 2015; 56:NP45. [PMID: 26475311 DOI: 10.1177/0284185115603067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Ioannis Tsougos
- Assistant Professor of Medical Physics, Medical School, University of Thessaly Biopolis, Larissa, Greece
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34
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35
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Alcantara D, Leal MP, García-Bocanegra I, García-Martín ML. Molecular imaging of breast cancer: present and future directions. Front Chem 2014; 2:112. [PMID: 25566530 PMCID: PMC4270251 DOI: 10.3389/fchem.2014.00112] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2014] [Accepted: 12/01/2014] [Indexed: 12/21/2022] Open
Abstract
Medical imaging technologies have undergone explosive growth over the past few decades and now play a central role in clinical oncology. But the truly transformative power of imaging in the clinical management of cancer patients lies ahead. Today, imaging is at a crossroads, with molecularly targeted imaging agents expected to broadly expand the capabilities of conventional anatomical imaging methods. Molecular imaging will allow clinicians to not only see where a tumor is located in the body, but also to visualize the expression and activity of specific molecules (e.g., proteases and protein kinases) and biological processes (e.g., apoptosis, angiogenesis, and metastasis) that influence tumor behavior and/or response to therapy. Breast cancer, the most common cancer among women and a research area where our group is actively involved, is a very heterogeneous disease with diverse patterns of development and response to treatment. Hence, molecular imaging is expected to have a major impact on this type of cancer, leading to important improvements in diagnosis, individualized treatment, and drug development, as well as our understanding of how breast cancer arises.
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Affiliation(s)
- David Alcantara
- Laboratory of Metabolomics and Molecular Imaging, BIONAND, Centro Andaluz de Nanomedicina y Biotecnología (Junta de Andalucía, Universidad de Málaga) Malaga, Spain
| | - Manuel Pernia Leal
- Laboratory of Metabolomics and Molecular Imaging, BIONAND, Centro Andaluz de Nanomedicina y Biotecnología (Junta de Andalucía, Universidad de Málaga) Malaga, Spain
| | - Irene García-Bocanegra
- Laboratory of Metabolomics and Molecular Imaging, BIONAND, Centro Andaluz de Nanomedicina y Biotecnología (Junta de Andalucía, Universidad de Málaga) Malaga, Spain
| | - Maria L García-Martín
- Laboratory of Metabolomics and Molecular Imaging, BIONAND, Centro Andaluz de Nanomedicina y Biotecnología (Junta de Andalucía, Universidad de Málaga) Malaga, Spain
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36
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Nissan N, Furman-Haran E, Feinberg-Shapiro M, Grobgeld D, Eyal E, Zehavi T, Degani H. Tracking the mammary architectural features and detecting breast cancer with magnetic resonance diffusion tensor imaging. J Vis Exp 2014:52048. [PMID: 25549209 PMCID: PMC4396944 DOI: 10.3791/52048] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI). The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices. The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection.
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Affiliation(s)
- Noam Nissan
- Department of Biological Regulation, Weizmann Institute of Science
| | | | | | - Dov Grobgeld
- Department of Biological Regulation, Weizmann Institute of Science
| | - Erez Eyal
- Department of Biological Regulation, Weizmann Institute of Science
| | | | - Hadassa Degani
- Department of Biological Regulation, Weizmann Institute of Science;
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Li L, Margolis DJA, Deng M, Cai J, Yuan L, Feng Z, Min X, Hu Z, Hu D, Liu J, Wang L. Correlation of gleason scores with magnetic resonance diffusion tensor imaging in peripheral zone prostate cancer. J Magn Reson Imaging 2014; 42:460-7. [PMID: 25469909 DOI: 10.1002/jmri.24813] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2014] [Accepted: 11/10/2014] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND To investigate tumor aggressiveness in peripheral zone prostate cancer (PCa) by correlating Gleason score (GS) with diffusion tensor imaging (DTI) from multiparametric magnetic resonance imaging (MRI) at 3.0 Tesla (T). METHODS Eighty-three patients with pathological proven peripheral zone PCa whose GS in at least one core biopsy met the criteria(GS ≤3+3, GS 3+4, GS 4+3, or GS ≥4+4) were included in this study. DTI was performed using b values of 0 and 800 s/mm(2) with 32 directions in all patients on a 3.0T MRI scanner. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were calculated from the DTI data of patients with the previously mentioned four categories of Gleason scores. An association between DTI measurements(FA, ADC) and GS was tested using the Spearman rank correlation analysis. RESULTS FA values in the sextants found to harbor cancer were positively correlated with the GS(r = 0.48; P < 0.001), while the ADC values were negatively correlated with GS(r = -0.54; P < 0.001). Statistical significance(P < 0.05) was found for FA values among different GS groups, with the exception of GS 3+4 versus GS 4+3 (P = 0.105). The differences between the ADC values were statistically significant for all four different scores(all P < 0.05). CONCLUSION Quantitative DTI at 3.0T MRI shows a significant association with GS in the evaluation of tumor aggressiveness in peripheral zone PCa, which may be useful to ensure concordance of biopsy results and therefore make the appropriate decision in the management of patients with PCa.
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Affiliation(s)
- Liang Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Daniel J A Margolis
- Department of Radiology, David Geffen School of Medicine at UCLA, Ronald Reagan UCLA Medical Center, Los Angeles, California, USA
| | - Ming Deng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jie Cai
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ling Yuan
- Institute of Pathology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhaoyan Feng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiangde Min
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhiquan Hu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Daoyu Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jihong Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Liang Wang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Menezes GLG, Knuttel FM, Stehouwer BL, Pijnappel RM, van den Bosch MAAJ. Magnetic resonance imaging in breast cancer: A literature review and future perspectives. World J Clin Oncol 2014; 5:61-70. [PMID: 24829852 PMCID: PMC4014797 DOI: 10.5306/wjco.v5.i2.61] [Citation(s) in RCA: 93] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2014] [Revised: 03/18/2014] [Accepted: 04/17/2014] [Indexed: 02/06/2023] Open
Abstract
Early detection and diagnosis of breast cancer are essential for successful treatment. Currently mammography and ultrasound are the basic imaging techniques for the detection and localization of breast tumors. The low sensitivity and specificity of these imaging tools resulted in a demand for new imaging modalities and breast magnetic resonance imaging (MRI) has become increasingly important in the detection and delineation of breast cancer in daily practice. However, the clinical benefits of the use of pre-operative MRI in women with newly diagnosed breast cancer is still a matter of debate. The main additional diagnostic value of MRI relies on specific situations such as detecting multifocal, multicentric or contralateral disease unrecognized on conventional assessment (particularly in patients diagnosed with invasive lobular carcinoma), assessing the response to neoadjuvant chemotherapy, detection of cancer in dense breast tissue, recognition of an occult primary breast cancer in patients presenting with cancer metastasis in axillary lymph nodes, among others. Nevertheless, the development of new MRI technologies such as diffusion-weighted imaging, proton spectroscopy and higher field strength 7.0 T imaging offer a new perspective in providing additional information in breast abnormalities. We conducted an expert literature review on the value of breast MRI in diagnosing and staging breast cancer, as well as the future potentials of new MRI technologies.
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