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Kratochvíla J, Jiřík R, Bartoš M, Standara M, Starčuk Z, Taxt T. Blind deconvolution decreases requirements on temporal resolution of DCE-MRI: Application to 2nd generation pharmacokinetic modeling. Magn Reson Imaging 2024; 109:238-248. [PMID: 38508292 DOI: 10.1016/j.mri.2024.03.019] [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: 08/07/2023] [Revised: 03/08/2024] [Accepted: 03/16/2024] [Indexed: 03/22/2024]
Abstract
PURPOSE Dynamic Contrast-Enhanced (DCE) MRI with 2nd generation pharmacokinetic models provides estimates of plasma flow and permeability surface-area product in contrast to the broadly used 1st generation models (e.g. the Tofts models). However, the use of 2nd generation models requires higher frequency with which the dynamic images are acquired (around 1.5 s per image). Blind deconvolution can decrease the demands on temporal resolution as shown previously for one of the 1st generation models. Here, the temporal-resolution requirements achievable for blind deconvolution with a 2nd generation model are studied. METHODS The 2nd generation model is formulated as the distributed-capillary adiabatic-tissue-homogeneity (DCATH) model. Blind deconvolution is based on Parker's model of the arterial input function. The accuracy and precision of the estimated arterial input functions and the perfusion parameters is evaluated on synthetic and real clinical datasets with different levels of the temporal resolution. RESULTS The estimated arterial input functions remained unchanged from their reference high-temporal-resolution estimates (obtained with the sampling interval around 1 s) when increasing the sampling interval up to about 5 s for synthetic data and up to 3.6-4.8 s for real data. Further increasing of the sampling intervals led to systematic distortions, such as lowering and broadening of the 1st pass peak. The resulting perfusion-parameter estimation error was below 10% for the sampling intervals up to 3 s (synthetic data), in line with the real data perfusion-parameter boxplots which remained unchanged up to the sampling interval 3.6 s. CONCLUSION We show that use of blind deconvolution decreases the demands on temporal resolution in DCE-MRI from about 1.5 s (in case of measured arterial input functions) to 3-4 s. This can be exploited in increased spatial resolution or larger organ coverage.
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Affiliation(s)
- Jiří Kratochvíla
- Czech Academy of Sciences, Institute of Scientific Instruments, Královopolská 147, 612 64 Brno, Czech Republic.
| | - Radovan Jiřík
- Czech Academy of Sciences, Institute of Scientific Instruments, Královopolská 147, 612 64 Brno, Czech Republic
| | - Michal Bartoš
- Czech Academy of Sciences, Institute of Information Technology and Automation, Pod Vodárenskou věží 4, 182 08 Praha 8, Czech Republic
| | - Michal Standara
- Department of Radiology, Masaryk Memorial Cancer Institute, Žlutý kopec 7, 656 53 Brno, Czech Republic
| | - Zenon Starčuk
- Czech Academy of Sciences, Institute of Scientific Instruments, Královopolská 147, 612 64 Brno, Czech Republic
| | - Torfinn Taxt
- Department of Biomedicine, University of Bergen, Jonas Lies vei 91, Bergen, Norway
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Dietzel M, Baltzer PAT. How to use the Kaiser score as a clinical decision rule for diagnosis in multiparametric breast MRI: a pictorial essay. Insights Imaging 2018; 9:325-335. [PMID: 29616496 PMCID: PMC5990997 DOI: 10.1007/s13244-018-0611-8] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2018] [Revised: 02/02/2018] [Accepted: 02/13/2018] [Indexed: 12/13/2022] Open
Abstract
Due to its superior sensitivity, breast MRI (bMRI) has been established as an important additional diagnostic tool in the breast clinic and is used for screening in patients with an elevated risk for breast cancer. Breast MRI, however, is a complex tool, providing multiple images containing several contrasts. Thus, reading bMRI requires a structured approach. A lack of structure will increase the rate of false-positive findings and sacrifice most of the advantages of bMRI as additional work-up will be required. While the BI-RADS (Breast Imaging Reporting And Data System) lexicon is a major step toward standardised and structured reporting, it does not provide a clinical decision rule with which to guide diagnostic decisions. Such a clinical decision rule, however, is provided by the Kaiser score, which combines five independent diagnostic BI-RADS lexicon criteria (margins, SI-time curve type, internal enhancement and presence of oedema) in an intuitive flowchart. The resulting score provides probabilities of malignancy that can be used for evidence-based decision-making in the breast clinic. Notably, considerable benefits have been demonstrated for radiologists with initial and intermediate experience in bMRI. This pictorial essay is a practical guide to the application of the Kaiser score in the interpretation of breast MRI examinations. TEACHING POINTS • bMRI requires standardisation of patient-management, protocols, and reading set-up. • Reading bMRI includes the assessment of breast parenchyma, associated findings, and lesions. • Diagnostic decisions should be made according to evidence-based clinical decision rules. • The evidence-based Kaiser score is applicable independent of bMRI protocol and scanner. • The Kaiser score provides high diagnostic accuracy with low inter-observer variability.
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Affiliation(s)
- Matthias Dietzel
- Department of Radiology, University Hospital Erlangen-Nürnberg, Maximiliansplatz 1, 91054, Erlangen, Germany
| | - Pascal A T Baltzer
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Waehringer-Guertel, 18-20, Vienna, Austria.
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Xu T, Zhang L, Xu H, Kang S, Xu Y, Luo X, Hua T, Tang G. Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis. Oncotarget 2017; 8:114360-114370. [PMID: 29371992 PMCID: PMC5768409 DOI: 10.18632/oncotarget.22267] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 07/26/2017] [Indexed: 12/17/2022] Open
Abstract
Purpose This study aimed to evaluate the difference of mass in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) characteristics between low-risk and non-low-risk breast cancers and to explore the possible pathological basis. Materials and Methods Approval from the institutional review board and informed consent were acquired for this study. The MR images of 104 patients with pathologically proven breast cancer (104 lesions) were prospectively analyzed. All of included patients were Chinese woman. The DCE-MRI morphologic findings, apparent diffusion coefficient (ADC) values, quantitative DCE-MRI parameters, and pathological biomarkers between the two subtypes of breast cancer were compared. The quantitative DCE-MRI parameters and ADC values were added to the morphologic features in multivariate models to evaluate diagnostic performance in predicting low-risk breast cancer. The values were further subjected to the receiver operating characteristic (ROC) curve analysis. Results Low-risk tumors showed significantly lower Ktrans and Kepvalues (t = 2.065, P = 0.043 and t = 3.548, P = 0.001, respectively) and higher ADC value (t = 4.713, P = 0.000) than non-low-risk breast cancers. Our results revealed no significant differences in clinic data and conventional imaging findings between the two breast cancer subtypes. Adding the quantitative DCE-MRI parameters and ADC values to conventional MRI improved the diagnostic performance of MRI: The area under the ROC improved from 0.63 to 0.91. Low-risk breast cancers showed significantly lower matrix metalloproteinase (MMP)-2 expression (P = 0.000), lower MMP-9 expression (P = 0.001), and lower microvessel density (MVD) values (P = 0.008) compared with non-low-risk breast cancers. Ktrans and Kep values were positively correlated with pathological biomarkers. The ADC value showed a significant inverse correlation with pathological biomarkers. Conclusions The prediction parameter using Ktrans, Kep, and ADC obtained on DCE-MRI and diffusion-weighted imaging could facilitate the identification of low-risk breast cancers. Decreased biological factors, including MVD, vascular endothelial growth factor, MMP-2, and MMP-9, may explain the possible pathological basis.
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Affiliation(s)
- Tingting Xu
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Lin Zhang
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Hong Xu
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Sifeng Kang
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Yali Xu
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Xiaoyu Luo
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Ting Hua
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Guangyu Tang
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
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Prediction of low-risk breast cancer using perfusion parameters and apparent diffusion coefficient. Magn Reson Imaging 2016; 34:67-74. [DOI: 10.1016/j.mri.2015.10.028] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2015] [Accepted: 10/21/2015] [Indexed: 11/20/2022]
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Singanamalli A, Rusu M, Sparks RE, Shih NNC, Ziober A, Wang LP, Tomaszewski J, Rosen M, Feldman M, Madabhushi A. Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer. J Magn Reson Imaging 2015; 43:149-58. [PMID: 26110513 DOI: 10.1002/jmri.24975] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2014] [Accepted: 05/29/2015] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND To identify computer extracted in vivo dynamic contrast enhanced (DCE) MRI markers associated with quantitative histomorphometric (QH) characteristics of microvessels and Gleason scores (GS) in prostate cancer. METHODS This study considered retrospective data from 23 biopsy confirmed prostate cancer patients who underwent 3 Tesla multiparametric MRI before radical prostatectomy (RP). Representative slices from RP specimens were stained with vascular marker CD31. Tumor extent was mapped from RP sections onto DCE MRI using nonlinear registration methods. Seventy-seven microvessel QH features and 18 DCE MRI kinetic features were extracted and evaluated for their ability to distinguish low from intermediate and high GS. The effect of temporal sampling on kinetic features was assessed and correlations between those robust to temporal resolution and microvessel features discriminative of GS were examined. RESULTS A total of 12 microvessel architectural features were discriminative of low and intermediate/high grade tumors with area under the receiver operating characteristic curve (AUC) > 0.7. These features were most highly correlated with mean washout gradient (WG) (max rho = -0.62). Independent analysis revealed WG to be moderately robust to temporal resolution (intraclass correlation coefficient [ICC] = 0.63) and WG variance, which was poorly correlated with microvessel features, to be predictive of low grade tumors (AUC = 0.77). Enhancement ratio was the most robust (ICC = 0.96) and discriminative (AUC = 0.78) kinetic feature but was moderately correlated with microvessel features (max rho = -0.52). CONCLUSION Computer extracted features of prostate DCE MRI appear to be correlated with microvessel architecture and may be discriminative of low versus intermediate and high GS.
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Affiliation(s)
- Asha Singanamalli
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Mirabela Rusu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Rachel E Sparks
- Centre for Medical Image Computing, University College of London, London, United Kingdom
| | - Natalie N C Shih
- Department of Pathology & Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Amy Ziober
- Department of Pathology & Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Li-Ping Wang
- Department of Pathology & Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John Tomaszewski
- Department of Pathology & Anatomical Sciences, University of Buffalo, Buffalo, New York, USA
| | - Mark Rosen
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Michael Feldman
- Department of Pathology & Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Anant Madabhushi
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
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Kratochvíla J, Jiřík R, Bartoš M, Standara M, Starčuk Z, Taxt T. Distributed capillary adiabatic tissue homogeneity model in parametric multi-channel blind AIF estimation using DCE-MRI. Magn Reson Med 2015; 75:1355-65. [PMID: 25865576 DOI: 10.1002/mrm.25619] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2014] [Revised: 12/01/2014] [Accepted: 12/24/2014] [Indexed: 12/21/2022]
Abstract
PURPOSE One of the main challenges in quantitative dynamic contrast-enhanced (DCE) MRI is estimation of the arterial input function (AIF). Usually, the signal from a single artery (ignoring contrast dispersion, partial volume effects and flow artifacts) or a population average of such signals (also ignoring variability between patients) is used. METHODS Multi-channel blind deconvolution is an alternative approach avoiding most of these problems. The AIF is estimated directly from the measured tracer concentration curves in several tissues. This contribution extends the published methods of multi-channel blind deconvolution by applying a more realistic model of the impulse residue function, the distributed capillary adiabatic tissue homogeneity model (DCATH). In addition, an alternative AIF model is used and several AIF-scaling methods are tested. RESULTS The proposed method is evaluated on synthetic data with respect to the number of tissue regions and to the signal-to-noise ratio. Evaluation on clinical data (renal cell carcinoma patients before and after the beginning of the treatment) gave consistent results. An initial evaluation on clinical data indicates more reliable and less noise sensitive perfusion parameter estimates. CONCLUSION Blind multi-channel deconvolution using the DCATH model might be a method of choice for AIF estimation in a clinical setup.
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Affiliation(s)
- Jiří Kratochvíla
- Department of Biomedical Engineering, Brno University of Technology, Brno, Czech Republic.,Institute of Scientific Instruments of the Academy of Sciences of the Czech Republic, Brno, Czech Republic
| | - Radovan Jiřík
- Institute of Scientific Instruments of the Academy of Sciences of the Czech Republic, Brno, Czech Republic
| | - Michal Bartoš
- Department of Biomedical Engineering, Brno University of Technology, Brno, Czech Republic.,Institute of Information Technology and Automation of the Academy of Sciences of the Czech Republic, Praha, Czech Republic
| | | | - Zenon Starčuk
- Institute of Scientific Instruments of the Academy of Sciences of the Czech Republic, Brno, Czech Republic
| | - Torfinn Taxt
- Department of Biomedicine, University of Bergen, Bergen, Norway
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Chen B, Zhang Y, Song X, Wang X, Zhang J, Fang J. Quantitative estimation of renal function with dynamic contrast-enhanced MRI using a modified two-compartment model. PLoS One 2014; 9:e105087. [PMID: 25141138 PMCID: PMC4139329 DOI: 10.1371/journal.pone.0105087] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2014] [Accepted: 07/19/2014] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVE To establish a simple two-compartment model for glomerular filtration rate (GFR) and renal plasma flow (RPF) estimations by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). MATERIALS AND METHODS A total of eight New Zealand white rabbits were included in DCE-MRI. The two-compartment model was modified with the impulse residue function in this study. First, the reliability of GFR measurement of the proposed model was compared with other published models in Monte Carlo simulation at different noise levels. Then, functional parameters were estimated in six healthy rabbits to test the feasibility of the new model. Moreover, in order to investigate its validity of GFR estimation, two rabbits underwent acute ischemia surgical procedure in unilateral kidney before DCE-MRI, and pixel-wise measurements were implemented to detect the cortical GFR alterations between normal and abnormal kidneys. RESULTS The lowest variability of GFR and RPF measurements were found in the proposed model in the comparison. Mean GFR was 3.03±1.1 ml/min and mean RPF was 2.64±0.5 ml/g/min in normal animals, which were in good agreement with the published values. Moreover, large GFR decline was found in dysfunction kidneys comparing to the contralateral control group. CONCLUSION Results in our study demonstrate that measurement of renal kinetic parameters based on the proposed model is feasible and it has the ability to discriminate GFR changes in healthy and diseased kidneys.
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Affiliation(s)
- Bin Chen
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Yudong Zhang
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - Xiaojian Song
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Department of Electrical Engineering, Chengdu University of Information Technology, Chengdu, Sichuan, China
| | - Xiaoying Wang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Department of Radiology, Peking University First Hospital, Beijing, China
- * E-mail: (XW); (JZ)
| | - Jue Zhang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- College of Engineering, Peking University, Beijing, China
- * E-mail: (XW); (JZ)
| | - Jing Fang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- College of Engineering, Peking University, Beijing, China
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Yi B, Kang DK, Yoon D, Jung YS, Kim KS, Yim H, Kim TH. Is there any correlation between model-based perfusion parameters and model-free parameters of time-signal intensity curve on dynamic contrast enhanced MRI in breast cancer patients? Eur Radiol 2014; 24:1089-96. [PMID: 24553785 DOI: 10.1007/s00330-014-3100-6] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2013] [Revised: 12/19/2013] [Accepted: 01/15/2014] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To find out any correlation between dynamic contrast-enhanced (DCE) model-based parameters and model-free parameters, and evaluate correlations between perfusion parameters with histologic prognostic factors. METHODS Model-based parameters (Ktrans, Kep and Ve) of 102 invasive ductal carcinomas were obtained using DCE-MRI and post-processing software. Correlations between model-based and model-free parameters and between perfusion parameters and histologic prognostic factors were analysed. RESULTS Mean Kep was significantly higher in cancers showing initial rapid enhancement (P = 0.002) and a delayed washout pattern (P = 0.001). Ve was significantly lower in cancers showing a delayed washout pattern (P = 0.015). Kep significantly correlated with time to peak enhancement (TTP) (ρ = -0.33, P < 0.001) and washout slope (ρ = 0.39, P = 0.002). Ve was significantly correlated with TTP (ρ = 0.33, P = 0.002). Mean Kep was higher in tumours with high nuclear grade (P = 0.017). Mean Ve was lower in tumours with high histologic grade (P = 0.005) and in tumours with negative oestrogen receptor status (P = 0.047). TTP was shorter in tumours with negative oestrogen receptor status (P = 0.037). CONCLUSIONS We could acquire general information about the tumour vascular physiology, interstitial space volume and pathologic prognostic factors by analyzing time-signal intensity curve without a complicated acquisition process for the model-based parameters. KEY POINTS • Kep mainly affected the initial and delayed curve pattern in time-signal intensity curve. • There is significant correlation between model-based and model-free parameters. • We acquired information about tumour vascular physiology, interstitial space volume and prognostic factors.
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Affiliation(s)
- Boram Yi
- Department of Radiology, Ajou University School of Medicine, San 5, Woncheon-dong, Yongtong-gu, Suwon, Gyeonggi-do, 442-749, South Korea
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Furman-Haran E, Feinberg MS, Badikhi D, Eyal E, Zehavi T, Degani H. Standardization of radiological evaluation of dynamic contrast enhanced MRI: application in breast cancer diagnosis. Technol Cancer Res Treat 2013; 13:445-54. [PMID: 24000989 PMCID: PMC4527468 DOI: 10.7785/tcrtexpress.2013.600263] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Dynamic contrast enhanced MRI is applied as an adjuvant tool for breast cancer detection, diagnosis, and follow-up of therapy. Despite improvements through the years in achieving higher spatial and temporal resolution, it still suffers from lack of scanning and processing standardization, and consequently, high variability in the radiological evaluation, particularly differentiating malignant from benign lesions. We describe here a hybrid method for achieving standardization of the radiological evaluation of breast dynamic contrast enhanced (DCE)-magnetic resonance imaging (MRI) protocols, based on integrating the model based three time point (3TP) method with principal component analysis (PCA). The scanning and image processing procedures consisted of three main steps: 1. 3TP standardization of the MRI acquisition parameters according to a kinetic model, 2. Applying PCA to test cases and constructing an eigenvectors' base related to the contrast-enhancement kinetics and 3. Projecting all new cases on the eigenvectors' base and evaluating the clinical outcome. Datasets of overall 96 malignant and 26 benign breast lesions were recorded on 1.5T and 3T scanners, using three different MRI acquisition parameters optimized by the 3TP method. The final radiological evaluation showed similar detection and diagnostic ability for the three different MRI acquisition parameters. The area under the curve of receiver operating characteristic analysis yielded a value of 0.88 ± 0.034 for differentiating malignant from benign lesions. This 3TP + PCA hybrid method is fast and can be readily applied as a computer aided diagnostic tool of breast cancer. The underlying principles of this method can be extended to standardize the evaluation of malignancies in other organs.
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