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Zhang X, Qiu Y, Jiang W, Yang Z, Wang M, Li Q, Liu Y, Yan X, Yang G, Shen J. Mean Apparent Propagator MRI: Quantitative Assessment of Tumor-Stroma Ratio in Invasive Ductal Breast Carcinoma. Radiol Imaging Cancer 2024; 6:e230165. [PMID: 38874529 PMCID: PMC11287226 DOI: 10.1148/rycan.230165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 04/07/2024] [Accepted: 05/13/2024] [Indexed: 06/15/2024]
Abstract
Purpose To determine whether metrics from mean apparent propagator (MAP) MRI perform better than apparent diffusion coefficient (ADC) value in assessing the tumor-stroma ratio (TSR) status in breast carcinoma. Materials and Methods From August 2021 to October 2022, 271 participants were prospectively enrolled (ClinicalTrials.gov identifier: NCT05159323) and underwent breast diffusion spectral imaging and diffusion-weighted imaging. MAP MRI metrics and ADC were derived from the diffusion MRI data. All participants were divided into high-TSR (stromal component < 50%) and low-TSR (stromal component ≥ 50%) groups based on pathologic examination. Clinicopathologic characteristics were collected, and MRI findings were assessed. Logistic regression was used to determine the independent variables for distinguishing TSR status. The area under the receiver operating characteristic curve (AUC) and sensitivity, specificity, and accuracy were compared between the MAP MRI metrics, either alone or combined with clinicopathologic characteristics, and ADC, using the DeLong and McNemar test. Results A total of 181 female participants (mean age, 49 years ± 10 [SD]) were included. All diffusion MRI metrics differed between the high-TSR and low-TSR groups (P < .001 to P = .01). Radial non-Gaussianity from MAP MRI and lymphovascular invasion were significant independent variables for discriminating the two groups, with a higher AUC (0.81 [95% CI: 0.74, 0.87] vs 0.61 [95% CI: 0.53, 0.68], P < .001) and accuracy (138 of 181 [76%] vs 106 of 181 [59%], P < .001) than that of the ADC. Conclusion MAP MRI may serve as a better approach than conventional diffusion-weighted imaging in evaluating the TSR of breast carcinoma. Keywords: MR Diffusion-weighted Imaging, MR Imaging, Breast, Oncology ClinicalTrials.gov Identifier: NCT05159323 Supplemental material is available for this article. © RSNA, 2024.
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Affiliation(s)
| | | | - Wei Jiang
- From the Department of Radiology (X.Z., Y.Q., W.J., Z.Y., J.S.),
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene
Regulation, Medical Research Center (X.Z., Y.Q., W.J., Z.Y., Q.L., Y.L., J.S.),
and Department of Pathology (Q.L., Y.L.), Sun Yat-Sen Memorial Hospital, Sun
Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou 510120,
People’s Republic of China; Department of Radiology, the First
People’s Hospital of Kashi Prefecture, Kashi, People’s Republic of
China (Y.Q.); Department of MR Scientific Marketing, Siemens Healthineers,
Guangzhou, People’s Republic of China (M.W., X.Y.); and Shanghai Key
Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East
China Normal University, Shanghai, People’s Republic of China
(G.Y.)
| | - Zehong Yang
- From the Department of Radiology (X.Z., Y.Q., W.J., Z.Y., J.S.),
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene
Regulation, Medical Research Center (X.Z., Y.Q., W.J., Z.Y., Q.L., Y.L., J.S.),
and Department of Pathology (Q.L., Y.L.), Sun Yat-Sen Memorial Hospital, Sun
Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou 510120,
People’s Republic of China; Department of Radiology, the First
People’s Hospital of Kashi Prefecture, Kashi, People’s Republic of
China (Y.Q.); Department of MR Scientific Marketing, Siemens Healthineers,
Guangzhou, People’s Republic of China (M.W., X.Y.); and Shanghai Key
Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East
China Normal University, Shanghai, People’s Republic of China
(G.Y.)
| | - Mengzhu Wang
- From the Department of Radiology (X.Z., Y.Q., W.J., Z.Y., J.S.),
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene
Regulation, Medical Research Center (X.Z., Y.Q., W.J., Z.Y., Q.L., Y.L., J.S.),
and Department of Pathology (Q.L., Y.L.), Sun Yat-Sen Memorial Hospital, Sun
Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou 510120,
People’s Republic of China; Department of Radiology, the First
People’s Hospital of Kashi Prefecture, Kashi, People’s Republic of
China (Y.Q.); Department of MR Scientific Marketing, Siemens Healthineers,
Guangzhou, People’s Republic of China (M.W., X.Y.); and Shanghai Key
Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East
China Normal University, Shanghai, People’s Republic of China
(G.Y.)
| | - Qin Li
- From the Department of Radiology (X.Z., Y.Q., W.J., Z.Y., J.S.),
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene
Regulation, Medical Research Center (X.Z., Y.Q., W.J., Z.Y., Q.L., Y.L., J.S.),
and Department of Pathology (Q.L., Y.L.), Sun Yat-Sen Memorial Hospital, Sun
Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou 510120,
People’s Republic of China; Department of Radiology, the First
People’s Hospital of Kashi Prefecture, Kashi, People’s Republic of
China (Y.Q.); Department of MR Scientific Marketing, Siemens Healthineers,
Guangzhou, People’s Republic of China (M.W., X.Y.); and Shanghai Key
Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East
China Normal University, Shanghai, People’s Republic of China
(G.Y.)
| | - Yeqing Liu
- From the Department of Radiology (X.Z., Y.Q., W.J., Z.Y., J.S.),
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene
Regulation, Medical Research Center (X.Z., Y.Q., W.J., Z.Y., Q.L., Y.L., J.S.),
and Department of Pathology (Q.L., Y.L.), Sun Yat-Sen Memorial Hospital, Sun
Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou 510120,
People’s Republic of China; Department of Radiology, the First
People’s Hospital of Kashi Prefecture, Kashi, People’s Republic of
China (Y.Q.); Department of MR Scientific Marketing, Siemens Healthineers,
Guangzhou, People’s Republic of China (M.W., X.Y.); and Shanghai Key
Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East
China Normal University, Shanghai, People’s Republic of China
(G.Y.)
| | - Xu Yan
- From the Department of Radiology (X.Z., Y.Q., W.J., Z.Y., J.S.),
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene
Regulation, Medical Research Center (X.Z., Y.Q., W.J., Z.Y., Q.L., Y.L., J.S.),
and Department of Pathology (Q.L., Y.L.), Sun Yat-Sen Memorial Hospital, Sun
Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou 510120,
People’s Republic of China; Department of Radiology, the First
People’s Hospital of Kashi Prefecture, Kashi, People’s Republic of
China (Y.Q.); Department of MR Scientific Marketing, Siemens Healthineers,
Guangzhou, People’s Republic of China (M.W., X.Y.); and Shanghai Key
Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East
China Normal University, Shanghai, People’s Republic of China
(G.Y.)
| | - Guang Yang
- From the Department of Radiology (X.Z., Y.Q., W.J., Z.Y., J.S.),
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene
Regulation, Medical Research Center (X.Z., Y.Q., W.J., Z.Y., Q.L., Y.L., J.S.),
and Department of Pathology (Q.L., Y.L.), Sun Yat-Sen Memorial Hospital, Sun
Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou 510120,
People’s Republic of China; Department of Radiology, the First
People’s Hospital of Kashi Prefecture, Kashi, People’s Republic of
China (Y.Q.); Department of MR Scientific Marketing, Siemens Healthineers,
Guangzhou, People’s Republic of China (M.W., X.Y.); and Shanghai Key
Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East
China Normal University, Shanghai, People’s Republic of China
(G.Y.)
| | - Jun Shen
- From the Department of Radiology (X.Z., Y.Q., W.J., Z.Y., J.S.),
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene
Regulation, Medical Research Center (X.Z., Y.Q., W.J., Z.Y., Q.L., Y.L., J.S.),
and Department of Pathology (Q.L., Y.L.), Sun Yat-Sen Memorial Hospital, Sun
Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou 510120,
People’s Republic of China; Department of Radiology, the First
People’s Hospital of Kashi Prefecture, Kashi, People’s Republic of
China (Y.Q.); Department of MR Scientific Marketing, Siemens Healthineers,
Guangzhou, People’s Republic of China (M.W., X.Y.); and Shanghai Key
Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East
China Normal University, Shanghai, People’s Republic of China
(G.Y.)
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Kwon MR, Youn I, Ko ES, Choi SH. Correlation of shear-wave elastography stiffness and apparent diffusion coefficient values with tumor characteristics in breast cancer. Sci Rep 2024; 14:7180. [PMID: 38531932 DOI: 10.1038/s41598-024-57832-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 03/22/2024] [Indexed: 03/28/2024] Open
Abstract
We aimed to investigate the correlation between shear-wave elastography (SWE) and apparent diffusion coefficient (ADC) values in breast cancer and to identify the associated characteristics. We included 91 breast cancer patients who underwent SWE and breast MRI prior to surgery between January 2016 and November 2017. We measured the lesion's mean (Emean) and maximum (Emax) elasticities of SWE and ADC values. We evaluated the correlation between SWE, ADC values and tumor size. The mean SWE and ADC values were compared for categorical variable of the pathological/imaging characteristics. ADC values showed negative correlation with Emean (r = - 0.315, p = 0.002) and Emax (r = - 0.326, p = 0.002). SWE was positively correlated with tumor size (r = 0.343-0.366, p < 0.001). A higher SWE value indicated a tendency towards a higher T stage (p < 0.001). Triple-negative breast cancer showed the highest SWE values (p = 0.02). SWE were significantly higher in breast cancers with posterior enhancement, vascularity, and washout kinetics (p < 0.02). SWE stiffness and ADC values were negatively correlated in breast cancer. SWE values correlated significantly with tumor size, and were higher in triple-negative subtype and aggressive imaging characteristics.
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Affiliation(s)
- Mi-Ri Kwon
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Inyoung Youn
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Eun Sook Ko
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, South Korea.
| | - Seon-Hyeong Choi
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Queen's U Clinic, Seoul, South Korea
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Zhang W, Liang F, Zhao Y, Li J, He C, Zhao Y, Lai S, Xu Y, Ding W, Wei X, Jiang X, Yang R, Zhen X. Multiparametric MR-based feature fusion radiomics combined with ADC maps-based tumor proliferative burden in distinguishing TNBC versus non-TNBC. Phys Med Biol 2024; 69:055032. [PMID: 38306970 DOI: 10.1088/1361-6560/ad25c0] [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: 06/23/2023] [Accepted: 02/01/2024] [Indexed: 02/04/2024]
Abstract
Objective.To investigate the incremental value of quantitative stratified apparent diffusion coefficient (ADC) defined tumor habitats for differentiating triple negative breast cancer (TNBC) from non-TNBC on multiparametric MRI (mpMRI) based feature-fusion radiomics (RFF) model.Approach.466 breast cancer patients (54 TNBC, 412 non-TNBC) who underwent routine breast MRIs in our hospital were retrospectively analyzed. Radiomics features were extracted from whole tumor on T2WI, diffusion-weighted imaging, ADC maps and the 2nd phase of dynamic contrast-enhanced MRI. Four models including the RFFmodel (fused features from all MRI sequences), RADCmodel (ADC radiomics feature), StratifiedADCmodel (tumor habitas defined on stratified ADC parameters) and combinational RFF-StratifiedADCmodel were constructed to distinguish TNBC versus non-TNBC. All cases were randomly divided into a training (n= 337) and test set (n= 129). The four competing models were validated using the area under the curve (AUC), sensitivity, specificity and accuracy.Main results.Both the RFFand StratifiedADCmodels demonstrated good performance in distinguishing TNBC from non-TNBC, with best AUCs of 0.818 and 0.773 in the training and test sets. StratifiedADCmodel revealed significant different tumor habitats (necrosis/cysts habitat, chaotic habitat or proliferative tumor core) between TNBC and non-TNBC with its top three discriminative parameters (p <0.05). The integrated RFF-StratifiedADCmodel demonstrated superior accuracy over the other three models, with higher AUCs of 0.832 and 0.784 in the training and test set, respectively (p <0.05).Significance.The RFF-StratifiedADCmodel through integrating various tumor habitats' information from whole-tumor ADC maps-based StratifiedADCmodel and radiomics information from mpMRI-based RFFmodel, exhibits tremendous promise for identifying TNBC.
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Affiliation(s)
- Wanli Zhang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510180, People's Republic of China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou, Guangdong, 510180, People's Republic of China
| | - Fangrong Liang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510180, People's Republic of China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou, Guangdong, 510180, People's Republic of China
| | - Yue Zhao
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou, Guangdong, 510180, People's Republic of China
| | - Jiamin Li
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510180, People's Republic of China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou, Guangdong, 510180, People's Republic of China
| | - Chutong He
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510180, People's Republic of China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou, Guangdong, 510180, People's Republic of China
| | - Yandong Zhao
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510180, People's Republic of China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou, Guangdong, 510180, People's Republic of China
| | - Shengsheng Lai
- School of Medical Equipment, Guangdong Food and Drug Vocational College, Guangzhou, Guangdong, 510520, People's Republic of China
| | - Yongzhou Xu
- Philips Healthcare, Guangzhou, Guangdong, 510220, People's Republic of China
| | - Wenshuang Ding
- Department of Pathology, Guangzhou First People's Hospital, Guangzhou, Guangdong, 510180, People's Republic of China
| | - Xinhua Wei
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510180, People's Republic of China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou, Guangdong, 510180, People's Republic of China
| | - Xinqing Jiang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510180, People's Republic of China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou, Guangdong, 510180, People's Republic of China
| | - Ruimeng Yang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510180, People's Republic of China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou, Guangdong, 510180, People's Republic of China
| | - Xin Zhen
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, 510515, People's Republic of China
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Cai C, Hu T, Rong Z, Gong J, Tong T. Prognostic prediction value of the clinical-radiomics tumour-stroma ratio in locally advanced rectal cancer. Eur J Radiol 2024; 170:111254. [PMID: 38091662 DOI: 10.1016/j.ejrad.2023.111254] [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: 08/29/2023] [Revised: 11/08/2023] [Accepted: 12/05/2023] [Indexed: 01/16/2024]
Abstract
PURPOSE To develop and validate a radiomics model based on high-resolution T2WI and a clinical-radiomics model for tumour-stroma ratio (TSR) evaluation with a gold standard of TSR evaluated by rectal specimens without therapeutic interference and further apply them in prognosis prediction of locally advanced rectal cancer (LARC) patients who received neoadjuvant chemoradiotherapy. METHODS A total of 178 patients (mean age: 59.35, range 20-85 years; 65 women and 113 men) with rectal cancer who received surgery alone from January 2016 to October 2020 were enrolled and randomly separated at a ratio of 7:3 into training and validation sets. A senior radiologist reviewed after 2 readers manually delineated the whole tumour in consensus on preoperative high-resolution T2WI in the training set. A total of 1046 features were then extracted, and recursive feature elimination embedded with leave-one-out cross validation was applied to select features, with which an MR-TSR evaluation model was built containing 6 filtered features via a support vector machine classifier trained by comparing patients' pathological TSR. Stepwise logistic regression was employed to integrate clinical factors with the radiomics model (Fusion-TSR) in the training set. Later, the MR-TSR and Fusion-TSR models were replicated in the validation set for diagnostic effectiveness evaluation. Subsequently, 243 patients (mean age: 53.74, range 23-74 years; 63 women and 180 men) with LARC from October 2012 to September 2017 who were treated with NCRT prior to surgery and underwent standard pretreatment rectal MR examination were enrolled. The MR-TSR and Fusion-TSR were applied, and the Kaplan-Meier method and log-rank test were used to compare the survival of patients with different MR-TSR and Fusion-TSR. Cox proportional hazards regression was used to calculate the hazard ratio (HR). RESULTS Both the MR-TSR and Fusion-TSR models were validated with favourable diagnostic power: the AUC of the MR-TSR was 0.77 (p = 0.01; accuracy = 69.8 %, sensitivity = 88.9 %, specificity = 65.9 %, PPV = 34.8 %, NPV = 96.7 %), while the AUC of the Fusion-TSR was 0.76 (p = 0.014; accuracy = 67.9 %, sensitivity = 88.9 %, specificity = 63.6 %, PPV = 33.3 %, NPV = 96.6 %), outperforming their effectiveness in the training set: the AUC of the MR-TSR was 0.65 (p = 0.035; accuracy = 66.4 %, sensitivity = 61.9 %, specificity = 67.3 %, PPV = 27.7 %, NPV = 90.0 %), while the AUC of the Fusion-TSR was 0.73 (p = 0.001; accuracy = 73.6 %, sensitivity = 71.4 %, specificity = 74.0 %, PPV = 35.73 %, NPV = 92.8 %). With further prognostic analysis, the MR-TSR was validated as a significant prognostic factor for DFS in LARC patients treated with NCRT (p = 0.020, HR = 1.662, 95 % CI = 1.077-2.565), while the Fusion-TSR was a significant prognostic factor for OS (p = 0.005, HR = 2.373, 95 % CI = 1.281-4.396). CONCLUSIONS We developed and validated a radiomics TSR and a clinical-radiomics TSR model and successfully applied them to better risk stratification for LARC patients receiving NCRT and for better decision making.
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Affiliation(s)
- Chongpeng Cai
- Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No. 270, Dongan Rd, Shanghai 200032, China
| | - Tingdan Hu
- Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No. 270, Dongan Rd, Shanghai 200032, China
| | - Zening Rong
- Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No. 270, Dongan Rd, Shanghai 200032, China
| | - Jing Gong
- Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No. 270, Dongan Rd, Shanghai 200032, China.
| | - Tong Tong
- Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No. 270, Dongan Rd, Shanghai 200032, China.
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Le MK, Odate T, Kawai M, Oishi N, Kondo T. Investigating the role of core needle biopsy in evaluating tumor-stroma ratio (TSR) of invasive breast cancer: a retrospective study. Breast Cancer Res Treat 2023; 197:113-121. [PMID: 36335529 DOI: 10.1007/s10549-022-06768-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 10/06/2022] [Indexed: 11/07/2022]
Abstract
PURPOSE Tumor-stroma ratio (TSR) of invasive breast carcinoma has gained attention in recent years due to its prognostic significance. Previous studies showed TSR is a potential biomarker for indicating the tumor response to neoadjuvant chemotherapy. However, it is not clear how well TSR evaluation in biopsy specimens might reflect the TSR in resection specimens. We conducted a study to investigate whether biopsy evaluation of TSR can be an alternative method. METHOD We collected cases with invasive breast carcinoma of no special type (IBC-NST) from University of Yamanashi hospital between 2011 and 2017 whose biopsy and resection specimens both had a pathologically diagnosis of IBC-NST (n = 146). We conceptualized a method for evaluating TSR in biopsy specimens within a preliminary cohort (n = 50). Within the studied cohort (n = 96), biopsy-based TSR (b-TSR) and resection-based TSR (r-TSR) were scored by two pathologists. We then evaluated our method's validity and performance by measuring interobserver variability between the two pathologists, Spearman's correlation between b-TSR and r-TSR, and the receiver operating characteristics (ROC) analysis for defining stroma-rich and stroma-poor tumors. RESULTS Intra-class coefficient between the two pathologists was 0.59. The correlation coefficients between b-TSR and r-TSR in the two pathologists were 0.45 and 0.37. The ROC areas under the curve were 0.7 and 0.67. By considering an r-TSR of < 50% as stroma-rich, the sensitivity and specificity of detecting stroma-rich tumors were 64.1% and 66.7%, respectively, when b-TSR was < 40%. CONCLUSION Our current b-TSR evaluation method can provide information about r-TSR and facilitate pre-treatment therapy follow-up.
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Affiliation(s)
- Minh-Khang Le
- Department of Pathology, University of Yamanashi, Yamanashi, 409-3898, Japan
| | - Toru Odate
- Department of Pathology, University of Yamanashi, Yamanashi, 409-3898, Japan
| | - Masataka Kawai
- Department of Pathology, University of Yamanashi, Yamanashi, 409-3898, Japan
| | - Naoki Oishi
- Department of Pathology, University of Yamanashi, Yamanashi, 409-3898, Japan
| | - Tetsuo Kondo
- Department of Pathology, University of Yamanashi, Yamanashi, 409-3898, Japan.
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Hu S, Xing X, Liu J, Liu X, Li J, Jin W, Li S, Yan Y, Teng D, Liu B, Wang Y, Xu B, Du X. Correlation between apparent diffusion coefficient and tumor-stroma ratio in hybrid 18F-FDG PET/MRI: preliminary results of a rectal cancer cohort study. Quant Imaging Med Surg 2022; 12:4213-4225. [PMID: 35919050 PMCID: PMC9338373 DOI: 10.21037/qims-21-938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 05/17/2022] [Indexed: 11/06/2022]
Abstract
Background To explore possible correlations between the tumor-stroma ratio (TSR) and different imaging features of fluorine-18-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI) in untreated rectal cancer patients. Methods A patients with rectal cancer were included in this study. All participants were examined preoperatively with whole-body 18F-FDG PET/MRI. Two pathologists evaluated the TSR of tumors together. Apparent diffusion coefficient (ADC) values and PET-related parameters of the primary lesions were measured and compared between the stroma-high and stroma-low groups. Pearson's correlation or Spearman's rank correlation were used to evaluate the correlation between the ADC values, PET-related parameters, and pathological indices. Results Our results showed that in the untreated rectal cancer patients, the ADC mean values correlated with the TSR (r=0.327; P=0.007), and stroma-high (low TSR) rectal cancer corresponded to relatively lower ADC mean values (813.54±88.68 vs. 879.92±133.18; P=0.018). The ADC mean and ADC minimum (ADCmin) values were found to be negatively correlated with the pathological T stages (r=-0.384, P=0.001; r=-0.416, P=0.001, respectively) as well as the largest tumor diameters (r=-0.340, P=0.005; r=-0.314, P=0.010, respectively) of rectal cancer. In addition, the pathological T stages correlated with all PET-related metabolic parameters, including mean standard uptake value (SUV), maximum SUV (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) (r=0.338, P=0.006; r=0.350, P=0.004; r=0.326, P=0.007; and r=0.472, P<0.001, respectively). Our results also identified associations between the ADCmin values and SUVmean, SUVmax, and TLG (r=-0.335, P=0.006; r=-0.343, P=0.005; and r=-0.343, P=0.005, respectively). However, there were no statistical correlations between the PET/MRI parameters and the immunohistochemical (IHC) results. Conclusions This study indicated that the intratumoral heterogeneity measured by PET/MRI may reflect characteristics of the tumor microenvironment. Hence, PET/MRI parameters might be helpful in predicting tumor aggressiveness and prognosis.
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Affiliation(s)
- Shidong Hu
- Department of General Surgery, The First Medical Center, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Xiaowei Xing
- Department of Hernia and Abdominal Wall Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Jiajin Liu
- Department of Nuclear Medicine, The First Medical Center, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Xi Liu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Jinhang Li
- Department of Pathology, The First Medical Center, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Wei Jin
- Department of Pathology, The First Medical Center, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Songyan Li
- Department of General Surgery, The First Medical Center, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Yang Yan
- Department of General Surgery, The First Medical Center, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Da Teng
- Department of General Surgery, The First Medical Center, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Boyan Liu
- Department of General Surgery, The First Medical Center, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Yufeng Wang
- Department of Hospital Management, The First Medical Center, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Baixuan Xu
- Department of Nuclear Medicine, The First Medical Center, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Xiaohui Du
- Department of General Surgery, The First Medical Center, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China
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Lee J, Kim SH, Kang BJ, Lee A, Park WC, Hwang J. Imaging characteristics of young age breast cancer (YABC) focusing on pathologic correlation and disease recurrence. Sci Rep 2021; 11:20205. [PMID: 34642389 PMCID: PMC8511101 DOI: 10.1038/s41598-021-99600-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Accepted: 09/14/2021] [Indexed: 11/19/2022] Open
Abstract
The purpose of this study is to investigate imaging characteristics of young age breast cancer (YABC) focusing on correlation with pathologic factors and association with disease recurrence. From January 2017 to December 2019, patients under 40 years old who were diagnosed as breast cancer were enrolled in this study. Morphologic analysis of tumor and multiple quantitative parameters were obtained from pre-treatment dynamic contrast enhanced breast magnetic resonance imaging (DCE-MRI). Tumor-stroma ratio (TSR), microvessel density (MVD) and endothelial Notch 1 (EC Notch 1) were investigated for correlation with imaging parameters. In addition, recurrence associated factors were assessed using both clinico-pathologic factors and imaging parameters. A total of 53 patients were enrolled. Several imaging parameters derived from apparent diffusion coefficient (ADC) histogram showed negative correlation with TSR; and there was negative correlation between MVD and Ve in perfusion analysis. There were nine cases of recurrences with median interval of 16 months. Triple negative subtype and low CD34 MVD positivity in Notch 1 hotspots showed significant association with tumor recurrence. Texture parameters reflecting tumor sphericity and homogeneity were also associated with disease recurrence. In conclusion, several quantitative MRI parameters can be used as imaging biomarkers for tumor microenvironment and can predict disease recurrence in YABC.
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Affiliation(s)
- Jeongmin Lee
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea
| | - Sung Hun Kim
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea.
| | - Bong Joo Kang
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea
| | - Ahwon Lee
- Department of Hospital Pathology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Woo-Chan Park
- Division of Breast-Thyroid Surgery, Department of Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Jinwoo Hwang
- Philips Healthcare Korea, Seoul, Republic of Korea
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8
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Value of multiple models of diffusion-weighted imaging for improving the nodal staging of preoperatively node-negative rectal cancer. Abdom Radiol (NY) 2021; 46:4548-4555. [PMID: 34125271 DOI: 10.1007/s00261-021-03125-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 05/10/2021] [Accepted: 05/19/2021] [Indexed: 12/22/2022]
Abstract
OBJECTIVE To investigate the parameters of multiple diffusion-weighted imaging (DWI) models for improving nodal staging of preoperatively node-negative rectal cancer. MATERIALS AND METHODS A total of 74 rectal cancer patients without suspected metastatic lymph nodes on conventional MRI who underwent direct surgical resection between November 2018 and January 2020 were enrolled in this prospective study. DWI parameters of mono-exponential model (ADC), intravoxel incoherent motion (D, D* and f), stretched exponential model (DDC and α), and diffusion kurtosis imaging (MD and MK) within the whole tumor were measured to predict the nodal staging in rectal cancer patients. RESULTS The D*, DDC, and MK values were significantly different in patients with pN0 and pN1-2 (all P < 0.001). The D*, DDC, and MK showed good diagnostic performance with the area under the receiver operating characteristic (AUC) of 0.788, 0.827 and 0.799. Multivariate analysis indicated D* (odds ratio, OR = 1.163, P = 0.003) and DDC (OR = 0.007, P = 0.019) as significant predictors of nodal staging. The combination of DDC and D* demonstrated superior diagnostic performance with the AUC, sensitivity, specificity and accuracy of 0.872, 0.800, 0.932 and 0.878, respectively. CONCLUSION Multiple functional DWI parameters were potential to identify the rectal cancer patients with micro-nodal involvement for accurate treatment.
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Zhao L, Liang M, Yang Y, Zhao X, Zhang H. Histogram models based on intravoxel incoherent motion diffusion-weighted imaging to predict nodal staging of rectal cancer. Eur J Radiol 2021; 142:109869. [PMID: 34303149 DOI: 10.1016/j.ejrad.2021.109869] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 06/19/2021] [Accepted: 07/14/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE To develop a model based on histogram parameters derived from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for predicting the nodal staging of rectal cancer (RC). MATERIAL AND METHODS A total of 95 RC patients who underwent direct surgical resection were enrolled in this prospective study. The nodal staging on conventional magnetic resonance imaging (MRI) was evaluated according to the short axis diameter and morphological characteristics. Histogram parameters were extracted from apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) maps. Multivariate binary logistic regression analysis was conducted to establish models for predicting nodal staging among all patients and those underestimated on conventional MRI. RESULTS The combined model based on multiple maps demonstrated superior diagnostic performance to single map models, with an area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy of 0.959, 94.3%, 88.3%, and 90.5%, respectively. The AUC of the combined model was significantly higher than that of the conventional nodal staging (P < 0.001). Additionally, 85.0% of the underestimated patients had suspicious lymph nodes with 5-8 mm short-axis diameter. The histogram model for these subgroups of patients showed good diagnostic efficacy with an AUC, sensitivity, specificity, and accuracy of 0.890, 100%, 75%, and 80.5%. CONCLUSION The histogram model based on IVIM-DWI could improve the diagnostic performance of nodal staging of RC. In addition, histogram parameters of IVIM-DWI may help to reduce the uncertainty of nodal staging in underestimated patients on conventional MRI.
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Affiliation(s)
- Li Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Meng Liang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Yang Yang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Xinming Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China.
| | - Hongmei Zhang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China.
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Fang S, Yang Y, Chen B, Yin Z, Liu Y, Tao J, Zhang Y, Yuan Y, Wang Q, Wang S. DWI and IVIM Imaging in a Murine Model of Rhabdomyosarcoma: Correlations with Quantitative Histopathologic Features. J Magn Reson Imaging 2021; 55:225-233. [PMID: 34240504 DOI: 10.1002/jmri.27828] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/23/2021] [Accepted: 06/23/2021] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND High cellularity and abnormal interstitial structures are some of the unfavorable factors that affect the treatment outcomes and survival of rhabdomyosarcoma (RMS) patients. PURPOSE To explore the correlation between diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) with quantitative histopathologic features in a murine model of RMS. STUDY TYPE Prospective. ANIMAL MODEL Murine model of RMS (31 female BALB/c nude mice). FIELD STRENGTH/SEQUENCE 3.0 T; fast spin-echo (FSE) T1-weighted imaging, fast relaxation fast spin-echo (FRFSE) T2-weighted imaging, DWI PROPELLER FSE imaging sequence, and IVIM echo planar imaging sequence; 10 different b-values (0, 50, 100, 150, 200, 400, 600, 800, 1000, and 1200 s/mm2 ). ASSESSMENT Magnetic resonance imaging (MRI) was performed after 30-45 days of implantation. The following MRI parameters were calculated: apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f). Histopathologic features, which contained nuclear, cytoplasmic, and stromal fractions, and the nuclear-to-cytoplasmic ratio within the tumor were measured using image-based segmentation. STATISTICAL TESTS Pearson's correlation, multiple linear regression analysis, and receiver operating characteristic curve analysis were performed. A P < 0.05 was considered statistically significant. RESULTS The ADC value showed moderate negative correlation with nuclear fraction (r = -0.540), and moderate positive correlation with stroma fraction (r = 0.474). The D value showed moderate negative correlation with nuclear fraction (r = -0.491), and moderate positive correlation with stroma fraction (r = 0.421). The f value showed a moderate negative correlation with stroma fraction (r = -0.423). The D value showed the best diagnostic ability. The optimal cut-off D value of 0.460 was associated with 77.8% sensitivity and 68.2% specificity (area under the curve, 0.747). DATA CONCLUSION The ADC, D, and f values obtained from DWI and IVIM images showed moderate correlation with the quantitative histopathologic features in a murine model of RMS. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY STAGE: 3.
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Affiliation(s)
- Shaobo Fang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Yanyu Yang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Bo Chen
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Zhenzhen Yin
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Yajie Liu
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Juan Tao
- Department of Pathology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Yu Zhang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Yuan Yuan
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Qi Wang
- Department of Respiratory, The Second Hospital, Dalian Medical University, Dalian, China
| | - Shaowu Wang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
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Zhao L, Liang M, Yang Y, Zhang H, Zhao X. Prediction of false-negative extramural venous invasion in patients with rectal cancer using multiple mathematical models of diffusion-weighted imaging. Eur J Radiol 2021; 139:109731. [PMID: 33905979 DOI: 10.1016/j.ejrad.2021.109731] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 04/10/2021] [Accepted: 04/16/2021] [Indexed: 01/12/2023]
Abstract
PURPOSE To investigate the parameters from mono-exponential, stretched-exponential, and intravoxel incoherent motion diffusion-weighted imaging (DWI) models for evaluating false-negative extramural venous invasion (EMVI) on conventional magnetic resonance imaging (MRI) in rectal cancer patients. MATERIAL AND METHODS Seventy-two rectal cancer patients with negative EMVI on conventional MRI who underwent direct surgical resection were enrolled in this prospective study. The apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), and water molecular diffusion heterogeneity index (α) values within the whole tumor were obtained to identify the patients with false-negative EMVI. Receiver operating characteristic (ROC) curves were applied to evaluate the diagnostic performance. Multivariate binary logistic regression analysis was conducted to determine the independent risk factors. RESULTS The DDC, D*, f, and α values were significantly different in the EMVI-positive and EMVI-negative groups (P = 0.018, and P < 0.001, respectively). The D*, f, and α values demonstrated good diagnostic performance with area under the ROC curve (AUC) of 0.861, 0.824, and 0.854, respectively. The combined model, including D*, α, and tumor location, proved superior diagnostic performance with the AUC, sensitivity, specificity, and accuracy of 0.971, 0.917, 0.967, and 0.931, respectively. The AUC of the combined model was significantly higher than that of the D*, f, and DDC (P = 0.004, 0.045, and 0.002, respectively). CONCLUSION Multi-b-value DWI may be a potential tool for identifying micro-EMVI in rectal cancer. The combination of DWI parameters and tumor location leads to superior diagnostic performance.
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Affiliation(s)
- Li Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China.
| | - Meng Liang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China.
| | - Yang Yang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China.
| | - Hongmei Zhang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China.
| | - Xinming Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China.
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Cai C, Hu T, Gong J, Huang D, Liu F, Fu C, Tong T. Multiparametric MRI-based radiomics signature for preoperative estimation of tumor-stroma ratio in rectal cancer. Eur Radiol 2020; 31:3326-3335. [PMID: 33180166 DOI: 10.1007/s00330-020-07403-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 09/26/2020] [Accepted: 10/09/2020] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To determine whether a radiomics signature (rad-score) outperforms ADC in TSR estimation by developing a radiomics biomarker for preoperative TSR diagnosis in rectal cancer. METHODS This study included 149 patients (119 and 30 in the training and validation cohorts, respectively). All patients underwent T2-weighted, diffusion-weighted, and contrast-enhanced T1-weighted imaging. A rad-score was generated using the least absolute shrinkage and selection operator (LASSO) algorithm and stepwise multivariate logistic regression. Meanwhile, the mean ADCs were calculated from ADC maps. For both the mean ADC and rad-score, binary logistic regression and Spearman correlation coefficients were used to determine associations with the TSR, and the area under the receiver operating characteristic (ROC) curve was used to assess the diagnostic performance. The reliability of the rad-score was quantified by comparing the imaging-estimated TSR with the actual TSR of each patient. RESULTS Both the mean ADC and rad-score were positively correlated with the TSR in the training cohort (mean ADC: p < 0.001, r = 0.566; rad-score: p < 0.001, r = 0.559) and validation cohort (mean ADC: p < 0.001, r = 0.671; rad-score: p = 0.002, r = 0.536). The rad-score, with AUCs of 0.917 (95% CI 0.869-0.965) and 0.787 (95% CI 0.602-0.972) in the training and validation cohorts, respectively, outperformed the mean ADC (training cohort: AUC = 0.776, 95% CI 0.693-0.859; validation cohort: AUC = 0.764, 95% CI 0.592-0.936) in TSR estimation. CONCLUSION The ADC possesses potential diagnostic value for TSR estimation in rectal cancer, and the rad-score shows increased diagnostic value over the ADC and may be a promising supplemental tool for patient stratification and informing decision-making. KEY POINTS • Tumor-stroma ratio has been verified as an independent prognostic factor for various solid tumors including rectal cancer. • The ADC and multiparametric MRI-based radiomics features were significantly and positively correlated with the tumor-stroma ratio in rectal cancer. • The radiomics signature outperformed the ADC in discriminating TSR in rectal cancer.
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Affiliation(s)
- Chongpeng Cai
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Tingdan Hu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jing Gong
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Dan Huang
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Fangqi Liu
- Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Caixia Fu
- MR Applications Development, Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China
| | - Tong Tong
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China. .,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
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Zunder SM, Perez-Lopez R, de Kok BM, Raciti MV, van Pelt GW, Dienstmann R, Garcia-Ruiz A, Meijer CA, Gelderblom H, Tollenaar RA, Nuciforo P, Wasser MN, Mesker WE. Correlation of the tumour-stroma ratio with diffusion weighted MRI in rectal cancer. Eur J Radiol 2020; 133:109345. [PMID: 33120239 DOI: 10.1016/j.ejrad.2020.109345] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 09/06/2020] [Accepted: 10/07/2020] [Indexed: 11/19/2022]
Abstract
OBJECTIVE This study evaluated the correlation between intratumoural stroma proportion, expressed as tumour-stroma ratio (TSR), and apparent diffusion coefficient (ADC) values in patients with rectal cancer. METHODS This multicentre retrospective study included all consecutive patients with rectal cancer, diagnostically confirmed by biopsy and MRI. The training cohort (LUMC, Netherlands) included 33 patients and the validation cohort (VHIO, Spain) 69 patients. Two observers measured the mean and minimum ADCs based on single-slice and whole-volume segmentations. The TSR was determined on diagnostic haematoxylin & eosin stained slides of rectal tumour biopsies. The correlation between TSR and ADC was assessed by Spearman correlation (rs). RESULTS The ADC values between stroma-low and stroma-high tumours were not significantly different. Intra-class correlation (ICC) demonstrated a good level of agreement for the ADC measurements, ranging from 0.84-0.86 for single slice and 0.86-0.90 for the whole-volume protocol. No correlation was observed between the TSR and ADC values, with ADCmeanrs= -0.162 (p= 0.38) and ADCminrs= 0.041 (p= 0.82) for the single-slice and rs= -0.108 (p= 0.55) and rs= 0.019 (p= 0.92) for the whole-volume measurements in the training cohort, respectively. Results from the validation cohort were consistent; ADCmeanrs= -0.022 (p= 0.86) and ADCminrs = 0.049 (p= 0.69) for the single-slice and rs= -0.064 (p= 0.59) and rs= -0.063 (p= 0.61) for the whole-volume measurements. CONCLUSIONS Reproducibility of ADC values is good. Despite positive reports on the correlation between TSR and ADC values in other tumours, this could not be confirmed for rectal cancer.
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Affiliation(s)
- Stéphanie M Zunder
- Department of Surgery, Leiden University Medical Centre, Albinusdreef 2, 2300 RC, Leiden, The Netherlands; Department of Medical Oncology, Leiden University Medical Centre, Albinusdreef 2, 2300 RC, Leiden, The Netherlands
| | - Raquel Perez-Lopez
- Radiomics Group, Vall d'Hebron Institute of Oncology, Natzaret 115-117. 08035 Barcelona, Spain
| | - Bente M de Kok
- Department of Radiology, Leiden University Medical Centre, Albinusdreef 2, 2300 RC Leiden, The Netherlands
| | - Maria Vittoria Raciti
- Radiomics Group, Vall d'Hebron Institute of Oncology, Natzaret 115-117. 08035 Barcelona, Spain
| | - Gabi W van Pelt
- Department of Surgery, Leiden University Medical Centre, Albinusdreef 2, 2300 RC, Leiden, The Netherlands
| | - Rodrigo Dienstmann
- Department of Oncology Data Science, Vall d'Hebron Institute of Oncology, Cellex Center, Natzaret 115-117 08035 Barcelona, Spain
| | - Alonso Garcia-Ruiz
- Radiomics Group, Vall d'Hebron Institute of Oncology, Natzaret 115-117. 08035 Barcelona, Spain
| | - C Arnoud Meijer
- Department of Radiology, Martini Hospital, Van Swietenplein 1, 9728 NT Groningen The Netherlands
| | - Hans Gelderblom
- Department of Medical Oncology, Leiden University Medical Centre, Albinusdreef 2, 2300 RC, Leiden, The Netherlands
| | - Rob A Tollenaar
- Department of Surgery, Leiden University Medical Centre, Albinusdreef 2, 2300 RC, Leiden, The Netherlands
| | - Paolo Nuciforo
- Department of Molecular Oncology Group, Vall d'Hebron Institute of Oncology, Cellex Center, Natzaret 115-117 08035 Barcelona, Spain
| | - Martin N Wasser
- Department of Radiology, Leiden University Medical Centre, Albinusdreef 2, 2300 RC Leiden, The Netherlands
| | - Wilma E Mesker
- Department of Surgery, Leiden University Medical Centre, Albinusdreef 2, 2300 RC, Leiden, The Netherlands.
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Wang H, Wu L, Wang H. Development and verification of a personalized immune prognostic feature in breast cancer. Exp Biol Med (Maywood) 2020; 245:1242-1253. [PMID: 32600059 PMCID: PMC7437380 DOI: 10.1177/1535370220936964] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 05/29/2020] [Indexed: 01/12/2023] Open
Abstract
IMPACT STATEMENT Breast cancer is among the highest prevalent malignant tumors worldwide with a low survival ratio. Immune-related genes have great potential as prognostic indicator in many types of tumors. Therefore, we have attempted to develop immune-related gene markers to enhance the prognosis of breast cancer. 17-IRGPs signature was constructed as a newly developed prognostic indicator to predict the survival of BC patients.
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Affiliation(s)
- HongLei Wang
- Department of Galactophore, The First Hospital of Lanzhou University, Lanzhou City, Gansu Province 730000, China
| | - Li Wu
- Department of Galactophore, The First Hospital of Lanzhou University, Lanzhou City, Gansu Province 730000, China
| | - HongTao Wang
- Department of General Surgery, The People’s Hospital of Wuwei City, Wuwei City, Gansu Province 733000, China
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15
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Mi HL, Suo ST, Cheng JJ, Yin X, Zhu L, Dong SJ, Huang SS, Lin C, Xu JR, Lu Q. The invasion status of lymphovascular space and lymph nodes in cervical cancer assessed by mono-exponential and bi-exponential DWI-related parameters. Clin Radiol 2020; 75:763-771. [PMID: 32723502 DOI: 10.1016/j.crad.2020.05.024] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 05/06/2020] [Indexed: 12/27/2022]
Abstract
AIM To investigate whether mono-exponential and bi-exponential diffusion-weighted imaging (DWI)-related parameters of the primary tumour can evaluate the status of lymphovascular space invasion (LVSI) and lymph node metastasis (LNM) in patients with cervical carcinoma preoperatively. MATERIALS AND METHODS Eighty patients with cervical carcinoma were enrolled, who underwent preoperative multi b-value DWI and radical hysterectomy. They were classified into LVSI(+) versus LVSI(-) and LNM(+) versus LNM(-) according to postoperative pathology. The apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion coefficient (D∗), and perfusion fraction (f) were calculated from the whole tumour (_whole) and tumour margin (_margin). All parameters were compared between LVSI(+) and LVSI(-) and between LNM(+) and LNM(-). Logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed to evaluate the diagnostic performance of these parameters. RESULTS f_margin and D∗_whole showed significant differences in differentiating LVSI(+) from LVSI(-) tumours (p=0.002, 0.008, respectively), while LNM(+) tumours presented with significantly higher ADC_margin than that of LNM(-) tumours (p=0.009). The other parameters were not independent related factors with the status of LVSI or LNM according to logistic regression analysis (p>0.05). The area under the ROC curve of f_margin combined with D∗_whole in discriminating LVSI(+) from LVSI(-) was 0.826 (95% confidence interval [CI]: 0.691-0.961), while ADC_margin in differentiating LNM(+) from LNM(-) was 0.788 (95% CI: 0.648-0.928). CONCLUSIONS The parameters generated from mono-exponential and bi-exponential DWI of the primary cervical carcinoma could help discriminate its status regarding LVSI (f_margin and D∗_whole) and LNM (ADC_margin).
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Affiliation(s)
- H L Mi
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Rd, Shanghai, 200127, China
| | - S T Suo
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Rd, Shanghai, 200127, China
| | - J J Cheng
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Rd, Shanghai, 200127, China
| | - X Yin
- Department of Gynecology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Rd, Shanghai, 200127, China
| | - L Zhu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Rd, Shanghai, 200127, China
| | - S J Dong
- Department of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, 516 Jungong Rd, Shanghai, 20093, China
| | - S S Huang
- Department of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, 516 Jungong Rd, Shanghai, 20093, China
| | - C Lin
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Rd, Shanghai, 200127, China
| | - J R Xu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Rd, Shanghai, 200127, China
| | - Q Lu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Rd, Shanghai, 200127, China.
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Zhang Q, Ouyang H, Ye F, Chen S, Xie L, Zhao X, Yu X. Multiple mathematical models of diffusion-weighted imaging for endometrial cancer characterization: Correlation with prognosis-related risk factors. Eur J Radiol 2020; 130:109102. [PMID: 32673928 DOI: 10.1016/j.ejrad.2020.109102] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2020] [Revised: 05/18/2020] [Accepted: 05/26/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE To investigate mono-exponential, bi-exponential, and stretched-exponential models of diffusion-weighted imaging (DWI) for evaluation of prognosis-related risk factors of endometrial cancer (EC). METHOD Sixty-one consecutive patients with EC who preoperatively underwent pelvic MRI with multiple b value DWI between September 2016 and May 2018 were enrolled. The apparent-diffusion-coefficient (ADC), bi-exponential model parameters (D, D* and f) and stretched-exponential model parameters (DDC and α) were measured and compared to analyze the following prognosis-related risk factors confirmed by pathology: histological grade, depth of myometrial invasion, cervical stromal infiltration (CSI) and lymphovascular invasion (LVSI). A stepwise multilvariate logistic regression and the receiver operating characteristic (ROC) curves were performed for further statistical analysis. RESULTS Lower ADC, D, f, and DDC were observed in tumor with high grade compared with a low-grade group, and the largest area under curve (AUC) was obtained when combining f and DDC values. ADC, D, f, DDC, and α were significantly different in patients with deep myometrial invasion (DMI) compared to those without DMI; the combination of f, DDC and α showed the highest AUC. Significantly different ADC and f were found between patients' presence and absence CSI; the f values showed the highest diagnostic performance with an AUC of 0.825. Regarding the LVSI, ADC, D*, f, and DDC were significantly lower in tumors with LVSI compared to those without LVSI; the combination of f and DDC showed the largest AUC. CONCLUSION Multiple mathematical DWI models are a useful approach for the prediction of prognosis-related risk factors in EC.
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Affiliation(s)
- Qi Zhang
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Han Ouyang
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Feng Ye
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Shuang Chen
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Lizhi Xie
- GE Healthcare, MR Research China, Beijing, China
| | - Xinming Zhao
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| | - Xiaoduo Yu
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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Yamada S, Morine Y, Imura S, Ikemoto T, Arakawa Y, Saito Y, Yoshikawa M, Miyazaki K, Shimada M. Prognostic prediction of apparent diffusion coefficient obtained by diffusion-weighted MRI in mass-forming intrahepatic cholangiocarcinoma. JOURNAL OF HEPATO-BILIARY-PANCREATIC SCIENCES 2020; 27:388-395. [PMID: 32162483 DOI: 10.1002/jhbp.732] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 02/11/2020] [Accepted: 03/02/2020] [Indexed: 01/14/2023]
Abstract
BACKGROUND We evaluated apparent diffusion coefficient (ADC) of diffusion-weighted image MRI as a prognostic factor for mass-forming intrahepatic cholangiocarcinoma (IHCC). METHODS We enrolled 26 patients who had undergone hepatic resections for mass-forming-type IHCC in this study, and calculated their mean ADC, using diffusion-weighted image MRI (b: 0, 20, 800 seconds/mm2 ; 1.5 T MRI). Patients were divided into the ADCHigh and the ADCLow groups at the median ADC value (n = 13 for both). We also immunohistochemically evaluated hypoxia-inducible factor (HIF)-1α in tumor tissue. RESULTS Median age in the ADCLow was older (P = .03), and showed significant higher rate of scirrhous tumor (P = .02). The 5-year overall survival rate in the ADCLow group was significantly worse than in the ADCHigh group (P = .04). In multivariate analysis, hilar tumor, portal vein invasion and low ADC were independent prognostic factors (P < .05). The ADCLow group also had a higher rate of high HIF-1α expression than the ADCHigh group (P < .05). Representative case of ADCLow group showed rich stroma and high HIF-1α expression. CONCLUSIONS The ADC values in MRIs can predict IHCC prognosis, and correlated with stromal density and HIF-1α expression.
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Affiliation(s)
| | - Yuji Morine
- Department of Surgery, Tokushima University, Tokushima City, Japan
| | - Satoru Imura
- Department of Surgery, Tokushima University, Tokushima City, Japan
| | - Tetsuya Ikemoto
- Department of Surgery, Tokushima University, Tokushima City, Japan
| | - Yusuke Arakawa
- Department of Surgery, Tokushima University, Tokushima City, Japan
| | - Yu Saito
- Department of Surgery, Tokushima University, Tokushima City, Japan
| | - Masato Yoshikawa
- Department of Surgery, Tokushima University, Tokushima City, Japan
| | - Katsuki Miyazaki
- Department of Surgery, Tokushima University, Tokushima City, Japan
| | - Mitsuo Shimada
- Department of Surgery, Tokushima University, Tokushima City, Japan
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Hirata A, Hayano K, Ohira G, Imanishi S, Hanaoka T, Toyozumi T, Murakami K, Aoyagi T, Shuto K, Matsubara H. Volumetric Histogram Analysis of Apparent Diffusion Coefficient as a Biomarker to Predict Survival of Esophageal Cancer Patients. Ann Surg Oncol 2020; 27:3083-3089. [PMID: 32100222 DOI: 10.1245/s10434-020-08270-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Indexed: 12/29/2022]
Abstract
BACKGROUND The purpose of this study was to investigate whether histogram analysis of an apparent diffusion coefficient (ADC) can serve as a prognostic biomarker for esophageal squamous cell carcinoma (ESCC). METHODS This retrospective study enrolled 116 patients with ESCC who received curative surgery from 2006 to 2015 (including 70 patients who received neoadjuvant chemotherapy). Diffusion-weighted magnetic resonance imaging (DWI) was performed prior to treatment. The ADC maps were generated by DWIs at b = 0 and 1000 (s/mm2), and analyzed to obtain ADC histogram-derived parameters (mean ADC, kurtosis, and skewness) of the primary tumor. Associations of these parameters with pathological features were analyzed, and Cox regression and Kaplan-Meier analyses were performed to compare these parameters with recurrence-free survival (RFS) and disease-specific survival (DSS). RESULTS Kurtosis was significantly higher in tumors with lymphatic invasion (p = 0.005) with respect to the associations with pathological features. In univariate Cox regression analysis, tumor depth, lymph node status, mean ADC, and kurtosis were significantly correlated with RFS (p = 0.047, p < 0.001, p = 0.037, and p < 0.001, respectively), while lymph node status and kurtosis were also correlated with DSS (p = 0.002 and p = 0.017, respectively). Furthermore, multivariate analysis demonstrated that kurtosis was the independent prognostic factor for both RFS and DSS (p < 0.001 and p = 0.015, respectively). In Kaplan-Meier analysis, patients with higher kurtosis tumors (> 3.24) showed a significantly worse RFS and DFS (p < 0.001 and p = 0.006, respectively). CONCLUSIONS Histogram analysis of ADC may serve as a useful biomarker for ESCC, reflecting pathological features and prognosis.
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Affiliation(s)
- Atsushi Hirata
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Koichi Hayano
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chiba, Japan.
| | - Gaku Ohira
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Shunsuke Imanishi
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Toshiharu Hanaoka
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Takeshi Toyozumi
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Kentaro Murakami
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Tomoyoshi Aoyagi
- Department of Surgery, Funabashi Municipal Medical Center, Chiba, Japan
| | - Kiyohiko Shuto
- Department of Surgery, Teikyo University Chiba Medical Center, Chiba, Japan
| | - Hisahiro Matsubara
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
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Okada KI, Kawai M, Hirono S, Kojima F, Tanioka K, Terada M, Miyazawa M, Kitahata Y, Iwahashi Y, Ueno M, Hayami S, Murata SI, Shimokawa T, Yamaue H. Diffusion-weighted MRI predicts the histologic response for neoadjuvant therapy in patients with pancreatic cancer: a prospective study (DIFFERENT trial). Langenbecks Arch Surg 2020; 405:23-33. [PMID: 31993737 DOI: 10.1007/s00423-020-01857-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 01/17/2020] [Indexed: 02/06/2023]
Abstract
PURPOSE Pre-operative prediction of histological response to neoadjuvant therapy aids decisions regarding surgical management of borderline resectable pancreatic cancer (BRPC). We elucidate correlation between pre-/post-treatment whole-tumor apparent diffusion coefficient (ADC) value and rate of tumor cell destruction. We newly verify whether post-treatment ADC value at the site of vascular contact predicts R0 resectability of BRPC. METHODS We prospectively reviewed 28 patients with BRPC who underwent diffusion-weighted magnetic resonance imaging before neoadjuvant chemotherapy and surgery. Correlation between the percentage of tumor cell destruction and various parameters was analyzed. Strong parameters were assessed for their ability to predict therapeutic histological response and R0 resectability. RESULTS Pre-/post-treatment whole-tumor ADC value correlated with tumor cell destruction rate by all parameters (R = 0.630/0.714, P < 0.001/< 0.0001). The post-treatment cutoff value of ADC at the site of vascular contact for discriminating histological response of tumor destruction of ≤ 50% and tumor destruction of > 50% was determined at 1.42 × 10-3 mm2/s. It predicts R0 with 88% sensitivity, 50% specificity, and 61% accuracy. For histological response, the post-treatment whole-tumor ADC cutoff value for discriminating between tumor destruction of ≤ 50% and tumor destruction of > 50% was determined at 1.40 × 10-3 mm2/s. It predicts histological response with 100% sensitivity, 81% specificity, and 89% accuracy. It predicts R0 with 88% sensitivity, 70% specificity, and 75% accuracy. CONCLUSIONS Post-treatment whole-tumor ADC value may be a predictor of R0 resectability in patients with BRPC. Tumor cell destruction rate is indicated by the difference between pre-/post-treatment ADC values. This difference is strongly affected by the pre-treatment ADC value. The cutoff value of ADC at the site of vascular contact could not discriminate R0 resectability.
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Affiliation(s)
- Ken-Ichi Okada
- Second Department of Surgery, Wakayama Medical University, Wakayama, 641-8510, Japan
| | - Manabu Kawai
- Second Department of Surgery, Wakayama Medical University, Wakayama, 641-8510, Japan
| | - Seiko Hirono
- Second Department of Surgery, Wakayama Medical University, Wakayama, 641-8510, Japan
| | - Fumiyoshi Kojima
- Department of Human Pathology, Wakayama Medical University, Wakayama, 641-8510, Japan
| | - Kensuke Tanioka
- Clinical Study Support Center, Wakayama Medical University, Wakayama, 641-8510, Japan
| | - Masaki Terada
- Wakayama Minami Radiology Clinic, Wakayama, 641-0012, Japan
| | - Motoki Miyazawa
- Second Department of Surgery, Wakayama Medical University, Wakayama, 641-8510, Japan
| | - Yuji Kitahata
- Second Department of Surgery, Wakayama Medical University, Wakayama, 641-8510, Japan
| | - Yoshifumi Iwahashi
- Department of Human Pathology, Wakayama Medical University, Wakayama, 641-8510, Japan
| | - Masaki Ueno
- Second Department of Surgery, Wakayama Medical University, Wakayama, 641-8510, Japan
| | - Shinya Hayami
- Second Department of Surgery, Wakayama Medical University, Wakayama, 641-8510, Japan
| | - Shin-Ichi Murata
- Department of Human Pathology, Wakayama Medical University, Wakayama, 641-8510, Japan
| | - Toshio Shimokawa
- Clinical Study Support Center, Wakayama Medical University, Wakayama, 641-8510, Japan
| | - Hiroki Yamaue
- Second Department of Surgery, Wakayama Medical University, Wakayama, 641-8510, Japan.
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20
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Li Y, Wang Z, Chen F, Qin X, Li C, Zhao Y, Yan C, Wu Y, Hao P, Xu Y. Intravoxel incoherent motion diffusion-weighted MRI in patients with breast cancer: Correlation with tumor stroma characteristics. Eur J Radiol 2019; 120:108686. [DOI: 10.1016/j.ejrad.2019.108686] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2019] [Revised: 09/15/2019] [Accepted: 09/18/2019] [Indexed: 12/14/2022]
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Sun J, Wu G, Shan F, Meng Z. The Value of IVIM DWI in Combination with Conventional MRI in Identifying the Residual Tumor After Cone Biopsy for Early Cervical Carcinoma. Acad Radiol 2019; 26:1040-1047. [PMID: 30385207 DOI: 10.1016/j.acra.2018.09.027] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Revised: 09/20/2018] [Accepted: 09/28/2018] [Indexed: 02/05/2023]
Abstract
RATIONALE AND OBJECTIVES To investigate the value of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) in combination with conventional MRI in identifying the residual tumor after biopsy for early cervical carcinoma. MATERIALS AND METHODS Eighty patients with histologically proven early cervical carcinoma were enrolled into this study. MRI sequences included two sets of MRI sequences including conventional MRI (T1WI, T2WI, and dynamic contrast-enhanced MRI) and IVIM DWI/conventional MRI combinations. The patients were classified into residual tumor and nonresidual tumor group after biopsy. IVIM parameters were quantitatively analyzed and compared between two groups. The diagnostic ability of two sets of MRI sequences were calculated and compared. RESULTS The mean D and f values were significantly lower in residual tumor group than in nonresidual tumor group (p < 0.05). The areas under receiver operating characteristic curves of D and f for discriminating between residual tumor and nonresidual tumor group were 0.848 and 0.767, respectively. The sensitivity and accuracy of conventional MRI/IVIM DWI combinations for the detection of residual tumor were 82.7% and 83.8%, respectively, while the sensitivity and accuracy of conventional MRI were 52.4% and 53.8%, respectively. CONCLUSION The addition of IVIM DWI to conventional MRI considerably improves the sensitivity and accuracy of the detection of residual tumor after biopsy for early cervical carcinoma.
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Affiliation(s)
- Junqi Sun
- Department of Radiology, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China
| | - Guangyao Wu
- Department of Radiology, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China.
| | - Feifei Shan
- Department of Ultrasound, The Affiliated Yuebei People's Hospital of Shantou University Medical College, Shaoguan, Guangdong Province, China
| | - Zhihua Meng
- Department of Radiology, The Affiliated Yuebei People's Hospital of Shantou University Medical College, Shaoguan, Guangdong Province, China
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Yamaguchi K, Hara Y, Kitano I, Hamamoto T, Kiyomatsu K, Yamasaki F, Egashira R, Nakazono T, Irie H. Tumor-stromal ratio (TSR) of invasive breast cancer: correlation with multi-parametric breast MRI findings. Br J Radiol 2019; 92:20181032. [PMID: 30835501 DOI: 10.1259/bjr.20181032] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
OBJECTIVE To correlate the tumor-stromal ratio (TSR) of invasive breast cancer and MRI findings. METHODS This study was approved by our institutional review board. 126 consecutive patients with surgically proven invasive breast cancer were included. All patients underwent MRI exams including short-tau inversion-recovery (STIR) T 2 weighted imaging, diffusion-weighted imaging (DWI) and post-contrast dynamic imaging. The mean signal intensity (SI) and apparent diffusion coefficient (ADC) value of each lesion were measured. To objectively evaluate the STIR images, the ratio of the SI of the lesion to the muscle (L/M ratio) was also measured. Percentages of MRI kinetic parameters obtained from dynamic images were also measured. The TSR was defined as the percentage of the stromal component, and categorized into high-stroma (> 50%) and low-stroma (< 50%) groups. Intergroup differences in the SI, L/M ratio, ADC value and percentages of kinetic parameters were examined. RESULTS The SI and L/M ratio of the high-stroma group were significantly lower than those of the low-stromal group (208.64 vs 331.86 for SI, 5.69 vs 9.31 for L/M ratio) (p < 0.001). The high-stroma group had significantly lower percentages of a washout pattern (25% vs 34.7 %) (p = 0.012) and significantly higher percentages of a persistent pattern (36.92% vs 28.26 %) (p = 0.044). There were no significant correlations between the TSR and ADC value. CONCLUSION STIR and dynamic sequence of breast MRI reflects the stromal component of invasive breast cancer. ADVANCES IN KNOWLEDGE This is the first study to correlate TSR and MRI findings. STIR and post-contrast dynamic study correlated with the stromal component of breast cancer.
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Affiliation(s)
- Ken Yamaguchi
- 1 Department of Radiology, Faculty of Medicine, Saga University , Saga , Japan
| | - Yukiko Hara
- 2 Department of Radiology, Saga Central Hospital , Saga , Japan
| | - Isao Kitano
- 2 Department of Radiology, Saga Central Hospital , Saga , Japan
| | | | | | - Fumio Yamasaki
- 5 Department of Pathology, Saga Central Hospital , Saga , Japan
| | - Ryoko Egashira
- 1 Department of Radiology, Faculty of Medicine, Saga University , Saga , Japan
| | - Takahiko Nakazono
- 1 Department of Radiology, Faculty of Medicine, Saga University , Saga , Japan
| | - Hiroyuki Irie
- 1 Department of Radiology, Faculty of Medicine, Saga University , Saga , Japan
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Yuan L, Li JJ, Li CQ, Yan CG, Cheng ZL, Wu YK, Hao P, Lin BQ, Xu YK. Diffusion-weighted MR imaging of locally advanced breast carcinoma: the optimal time window of predicting the early response to neoadjuvant chemotherapy. Cancer Imaging 2018; 18:38. [PMID: 30373679 PMCID: PMC6206724 DOI: 10.1186/s40644-018-0173-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Accepted: 10/16/2018] [Indexed: 02/05/2023] Open
Abstract
Background It is very difficult to predict the early response to NAC only on the basis of change in tumor size. ADC value derived from DWI promises to be a valuable parameter for evaluating the early response to treatment. This study aims to establish the optimal time window of predicting the early response to neoadjuvant chemotherapy (NAC) for different subtypes of locally advanced breast carcinoma using diffusion-weighted imaging (DWI). Methods We conducted an institutional review board-approved prospective clinical study of 142 patients with locally advanced breast carcinoma. All patients underwent conventional MR and DW examinations prior to treatment and after first, second, third, fourth, sixth and eighth cycle of NAC. The response to NAC was classified into a pathologic complete response (pCR) and a non-pCR group. DWI parameters were compared between two groups, and the optimal time window for predicting tumor response was established for each chemotherapy regimen. Results For all the genomic subtypes, there were significant differences in baseline ADC value between pCR and non-pCR group (p < 0.05). The time point prior to treatment could be considered as the ideal time point regardless of genomic subtype. In the group that started with taxanes or anthracyclines, for Luminal A or Luminal B subtype, postT1 could be used as the ideal time point during chemotherapy; for Basal-like or HER2-enriched subtype, postT2 as the ideal time point during chemotherapy. In the group that started with taxanes and anthracyclines, for HER2-enriched, Luminal B or Basal-like subtype, postT1 could be used as the ideal time point during chemotherapy; for Luminal A subtype, postT2 as the ideal time point during chemotherapy. Conclusions The time point prior to treatment can be considered as the optimal time point regardless of genomic subtype. For each chemotherapy regimen, the optimal time point during chemotherapy varies across different genomic subtypes.
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Affiliation(s)
- Li Yuan
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, #1838 Guangzhou Avenue North, Guangzhou City, 510515, Guangdong Province, China.,Department of Radiology, Hainan General Hospital, Haikou, 570311, Hainan Province, China
| | - Jian-Jun Li
- Department of Radiology, Hainan General Hospital, Haikou, 570311, Hainan Province, China
| | - Chang-Qing Li
- Department of Radiology, Hainan General Hospital, Haikou, 570311, Hainan Province, China
| | - Cheng-Gong Yan
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, #1838 Guangzhou Avenue North, Guangzhou City, 510515, Guangdong Province, China
| | - Ze-Long Cheng
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, #1838 Guangzhou Avenue North, Guangzhou City, 510515, Guangdong Province, China
| | - Yuan-Kui Wu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, #1838 Guangzhou Avenue North, Guangzhou City, 510515, Guangdong Province, China
| | - Peng Hao
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, #1838 Guangzhou Avenue North, Guangzhou City, 510515, Guangdong Province, China
| | - Bing-Quan Lin
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, #1838 Guangzhou Avenue North, Guangzhou City, 510515, Guangdong Province, China
| | - Yi-Kai Xu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, #1838 Guangzhou Avenue North, Guangzhou City, 510515, Guangdong Province, China.
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Net JM, Whitman GJ, Morris E, Brandt KR, Burnside ES, Giger ML, Ganott M, Sutton EJ, Zuley ML, Rao A. Relationships Between Human-Extracted MRI Tumor Phenotypes of Breast Cancer and Clinical Prognostic Indicators Including Receptor Status and Molecular Subtype. Curr Probl Diagn Radiol 2018; 48:467-472. [PMID: 30270031 DOI: 10.1067/j.cpradiol.2018.08.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Accepted: 08/16/2018] [Indexed: 12/14/2022]
Abstract
PURPOSE The purpose of this study was to investigate if human-extracted MRI tumor phenotypes of breast cancer could predict receptor status and tumor molecular subtype using MRIs from The Cancer Genome Atlas project. MATERIALS AND METHODS Our retrospective interpretation study utilized the analysis of HIPAA-compliant breast MRI data from The Cancer Imaging Archive. One hundred and seven preoperative breast MRIs of biopsy proven invasive breast cancers were analyzed by 3 fellowship-trained breast-imaging radiologists. Each study was scored according to the Breast Imaging Reporting and Data System lexicon for mass and nonmass features. The Spearman rank correlation was used for association analysis of continuous variables; the Kruskal-Wallis test was used for associating continuous outcomes with categorical variables. The Fisher-exact test was used to assess correlations between categorical image-derived features and receptor status. Prediction of estrogen receptor (ER), progesterone receptor, human epidermal growth factor receptor, and molecular subtype were performed using random forest classifiers. RESULTS ER+ tumors were associated with the absence of rim enhancement (P = 0.019, odds ratio [OR] 5.5), heterogeneous internal enhancement (P = 0.02, OR 6.5), peritumoral edema (P = 0.0001, OR 10.0), and axillary adenopathy (P = 0.04, OR 4.4). ER+ tumors were smaller than ER- tumors (23.7 mm vs 29.2 mm, P = 0.02, OR 8.2). All of these variables except the lack of axillary adenopathy were also associated with progesterone receptor+ status. Luminal A tumors (n = 57) were smaller compared to nonLuminal A (21.8 mm vs 27.5 mm, P = 0.035, OR 7.3) and lacked peritumoral edema (P = 0.001, OR 6.8). Basal like tumors were associated with heterogeneous internal enhancement (P = 0.05, OR 10.1), rim enhancement (P = 0.05, OR6.9), and perituomral edema (P = 0.0001, OR 13.8). CONCLUSIONS Human extracted MRI tumor phenotypes may be able to differentiate those tumors with a more favorable clinical prognosis from their more aggressive counterparts.
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Affiliation(s)
- Jose M Net
- Department of Radiology, University of Miami, Miller School of Medicine, Miami, FL.
| | - Gary J Whitman
- Department of Diagnostic Imaging, University of Texas, MD Anderson Cancer Center, Houston, TX
| | - Elizabteh Morris
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | | | | | | | - Marie Ganott
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA
| | - Elizabeth J Sutton
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Arvind Rao
- Department of Bioinformatics and Computational Biology, University of Texas, MD Anderson Cancer Center, Houston, TX
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Li X, Wang P, Li D, Zhu H, Meng L, Song Y, Xie L, Zhu J, Yu T. Intravoxel incoherent motion MR imaging of early cervical carcinoma: correlation between imaging parameters and tumor-stroma ratio. Eur Radiol 2017; 28:1875-1883. [DOI: 10.1007/s00330-017-5183-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 11/01/2017] [Accepted: 11/07/2017] [Indexed: 12/11/2022]
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26
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Hauge A, Wegner CS, Gaustad JV, Simonsen TG, Andersen LMK, Rofstad EK. Diffusion-weighted MRI-derived ADC values reflect collagen I content in PDX models of uterine cervical cancer. Oncotarget 2017; 8:105682-105691. [PMID: 29285283 PMCID: PMC5739670 DOI: 10.18632/oncotarget.22388] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2017] [Accepted: 10/27/2017] [Indexed: 01/09/2023] Open
Abstract
Apparent diffusion coefficient (ADC) values derived from diffusion-weighted magnetic resonance imaging (DW-MRI) are known to reflect the cellular environment of biological tissues. However, emerging evidence accentuates the influence of stromal elements on ADC values. The current study sought to elucidate whether a correlation exists between ADC and the fraction of collagen I-positive tissue across different tumor models of uterine cervical cancer. Early and late generation tumors of four patient-derived xenograft (PDX) models of squamous cell carcinoma (BK-12, ED-15, HL-16, and LA-19) were included. DW-MRI was performed with diffusion encoding constants (b) of 200, 400, 700, and 1000 s/mm2 and diffusion gradient sensitization in three orthogonal directions. The fraction of collagen I-positive connective tissue was determined by immunohistochemistry. Mono-exponential decay curves, from which the ADC value of tumor voxels was calculated, yielded good fits to the diffusion data. A significant inverse correlation was detected between median tumor ADC and collagen I fraction across the four PDX models, indicating that collagen fibers in the extracellular space have the ability to inhibit the movement of water molecules in these xenografts. The results encourage further exploration of DW-MRI as a non-invasive imaging method for characterizing the stromal microenvironment of tumors.
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Affiliation(s)
- Anette Hauge
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Catherine S. Wegner
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Jon-Vidar Gaustad
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Trude G. Simonsen
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Lise Mari K. Andersen
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Einar K. Rofstad
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
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Jalaguier-Coudray A, Villard-Mahjoub R, Delouche A, Delarbre B, Lambaudie E, Houvenaeghel G, Minsat M, Tallet A, Sabatier R, Thomassin-Naggara I. Value of Dynamic Contrast-enhanced and Diffusion-weighted MR Imaging in the Detection of Pathologic Complete Response in Cervical Cancer after Neoadjuvant Therapy: A Retrospective Observational Study. Radiology 2017; 284:432-442. [DOI: 10.1148/radiol.2017161299] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Affiliation(s)
- Aurélie Jalaguier-Coudray
- From the Departments of Radiology (A.J.C., B.D., R.V.M., B.D., A.D.), Gynecology (E.L., G.H.), Radiotherapy (M.M., A.T.), and Oncology (R.S.), Institut Paoli-Calmettes, 232 Boulevard Sainte-Marguerite, 13009 Marseille, France; CRCM and Université Aix-Marseille, Marseille, France (G.H.); Department of Radiology, Hôpital Tenon, APHP, Paris, France (I.T.N.); and Department of Radiology, UPMC, Université Paris 06,
| | - Rim Villard-Mahjoub
- From the Departments of Radiology (A.J.C., B.D., R.V.M., B.D., A.D.), Gynecology (E.L., G.H.), Radiotherapy (M.M., A.T.), and Oncology (R.S.), Institut Paoli-Calmettes, 232 Boulevard Sainte-Marguerite, 13009 Marseille, France; CRCM and Université Aix-Marseille, Marseille, France (G.H.); Department of Radiology, Hôpital Tenon, APHP, Paris, France (I.T.N.); and Department of Radiology, UPMC, Université Paris 06,
| | - Aurélie Delouche
- From the Departments of Radiology (A.J.C., B.D., R.V.M., B.D., A.D.), Gynecology (E.L., G.H.), Radiotherapy (M.M., A.T.), and Oncology (R.S.), Institut Paoli-Calmettes, 232 Boulevard Sainte-Marguerite, 13009 Marseille, France; CRCM and Université Aix-Marseille, Marseille, France (G.H.); Department of Radiology, Hôpital Tenon, APHP, Paris, France (I.T.N.); and Department of Radiology, UPMC, Université Paris 06,
| | - Béatrice Delarbre
- From the Departments of Radiology (A.J.C., B.D., R.V.M., B.D., A.D.), Gynecology (E.L., G.H.), Radiotherapy (M.M., A.T.), and Oncology (R.S.), Institut Paoli-Calmettes, 232 Boulevard Sainte-Marguerite, 13009 Marseille, France; CRCM and Université Aix-Marseille, Marseille, France (G.H.); Department of Radiology, Hôpital Tenon, APHP, Paris, France (I.T.N.); and Department of Radiology, UPMC, Université Paris 06,
| | - Eric Lambaudie
- From the Departments of Radiology (A.J.C., B.D., R.V.M., B.D., A.D.), Gynecology (E.L., G.H.), Radiotherapy (M.M., A.T.), and Oncology (R.S.), Institut Paoli-Calmettes, 232 Boulevard Sainte-Marguerite, 13009 Marseille, France; CRCM and Université Aix-Marseille, Marseille, France (G.H.); Department of Radiology, Hôpital Tenon, APHP, Paris, France (I.T.N.); and Department of Radiology, UPMC, Université Paris 06,
| | - Gilles Houvenaeghel
- From the Departments of Radiology (A.J.C., B.D., R.V.M., B.D., A.D.), Gynecology (E.L., G.H.), Radiotherapy (M.M., A.T.), and Oncology (R.S.), Institut Paoli-Calmettes, 232 Boulevard Sainte-Marguerite, 13009 Marseille, France; CRCM and Université Aix-Marseille, Marseille, France (G.H.); Department of Radiology, Hôpital Tenon, APHP, Paris, France (I.T.N.); and Department of Radiology, UPMC, Université Paris 06,
| | - Mathieu Minsat
- From the Departments of Radiology (A.J.C., B.D., R.V.M., B.D., A.D.), Gynecology (E.L., G.H.), Radiotherapy (M.M., A.T.), and Oncology (R.S.), Institut Paoli-Calmettes, 232 Boulevard Sainte-Marguerite, 13009 Marseille, France; CRCM and Université Aix-Marseille, Marseille, France (G.H.); Department of Radiology, Hôpital Tenon, APHP, Paris, France (I.T.N.); and Department of Radiology, UPMC, Université Paris 06,
| | - Agnès Tallet
- From the Departments of Radiology (A.J.C., B.D., R.V.M., B.D., A.D.), Gynecology (E.L., G.H.), Radiotherapy (M.M., A.T.), and Oncology (R.S.), Institut Paoli-Calmettes, 232 Boulevard Sainte-Marguerite, 13009 Marseille, France; CRCM and Université Aix-Marseille, Marseille, France (G.H.); Department of Radiology, Hôpital Tenon, APHP, Paris, France (I.T.N.); and Department of Radiology, UPMC, Université Paris 06,
| | - Renaud Sabatier
- From the Departments of Radiology (A.J.C., B.D., R.V.M., B.D., A.D.), Gynecology (E.L., G.H.), Radiotherapy (M.M., A.T.), and Oncology (R.S.), Institut Paoli-Calmettes, 232 Boulevard Sainte-Marguerite, 13009 Marseille, France; CRCM and Université Aix-Marseille, Marseille, France (G.H.); Department of Radiology, Hôpital Tenon, APHP, Paris, France (I.T.N.); and Department of Radiology, UPMC, Université Paris 06,
| | - Isabelle Thomassin-Naggara
- From the Departments of Radiology (A.J.C., B.D., R.V.M., B.D., A.D.), Gynecology (E.L., G.H.), Radiotherapy (M.M., A.T.), and Oncology (R.S.), Institut Paoli-Calmettes, 232 Boulevard Sainte-Marguerite, 13009 Marseille, France; CRCM and Université Aix-Marseille, Marseille, France (G.H.); Department of Radiology, Hôpital Tenon, APHP, Paris, France (I.T.N.); and Department of Radiology, UPMC, Université Paris 06,
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Evaluation of the R2* value in invasive ductal carcinoma with respect to hypoxic-related prognostic factors using iterative decomposition of water and fat with echo asymmetry and least-squares emission (IDEAL). Eur Radiol 2017; 27:4316-4323. [PMID: 28401339 DOI: 10.1007/s00330-017-4832-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2016] [Revised: 03/15/2017] [Accepted: 03/21/2017] [Indexed: 12/26/2022]
Abstract
OBJECTIVE To correlate the R2* value obtained by iterative decomposition of water and fat with echo asymmetry and least-squares emission (IDEAL) with fibrotic focus (FF), microvessel density and hypoxic biomarker (HIF-1α) in breast carcinoma. METHODS Forty-two patients who were diagnosed with invasive ductal carcinoma (IDC) of the breast underwent breast MRI including IDEAL before surgery. The entire region of interest (ROI) was delineated on the R2* map, and average tumour R2* value was calculated for each ROI. Histological specimens were evaluated for the presence of FF, the microvessel density (the average microvessel density and the ratio of peripheral to central microvessel density), and the grading of HIF-1α. RESULTS FF was identified in 47.6% (20/42) of IDCs. Average R2* value for IDC with FF (42.4±13.2 Hz) was significantly higher than that without FF (28.5±13.9 Hz) (P = 0.01). Spearman rank correlation suggested that the average R2* value correlated with the grade of HIF-1α and the ratio of peripheral to central microvessel density for IDCs (P < 0.001). CONCLUSION Quantification of tumour R2* using IDEAL is associated with the presence of FF and the overexpression of HIF-1α, and may therefore be useful in predicting hypoxia of breast carcinoma. KEY POINTS • R2* value obtained by IDEAL correlates with the overexpression of HIF-1α. • R2* value obtained by IDEAL is associated with fibrotic focus. • R2* quantification may be useful in predicting hypoxia of breast carcinoma.
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Choi JW, Lee D, Hyun SH, Han M, Kim JH, Lee SJ. Intratumoural heterogeneity measured using FDG PET and MRI is associated with tumour-stroma ratio and clinical outcome in head and neck squamous cell carcinoma. Clin Radiol 2017; 72:482-489. [PMID: 28285707 DOI: 10.1016/j.crad.2017.01.019] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2016] [Revised: 01/02/2017] [Accepted: 01/31/2017] [Indexed: 11/28/2022]
Abstract
AIM To evaluate the association between the tumour-stroma ratio and intratumoural heterogeneity measured using 2-[18F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography (PET) and magnetic resonance imaging (MRI), and further investigate the prognostic significance of imaging biomarkers in head and neck squamous cell carcinoma (HNSCC). MATERIALS AND METHODS Textural-based imaging parameters of the primary tumour were extracted in 44 patients. In addition, the difference between the minimum and maximum apparent diffusion coefficient (ADC) values (ADCdiff) was calculated on MRI. The relationships between the tumour-stroma ratio and imaging parameters were evaluated. The associations between imaging parameters and recurrence-free survival (RFS) were assessed using Cox proportional hazard regression models. RESULTS Coarseness (r=-0.382) on PET and ADCdiff (r=0.534) on MRI were significantly correlated with the proportion of stroma. The best imaging biomarkers for the 2-year RFS prediction were coarseness (AUC=0.741) and ADCdiff (AUC=0.779). Multivariate analysis showed that coarseness (hazard ratio=10.549, 95% confidence interval=2.544-43.748, p=0.001) was an independent prognostic factor for RFS. CONCLUSION Heterogeneity imaging parameters are significantly associated with the tumour-stroma ratio. These imaging biomarkers may help to facilitate the risk stratification for tumour recurrence in HNSCC.
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Affiliation(s)
- J W Choi
- Department of Radiology, Ajou University School of Medicine, Suwon, Republic of Korea
| | - D Lee
- Department of Pathology, Ajou University School of Medicine, Suwon, Republic of Korea
| | - S H Hyun
- Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - M Han
- Department of Radiology, Ajou University School of Medicine, Suwon, Republic of Korea
| | - J-H Kim
- Department of Pathology, Ajou University School of Medicine, Suwon, Republic of Korea
| | - S J Lee
- Department of Nuclear Medicine, Ajou University School of Medicine, Suwon, Republic of Korea.
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30
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Seo M, Ryu JK, Jahng GH, Sohn YM, Rhee SJ, Oh JH, Won KY. Estimation of T2* Relaxation Time of Breast Cancer: Correlation with Clinical, Imaging and Pathological Features. Korean J Radiol 2017; 18:238-248. [PMID: 28096732 PMCID: PMC5240483 DOI: 10.3348/kjr.2017.18.1.238] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Accepted: 08/20/2016] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVE The purpose of this study was to estimate the T2* relaxation time in breast cancer, and to evaluate the association between the T2* value with clinical-imaging-pathological features of breast cancer. MATERIALS AND METHODS Between January 2011 and July 2013, 107 consecutive women with 107 breast cancers underwent multi-echo T2*-weighted imaging on a 3T clinical magnetic resonance imaging system. The Student's t test and one-way analysis of variance were used to compare the T2* values of cancer for different groups, based on the clinical-imaging-pathological features. In addition, multiple linear regression analysis was performed to find independent predictive factors associated with the T2* values. RESULTS Of the 107 breast cancers, 92 were invasive and 15 were ductal carcinoma in situ (DCIS). The mean T2* value of invasive cancers was significantly longer than that of DCIS (p = 0.029). Signal intensity on T2-weighted imaging (T2WI) and histologic grade of invasive breast cancers showed significant correlation with T2* relaxation time in univariate and multivariate analysis. Breast cancer groups with higher signal intensity on T2WI showed longer T2* relaxation time (p = 0.005). Cancer groups with higher histologic grade showed longer T2* relaxation time (p = 0.017). CONCLUSION The T2* value is significantly longer in invasive cancer than in DCIS. In invasive cancers, T2* relaxation time is significantly longer in higher histologic grades and high signal intensity on T2WI. Based on these preliminary data, quantitative T2* mapping has the potential to be useful in the characterization of breast cancer.
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Affiliation(s)
- Mirinae Seo
- Department of Radiology, Kyung Hee University Hospital, College of Medicine, Kyung Hee University, Seoul 02447, Korea
| | - Jung Kyu Ryu
- Department of Radiology, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University, Seoul 05278, Korea
| | - Geon-Ho Jahng
- Department of Radiology, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University, Seoul 05278, Korea
| | - Yu-Mee Sohn
- Department of Radiology, Kyung Hee University Hospital, College of Medicine, Kyung Hee University, Seoul 02447, Korea
| | - Sun Jung Rhee
- Department of Radiology, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University, Seoul 05278, Korea
| | - Jang-Hoon Oh
- Department of Radiology, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University, Seoul 05278, Korea
| | - Kyu-Yeoun Won
- Department of Pathology, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University, Seoul 05278, Korea
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31
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Lee YJ, Kim SH, Kang BJ, Kang YJ, Yoo H, Yoo J, Lee J, Son YH, Grimm R. Intravoxel incoherent motion (IVIM)‐derived parameters in diffusion‐weighted MRI: Associations with prognostic factors in invasive ductal carcinoma. J Magn Reson Imaging 2016; 45:1394-1406. [DOI: 10.1002/jmri.25514] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2016] [Accepted: 10/05/2016] [Indexed: 12/26/2022] Open
Affiliation(s)
- Youn Joo Lee
- Department of RadiologyDaejeon St. Mary's HospitalSeoul Republic of Korea
| | - Sung Hun Kim
- Seoul St. Mary's HospitalSeoul Republic of Korea
| | | | - Young Jee Kang
- College of MedicineThe Catholic University of KoreaSeoul Republic of Korea
| | - Heesoo Yoo
- College of MedicineThe Catholic University of KoreaSeoul Republic of Korea
| | - Jaewan Yoo
- College of MedicineThe Catholic University of KoreaSeoul Republic of Korea
| | - Jaeun Lee
- College of MedicineThe Catholic University of KoreaSeoul Republic of Korea
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32
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Meng L, Xu Y, Xu C, Zhang W. Biomarker discovery to improve prediction of breast cancer survival: using gene expression profiling, meta-analysis, and tissue validation. Onco Targets Ther 2016; 9:6177-6185. [PMID: 27785066 PMCID: PMC5067006 DOI: 10.2147/ott.s113855] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Purpose Breast cancer is the leading cause of cancer death worldwide in women. The molecular mechanism for human breast cancer is unknown. Gene microarray has been widely used in breast cancer research to identify clinically relevant molecular subtypes as well as to predict prognosis survival. So far, the valuable multigene signatures in clinical practice are unclear, and the biological importance of individual genes is difficult to detect, as the described signatures virtually do not overlap. Early prognosis of this disease, breast invasive ductal carcinoma (IDC) and breast ductal carcinoma in situ (DCIS), is vital in breast surgery. Methods Thus, this study reports gene expression profiling in large breast cancer cohorts from Gene Expression Omnibus, including GSE29044 (N=138) and GSE10780 (N=185) test series and four independent validation series GSE21653 (N=266), GSE20685 (N=327), GSE26971 (N=276), and GSE12776 (N=204). Significantly differentially expressed genes in human breast IDC and breast DCIS were detected by transcriptome microarray analysis. Results We created a set of three genes (MAMDC2, TSHZ2, and CLDN11) that were significantly correlated with disease-free survival of breast cancer patients using a univariate Cox regression model (significance level P<0.01) in a meta-analysis. Based on the risk score of the three genes, the test series patients could be separated into low-risk and high-risk groups with significantly different survival times. This signature was validated in the other three cohorts. The prognostic value of this three-gene signature was confirmed in the internal validation series and another four independent breast cancer data sets. The prognostic impact of one of the three genes, CLDN11, was confirmed by immunohistochemistry. CLDN11 was significantly overexpressed in human breast IDC as compared with normal breast tissues and breast DCIS. Conclusion Using novel gene expression profiling together with a meta-analysis validation approach, we have identified a three-gene signature with independent prognostic impact. Furthermore, CLDN11 may offer a biomarker to predict prognosis as well as a new target for prognostic and therapeutic intervention for human breast IDC.
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Affiliation(s)
- Liwei Meng
- Department of Breast and Thyroid Surgery, Shaoxing People's Hospital, Shaoxing Hospital of Zhejiang University, Shaoxing, Zhejiang, People's Republic of China
| | - Yingchun Xu
- Department of Breast and Thyroid Surgery, Shaoxing People's Hospital, Shaoxing Hospital of Zhejiang University, Shaoxing, Zhejiang, People's Republic of China
| | - Chaoyang Xu
- Department of Breast and Thyroid Surgery, Shaoxing People's Hospital, Shaoxing Hospital of Zhejiang University, Shaoxing, Zhejiang, People's Republic of China
| | - Wei Zhang
- Department of Breast and Thyroid Surgery, Shaoxing People's Hospital, Shaoxing Hospital of Zhejiang University, Shaoxing, Zhejiang, People's Republic of China
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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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Hahn SY, Ko ES, Han BK, Lim Y, Gu S, Ko EY. Analysis of factors influencing the degree of detectability on diffusion-weighted MRI and diffusion background signals in patients with invasive breast cancer. Medicine (Baltimore) 2016; 95:e4086. [PMID: 27399100 PMCID: PMC5058829 DOI: 10.1097/md.0000000000004086] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
To determine the factors influencing the degree of detectability of lesions and diffusion background signals on magnetic resonance diffusion-weighted imaging (DWI) in invasive breast cancer.Institutional review board approval was obtained and patient consent was waived. Patients with newly diagnosed invasive ductal carcinoma, who underwent preoperative breast magnetic resonance imaging with DWI were included in this study (n = 167). Lesion detectability on DWI and contrast-enhanced subtracted T1-weighted images, the degree of background parenchymal enhancement (BPE), and diffusion background signal were qualitatively rated. Detectability of lesions on DWI was compared with clinicopathological findings including menopausal status, mammographic density, and molecular subtype of breast cancer. Multivariate linear regression analysis was performed to determine variables independently associated with detectability of lesions on DWI and diffusion background signals.Univariate analysis showed that the detectability of lesions on DWI was significantly associated with lesion size (P = 0.001), diffuse background signal (P < 0.0001), and higher detectability scores for contrast-enhanced T1-weighted subtraction images (P = 0.000). The degree of diffusion background signal was significantly affected by age (P < 0.0001), BPE (P < 0.0001), mammographic density (P = 0.002), and menopausal status (P < 0.0001). On multivariate analysis, the diffusion background signal (P < 0.0001) and histologic grade (P < 0.0001) were correlated with the detectability on DWI of invasive breast cancer. Only BPE was correlated with the amount of diffusion background signal on DWI (P < 0.0001).For invasive breast cancers, detectability on DWI was significantly affected by the diffusion background signal. BPE, menopausal status, menstrual cycle, or mammographic density did not show statistically significant correlation with the diffusion detectability of lesions on DWI.
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Affiliation(s)
- Soo Yeon Hahn
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul
| | - Eun Sook Ko
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul
| | - Boo-Kyung Han
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul
| | - Yaeji Lim
- Department of Statistics, Pukyong National University, Busan
| | - Seonhye Gu
- Biostatistics and Clinical Epidemiology Center, Samsung Medical Center, Seoul, Korea
| | - Eun Young Ko
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul
- Correspondence: Eun Sook Ko, Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul 135-710, Korea (e-mail: )
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35
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Li H, Zhu Y, Burnside ES, Huang E, Drukker K, Hoadley KA, Fan C, Conzen SD, Zuley M, Net JM, Sutton E, Whitman GJ, Morris E, Perou CM, Ji Y, Giger ML. Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set. NPJ Breast Cancer 2016; 2. [PMID: 27853751 PMCID: PMC5108580 DOI: 10.1038/npjbcancer.2016.12] [Citation(s) in RCA: 230] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Using quantitative radiomics, we demonstrate that computer-extracted magnetic resonance (MR) image-based tumor phenotypes can be predictive of the molecular classification of invasive breast cancers. Radiomics analysis was performed on 91 MRIs of biopsy-proven invasive breast cancers from National Cancer Institute’s multi-institutional TCGA/TCIA. Immunohistochemistry molecular classification was performed including estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and for 84 cases, the molecular subtype (normal-like, luminal A, luminal B, HER2-enriched, and basal-like). Computerized quantitative image analysis included: three-dimensional lesion segmentation, phenotype extraction, and leave-one-case-out cross validation involving stepwise feature selection and linear discriminant analysis. The performance of the classifier model for molecular subtyping was evaluated using receiver operating characteristic analysis. The computer-extracted tumor phenotypes were able to distinguish between molecular prognostic indicators; area under the ROC curve values of 0.89, 0.69, 0.65, and 0.67 in the tasks of distinguishing between ER+ versus ER−, PR+ versus PR−, HER2+ versus HER2−, and triple-negative versus others, respectively. Statistically significant associations between tumor phenotypes and receptor status were observed. More aggressive cancers are likely to be larger in size with more heterogeneity in their contrast enhancement. Even after controlling for tumor size, a statistically significant trend was observed within each size group (P=0.04 for lesions ⩽2 cm; P=0.02 for lesions >2 to ⩽5 cm) as with the entire data set (P-value=0.006) for the relationship between enhancement texture (entropy) and molecular subtypes (normal-like, luminal A, luminal B, HER2-enriched, basal-like). In conclusion, computer-extracted image phenotypes show promise for high-throughput discrimination of breast cancer subtypes and may yield a quantitative predictive signature for advancing precision medicine.
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Affiliation(s)
- Hui Li
- Department of Radiology, The University of Chicago, Chicago, IL, USA
| | - Yitan Zhu
- Program of Computational Genomics & Medicine, NorthShore University HealthSystem, Evanston, IL, USA
| | | | - Erich Huang
- National Cancer Institute, Cancer Imaging Program, Bethesda, MA, USA
| | - Karen Drukker
- Department of Radiology, The University of Chicago, Chicago, IL, USA
| | - Katherine A Hoadley
- Department of Genetics, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Cheng Fan
- Department of Genetics, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Suzanne D Conzen
- Department of Medicine, The University of Chicago, Chicago, IL, USA
| | - Margarita Zuley
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jose M Net
- Department of Radiology, University of Miami Health System, Miami, FL, USA
| | - Elizabeth Sutton
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Gary J Whitman
- Department of Radiology, MD Anderson Cancer Center, Houston, TX, USA
| | - Elizabeth Morris
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Charles M Perou
- Department of Genetics, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Yuan Ji
- Program of Computational Genomics & Medicine, NorthShore University HealthSystem, Evanston, IL, USA; Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Maryellen L Giger
- Department of Radiology, The University of Chicago, Chicago, IL, USA
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36
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Cho EY, Ko ES, Han BK, Kim RB, Cho S, Choi JS, Hahn SY. Shear-wave elastography in invasive ductal carcinoma: correlation between quantitative maximum elasticity value and detailed pathological findings. Acta Radiol 2016; 57:521-8. [PMID: 26071494 DOI: 10.1177/0284185115590287] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2014] [Accepted: 05/11/2015] [Indexed: 01/25/2023]
Abstract
BACKGROUND Further information is needed regarding whether histopathological characteristics affect breast tumor elasticity. PURPOSE To determine whether maximum elasticity values vary according to tumor-stroma ratio, dominant stroma type, or presence of fibrosis in invasive breast cancer. MATERIAL AND METHODS This study included 71 patients with invasive ductal carcinoma not otherwise specified (IDC NOS) who underwent breast shear-wave elastography (SWE). Maximum elasticity (Emax) values were retrospectively correlated with pathological findings that included tumor-stroma ratio, dominant stroma type (collagen, fibroblast, lymphocyte), and fibrosis. Multiple linear regression analysis was performed to determine variables independently associated with Emax. RESULTS High histologic grade was significantly correlated with higher Emax (P = 0.042). Estrogen receptor and progesterone receptor expression negatively correlated with high elasticity values (P = 0.013 and P = 0.03, respectively). Breast cancers that exhibited higher cellularity demonstrated a greater level of stiffness that was not statistically significant (ρ = 0.153; P = 0.193). While dominant stroma type and fibrosis did not affect Emax (P = 0.197 and P = 0.598, respectively), lesion size was significantly associated with Emax (ρ = 0.474, P < 0.001). On multivariate analysis, only lesion size was significantly associated with Emax (P < 0.001). CONCLUSION The composition of tumors did not affect their Emax.
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Affiliation(s)
- Eun Yoon Cho
- Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Eun Sook Ko
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Boo-Kyung Han
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Rock Bum Kim
- Department of Preventive Medicine, Dong-A University School of Medicine, Busan, Republic of Korea
| | - Sooyoun Cho
- Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Ji Soo Choi
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Soo Yeon Hahn
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
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Ko ES, Kim JH, Lim Y, Han BK, Cho EY, Nam SJ. Assessment of Invasive Breast Cancer Heterogeneity Using Whole-Tumor Magnetic Resonance Imaging Texture Analysis: Correlations With Detailed Pathological Findings. Medicine (Baltimore) 2016; 95:e2453. [PMID: 26817878 PMCID: PMC4998252 DOI: 10.1097/md.0000000000002453] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
There is no study that investigates the potential correlation between the heterogeneity obtained from texture analysis of medical images and the heterogeneity observed from histopathological findings. We investigated whether texture analysis of magnetic resonance images correlates with histopathological findings.Seventy-five patients with estrogen receptor positive invasive ductal carcinoma who underwent preoperative breast magnetic resonance imaging (MRI) were included. Tumor entropy and uniformity were determined on T2- and contrast-enhanced T1-weighted subtraction images under different filter levels. Two pathologists evaluated the detailed histopathological findings of the tumors including tumor cellularity, dominant stroma type, central scar, histologic grade, extensive intraductal component (EIC), and lymphovascular invasion. Entropy and uniformity values on both T2- and contrast-enhanced T1-weighted subtraction images were compared with detailed pathological findings.In a multivariate analysis, entropy significantly increased only on unfiltered T2-weighted images (P = 0.013). Tumor cellularity and predominant stroma did not affect the uniformity or entropy on both T2- and contrast-enhanced T1-weighted subtraction images. High histologic grades showed increased uniformity and decreased entropy on contrast-enhanced T1-weighted subtraction images, whereas the opposite tendency was observed on T2-weighted images. Invasive ductal carcinoma with an EIC or lymphovascular invasion only affected the contrast-enhanced T1-weighted subtraction images, through increased uniformity and decreased entropy. The best uniformity results were recorded on T2- and contrast-enhanced T1-weighted subtraction images at a filter level of 0.5. Entropy showed the best results at a filter level of 0.5 on contrast-enhanced T1-weighted subtraction images. However, on T2-weighted images, an ideal model was achieved on unfiltered images.MRI texture analysis correlated with pathological tumor heterogeneity.
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Affiliation(s)
- Eun Sook Ko
- From the Department of Radiology (ESK, J-HK, B-KH); Biostatistics and Clinical Epidemiology Center (YL); Department of Pathology (EYC); and Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, Korea (SJN)
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Analysis of kinetic curve and model-based perfusion parameters on dynamic contrast enhanced MRI in breast cancer patients: Correlations with dominant stroma type. Magn Reson Imaging 2016; 34:60-5. [DOI: 10.1016/j.mri.2015.07.010] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Revised: 06/26/2015] [Accepted: 07/25/2015] [Indexed: 11/22/2022]
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Sun K, Chen X, Chai W, Fei X, Fu C, Yan X, Zhan Y, Chen K, Shen K, Yan F. Breast Cancer: Diffusion Kurtosis MR Imaging—Diagnostic Accuracy and Correlation with Clinical-Pathologic Factors. Radiology 2015; 277:46-55. [DOI: 10.1148/radiol.15141625] [Citation(s) in RCA: 169] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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Koyasu S, Tsuji Y, Harada H, Nakamoto Y, Nobashi T, Kimura H, Sano K, Koizumi K, Hamaji M, Togashi K. Evaluation of Tumor-associated Stroma and Its Relationship with Tumor Hypoxia Using Dynamic Contrast-enhanced CT and (18)F Misonidazole PET in Murine Tumor Models. Radiology 2015; 278:734-41. [PMID: 26393963 DOI: 10.1148/radiol.2015150416] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
PURPOSE To determine the relationship between the fractional interstitial volume (Fis), as calculated at dynamic contrast material-enhanced (DCE) computed tomography (CT), and tumor-associated stroma and to analyze its spatial relationship with tumor hypoxia in several xenograft tumor models. MATERIALS AND METHODS All animal experiments were approved by the animal research committee. Mice with three different xenograft tumors (U251, CFPAC-1, and BxPC-3; n = 6, n = 8, and n = 6, respectively) underwent DCE CT then hypoxia imaging with fluorine 18 ((18)F) fluoromisonidazole (FMISO) positron emission tomography (PET) within 24 hours. Immunohistochemical analysis was performed in harvested tumors to detect hypoxia markers and to quantify microvascular and stromal density. Two DCE CT parameters (amount of interstitial space associated with the amount of stroma [Fis] and flow velocity [Fv]) were identified and quantitatively validated by using immunohistochemistry. FMISO uptake within the tumor was also assessed in relation to DCE CT parameters. Imaging and immunohistochemical parameters were assessed by using the Kruskal-Wallis test, Wilcoxon rank-sum test with Bonferroni correction, and Pearson correlation coefficient. RESULTS Almost no α-smooth muscle actin-positive cells were found in the U251 xenograft, while abundant stroma was found in the entire BxPC-3 xenograft and in the periphery of the CFPAC-1 xenograft. Quantitative analysis showed a significant correlation (R = 0.83, P < .0001) between Fis and stromal density. FMISO uptake had a negative correlation with Fis (R = -0.58, P < .0001) and Fv (R = -0.53, P < .0001). CONCLUSION DCE CT can be used to quantify parameters associated with tumor-associated stroma. Tumor hypoxia was Complementarily localized in tumor-associated stroma in these models.
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Affiliation(s)
- Sho Koyasu
- From the Departments of Diagnostic Imaging and Nuclear Medicine (S.K., Y.N., T.N., K.S., K.T.), Gastroenterology and Hepatology (Y.T.), and Radiation Oncology and Image-Applied Therapy (H.H.), Graduate School of Medicine, Division of Molecular Imaging, Radioisotope Research Center (H.K), Clinical Radiology Service, Kyoto University Hospital (K.K.); and Department of Bioartificial Organs, Institute for Frontier Medical Science (M.H.), Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Yoshihisa Tsuji
- From the Departments of Diagnostic Imaging and Nuclear Medicine (S.K., Y.N., T.N., K.S., K.T.), Gastroenterology and Hepatology (Y.T.), and Radiation Oncology and Image-Applied Therapy (H.H.), Graduate School of Medicine, Division of Molecular Imaging, Radioisotope Research Center (H.K), Clinical Radiology Service, Kyoto University Hospital (K.K.); and Department of Bioartificial Organs, Institute for Frontier Medical Science (M.H.), Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Hiroshi Harada
- From the Departments of Diagnostic Imaging and Nuclear Medicine (S.K., Y.N., T.N., K.S., K.T.), Gastroenterology and Hepatology (Y.T.), and Radiation Oncology and Image-Applied Therapy (H.H.), Graduate School of Medicine, Division of Molecular Imaging, Radioisotope Research Center (H.K), Clinical Radiology Service, Kyoto University Hospital (K.K.); and Department of Bioartificial Organs, Institute for Frontier Medical Science (M.H.), Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Yuji Nakamoto
- From the Departments of Diagnostic Imaging and Nuclear Medicine (S.K., Y.N., T.N., K.S., K.T.), Gastroenterology and Hepatology (Y.T.), and Radiation Oncology and Image-Applied Therapy (H.H.), Graduate School of Medicine, Division of Molecular Imaging, Radioisotope Research Center (H.K), Clinical Radiology Service, Kyoto University Hospital (K.K.); and Department of Bioartificial Organs, Institute for Frontier Medical Science (M.H.), Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Tomomi Nobashi
- From the Departments of Diagnostic Imaging and Nuclear Medicine (S.K., Y.N., T.N., K.S., K.T.), Gastroenterology and Hepatology (Y.T.), and Radiation Oncology and Image-Applied Therapy (H.H.), Graduate School of Medicine, Division of Molecular Imaging, Radioisotope Research Center (H.K), Clinical Radiology Service, Kyoto University Hospital (K.K.); and Department of Bioartificial Organs, Institute for Frontier Medical Science (M.H.), Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Hiroyuki Kimura
- From the Departments of Diagnostic Imaging and Nuclear Medicine (S.K., Y.N., T.N., K.S., K.T.), Gastroenterology and Hepatology (Y.T.), and Radiation Oncology and Image-Applied Therapy (H.H.), Graduate School of Medicine, Division of Molecular Imaging, Radioisotope Research Center (H.K), Clinical Radiology Service, Kyoto University Hospital (K.K.); and Department of Bioartificial Organs, Institute for Frontier Medical Science (M.H.), Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Kohei Sano
- From the Departments of Diagnostic Imaging and Nuclear Medicine (S.K., Y.N., T.N., K.S., K.T.), Gastroenterology and Hepatology (Y.T.), and Radiation Oncology and Image-Applied Therapy (H.H.), Graduate School of Medicine, Division of Molecular Imaging, Radioisotope Research Center (H.K), Clinical Radiology Service, Kyoto University Hospital (K.K.); and Department of Bioartificial Organs, Institute for Frontier Medical Science (M.H.), Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Koji Koizumi
- From the Departments of Diagnostic Imaging and Nuclear Medicine (S.K., Y.N., T.N., K.S., K.T.), Gastroenterology and Hepatology (Y.T.), and Radiation Oncology and Image-Applied Therapy (H.H.), Graduate School of Medicine, Division of Molecular Imaging, Radioisotope Research Center (H.K), Clinical Radiology Service, Kyoto University Hospital (K.K.); and Department of Bioartificial Organs, Institute for Frontier Medical Science (M.H.), Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Masatsugu Hamaji
- From the Departments of Diagnostic Imaging and Nuclear Medicine (S.K., Y.N., T.N., K.S., K.T.), Gastroenterology and Hepatology (Y.T.), and Radiation Oncology and Image-Applied Therapy (H.H.), Graduate School of Medicine, Division of Molecular Imaging, Radioisotope Research Center (H.K), Clinical Radiology Service, Kyoto University Hospital (K.K.); and Department of Bioartificial Organs, Institute for Frontier Medical Science (M.H.), Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Kaori Togashi
- From the Departments of Diagnostic Imaging and Nuclear Medicine (S.K., Y.N., T.N., K.S., K.T.), Gastroenterology and Hepatology (Y.T.), and Radiation Oncology and Image-Applied Therapy (H.H.), Graduate School of Medicine, Division of Molecular Imaging, Radioisotope Research Center (H.K), Clinical Radiology Service, Kyoto University Hospital (K.K.); and Department of Bioartificial Organs, Institute for Frontier Medical Science (M.H.), Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
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Shin S, Ko ES, Kim RB, Han BK, Nam SJ, Shin JH, Hahn SY. Effect of menstrual cycle and menopausal status on apparent diffusion coefficient values and detectability of invasive ductal carcinoma on diffusion-weighted MRI. Breast Cancer Res Treat 2015; 149:751-9. [PMID: 25638396 DOI: 10.1007/s10549-015-3278-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Accepted: 01/18/2015] [Indexed: 11/28/2022]
Abstract
The purpose of this study was to determine whether the apparent diffusion coefficient (ADC) and tumor detectability based on diffusion-weighted imaging (DWI) are affected by the menstrual cycle or menopausal status in breast cancer patients. Institutional review board approval was obtained, and the requirement for informed consent was waived. A total of 124 women with invasive ductal carcinoma not otherwise specified (IDC NOS) who underwent breast MRI with DWI were included in this study. Two radiologists retrospectively measured the ADCs of tumor and contralateral normal glandular tissue and scored the tumor detectability. The ADCs and detectability were compared to menstrual cycle and menopausal status, based on patient questionnaires. ADCs of tumors and contralateral tissue were significantly lower in postmenopausal women than in premenopausal women (P = 0.006 and P < 0.001, respectively). Tumor detectability did not differ significantly between the premenopausal and postmenopausal groups (P = 0.454). Normalized ADCs were not significantly lower in postmenopausal women compared to premenopausal women (P = 0.880). There was no statistically significant difference in the absolute, contralateral, and normalized ADCs (P = 0.091, 0.809, and 0.299, respectively), and the tumor detectability (P = 0.680) according to the menstrual cycle. Although ADCs of the IDC and normal glandular tissue in postmenopausal women were significantly lower than those in premenopausal women, the menstrual cycle did not affect tumor detectability and ADCs of IDC.
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Affiliation(s)
- Suyoung Shin
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Irwon-dong, Gangnam-gu, Seoul, 135-710, Republic of Korea
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Differential Diagnosis of Benign and Malignant Breast Tumors Using Apparent Diffusion Coefficient Value Measured Through Diffusion-Weighted Magnetic Resonance Imaging. J Comput Assist Tomogr 2015; 39:513-22. [DOI: 10.1097/rct.0000000000000226] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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Baikeev RF, Gubanov RA, Sadikov KK, Safina SZ, Muhamadiev FF, Sibgatullin TA. Dynamic properties of water in breast pathology depend on the histological compounds: distinguishing tissue malignancy by water diffusion coefficients. BMC Res Notes 2014; 7:887. [PMID: 25487139 PMCID: PMC4295355 DOI: 10.1186/1756-0500-7-887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2013] [Accepted: 11/18/2014] [Indexed: 11/11/2022] Open
Abstract
Background The parameters that characterize the intricate water diffusion in tumors may also reveal their distinct pathology. Specifically, characterization of breast cancer could be aided by diffusion magnetic resonance. The present in vitro study aimed to discover connections between the NMR biexponential diffusion parameters [fast diffusion phase (DFDP ), slow diffusion phase (DSDP ), and spin population of fast diffusion phase (P1)] and the histological constituents of nonmalignant (control) and malignant human breast tissue. It also investigates whether the diffusion coefficients indicate tissue status. Methods Post-surgical specimens of control (mastopathy and peritumoral tissues) and malignant human breast tissue were placed in an NMR spectrometer and diffusion sequences were applied. The resulting decay curves were analyzed by a biexponential model, and slow and fast diffusion parameters as well as percentage signal were identified. The same samples were also histologically examined and their percentage composition of several tissue constituents were measured: parenchyma (P), stroma (St), adipose tissue (AT), vessels (V) , pericellular edema (PCE), and perivascular edema (PVE). Correlations between the biexponential model parameters and tissue types were evaluated for different specimens. The effects of tissue composition on the biexponential model parameters, and the effects of histological and model parameters on cancer probability, were determined by non-linear regression. Results Meaningful relationships were found among the in vitro data. The dynamic parameters of water in breast tissue are stipulated by the histological constituents of the tissues (P, St, AT, PCE, and V). High coefficients of determination (R2) were obtained in the non-linear regression analysis: DFDP (R2 = 0.92), DSDP (R2 = 0.81), and P1(R2 = 0.93). In the cancer probability analysis, the informative value (R2) of the obtained equations of cancer probability in distinguishing tissue malignancy depended on the parameters input to the model. In order of increasing value, these equations were: cancer probability (P, St, AT, PCE, V) (R2 = 0.66), cancer probability (DFDP, DSDP)(R2 = 0.69), cancer probability (DFDP, DSDP, P1) (R2 = 0.85). Conclusion Histological tissue components are related to the diffusion biexponential model parameters. From these parameters, the relative probability of cancer in a given specimen can be determined with some certainty.
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Affiliation(s)
- Rustem F Baikeev
- Department of Biochemistry, Kazan State Medical University, Butlerova St,, 49, Kazan, Tatarstan, Russia.
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