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Liu H, Lao M, Zhang Y, Chang C, Yin Y, Wang R. Radiomics-based machine learning models for differentiating pathological subtypes in cervical cancer: a multicenter study. Front Oncol 2024; 14:1346336. [PMID: 39355130 PMCID: PMC11442173 DOI: 10.3389/fonc.2024.1346336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 08/27/2024] [Indexed: 10/03/2024] Open
Abstract
Purpose This study was designed to determine the diagnostic performance of fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) radiomics-based machine learning (ML) in the classification of cervical adenocarcinoma (AC) and squamous cell carcinoma (SCC). Methods Pretreatment 18F-FDG PET/CT data were retrospectively collected from patients who were diagnosed with locally advanced cervical cancer at two centers. Radiomics features were extracted and selected by the Pearson correlation coefficient and least absolute shrinkage and selection operator regression analysis. Six ML algorithms were then applied to establish models, and the best-performing classifier was selected based on accuracy, sensitivity, specificity, and area under the curve (AUC). The performance of different model was assessed and compared using the DeLong test. Results A total of 227 patients with locally advanced cervical cancer were enrolled in this study (N=136 for the training cohort, N=59 for the internal validation cohort, and N=32 for the external validation cohort). The PET radiomics model constructed based on the lightGBM algorithm had an accuracy of 0.915 and an AUC of 0.851 (95% confidence interval [CI], 0.715-0.986) in the internal validation cohort, which were higher than those of the CT radiomics model (accuracy: 0.661; AUC: 0.513 [95% CI, 0.339-0.688]). The DeLong test revealed no significant difference in AUC between the combined radiomics model and the PET radiomics model in either the training cohort (z=0.940, P=0.347) or the internal validation cohort (z=0.285, P=0.776). In the external validation cohort, the lightGBM-based PET radiomics model achieved good discrimination between SCC and AC (AUC = 0.730). Conclusions The lightGBM-based PET radiomics model had great potential to predict the fine histological subtypes of locally advanced cervical cancer and might serve as a promising noninvasive approach for the diagnosis and management of locally advanced cervical cancer.
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Affiliation(s)
- Huiling Liu
- Department of Radiation Oncology, The Third Affiliated Teaching Hospital of Xinjiang Medical University, Affiliated Cancer Hospital, Urumuqi, China
- Department of Radiation Oncology, Binzhou People's Hospital, Binzhou, China
| | - Mi Lao
- Department of Cardiology, Binzhou People's Hospital, Binzhou, China
| | - Yalin Zhang
- Department of Radiation Oncology, The Third Affiliated Teaching Hospital of Xinjiang Medical University, Affiliated Cancer Hospital, Urumuqi, China
| | - Cheng Chang
- Department of Nuclear Medicine, The Third Affiliated Teaching Hospital of Xinjiang Medical University, Affiliated Cancer Hospital, Urumuqi, China
| | - Yong Yin
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Ruozheng Wang
- Department of Radiation Oncology, The Third Affiliated Teaching Hospital of Xinjiang Medical University, Affiliated Cancer Hospital, Urumuqi, China
- Key Laboratory of Oncology of Xinjiang Uyghur Autonomous Region, Urumuqi, China
- Clinical Key Specialty of Radiotherapy of Xinjiang Uygur Autonomous Region, Urumuqi, China
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Wang K, Wu G. Whole-volume diffusion kurtosis magnetic resonance (MR) imaging histogram analysis of non-small cell lung cancer: correlation with histopathology and degree of tumor differentiation. Clin Radiol 2024; 79:e1072-e1080. [PMID: 38816262 DOI: 10.1016/j.crad.2024.04.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 04/24/2024] [Accepted: 04/29/2024] [Indexed: 06/01/2024]
Abstract
AIMS To evaluate the role of diffusion kurtosis imaging (DKI) histogram analysis in the characterization of non-small cell lung cancer (NSCLC) and to correlate DKI parameters with tumor cellularity. MATERIALS AND METHODS Sixty-four patients with pathologically diagnosed NSCLCs were evaluated by DKI on a 3-T scanner. Regions of interest (ROIs) were drawn on the map of b1000 manually. All NSCLCs were histologically graded according to the degree of tumor differentiation. Tumor cellularity was measured by the nuclear-to-cytoplasm (N/C) ratio and the number of tumor cell nuclei (NTCN), the expression of Ki-67 was detected using the streptavidin-peroxidase method. Histogram analysis was performed using voxel-based on raw data from each ROI. RESULTS NSCLCs were classified as grades 1, 2, and 3 according to differentiation degree. Histogram parameters of apparent diffusion coefficient (ADC) and DKI could discriminate between different grades of tumors (p<0.001). Receiver operating characteristic (ROC) curve analysis showed that Kapp 75th exhibited the best performance with an AUC of 0.936 and sensitivity/specificity of 95.74%/80% (p<0.001) in distinguishing grade 1 from grade 2, ADC mean exhibited the best performance with an AUC of 0.923 and sensitivity/specificity of 92.33%/86.67% (p<0.001) in distinguishing grade 2 from 3. N/C ratio and Ki-67 changed significantly with grade (p<0.01). Negative correlations were found between the ADC mean and the N/C ratio, Ki-67, Dapp mean and N/C ratio, whereas Kapp mean and N/C ratio, Ki-67 were positively correlated. CONCLUSIONS DKI histogram analysis could quantitatively characterize NSCLC with different grades by probing non-Gaussian diffusion properties related to changes in the tumor microenvironment or tissue complexities in the tumor.
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Affiliation(s)
- K Wang
- PET-CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan 430000, Hubei, China.
| | - G Wu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan 430000, Hubei, China
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Yang L, Hu H, Yang X, Yan Z, Shi G, Yang L, Wang Y, Han R, Yan X, Wang M, Ban X, Duan X. Whole-tumor histogram analysis of multiple non-Gaussian diffusion models at high b values for assessing cervical cancer. Abdom Radiol (NY) 2024; 49:2513-2524. [PMID: 38995401 DOI: 10.1007/s00261-024-04486-3] [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: 05/05/2024] [Revised: 06/26/2024] [Accepted: 06/30/2024] [Indexed: 07/13/2024]
Abstract
PURPOSE To assess the diagnostic potential of whole-tumor histogram analysis of multiple non-Gaussian diffusion models for differentiating cervical cancer (CC) aggressive status regarding of pathological types, differentiation degree, stage, and p16 expression. METHODS Patients were enrolled in this prospective single-center study from March 2022 to July 2023. Diffusion-weighted images (DWI) were obtained including 15 b-values (0 ~ 4000 s/mm2). Diffusion parameters derived from four non-Gaussian diffusion models including continuous-time random-walk (CTRW), diffusion-kurtosis imaging (DKI), fractional order calculus (FROC), and intravoxel incoherent motion (IVIM) were calculated, and their histogram features were analyzed. To select the most significant features and establish predictive models, univariate analysis and multivariate logistic regression were performed. Finally, we evaluated the diagnostic performance of our models by using receiver operating characteristic (ROC) analyses. RESULTS 89 women (mean age, 55 ± 11 years) with CC were enrolled in our study. The combined model, which incorporated the CTRW, DKI, FROC, and IVIM diffusion models, offered a significantly higher AUC than that from any individual models (0.836 vs. 0.664, 0.642, 0.651, 0.649, respectively; p < 0.05) in distinguishing cervical squamous cell cancer from cervical adenocarcinoma. To distinguish tumor differentiation degree, except the combined model showed a better predictive performance compared to the DKI model (AUC, 0.839 vs. 0.697, respectively; p < 0.05), no significant differences in AUCs were found among other individual models and combined model. To predict the International Federation of Gynecology and Obstetrics (FIGO) stage, only DKI and FROC model were established and there was no significant difference in predictive performance among different models. In terms of predicting p16 expression, the predictive ability of DKI model is significantly lower than that of FROC and combined model (AUC, 0.693 vs. 0.850, 0.859, respectively; p < 0.05). CONCLUSION Multiple non-Gaussian diffusion models with whole-tumor histogram analysis show great promise to assess the aggressive status of CC.
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Affiliation(s)
- Lu Yang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Huijun Hu
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Xiaojun Yang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Zhuoheng Yan
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Guangzi Shi
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, Guangdong, China
| | - Lingjie Yang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Yu Wang
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Riyu Han
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China
| | - Xu Yan
- MR Research Collaboration, Siemens Healthineers Ltd., Beijing, China
| | - Mengzhu Wang
- MR Research Collaboration, Siemens Healthineers Ltd., Beijing, China
| | - Xiaohua Ban
- Department of Radiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China.
| | - Xiaohui Duan
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China.
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, Guangdong, China.
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Yu Z, Zhihui Q, Linrui L, Long L, Qibing W. Machine Learning-Based Models for Assessing Postoperative Risk Factors in Patients with Cervical Cancer. Acad Radiol 2024; 31:1410-1418. [PMID: 37891091 DOI: 10.1016/j.acra.2023.09.031] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 09/21/2023] [Accepted: 09/21/2023] [Indexed: 10/29/2023]
Abstract
RATIONALE AND OBJECTIVES To investigate the value of machine learning-based radiomics, intravoxel incoherent motion (IVIM) diffusion-weighted imaging and its combined model in predicting the postoperative risk factors of parametrial infiltration (PI), lymph node metastasis (LNM), deep muscle invasion (DMI), lymph-vascular space invasion (LVSI), pathological type (PT), differentiation degree (DD), and Ki-67 expression level in patients with cervical cancer. MATERIALS AND METHODS The data of 180 patients with cervical cancer were retrospectively analyzed and randomized 2:1 into a training and validation group. The IVIM-DWI and radiomics parameters of primary lesions were measured in all patients. Seven machine learning methods were used to calculate the optimal radiomics score (Rad-score), which was combined with IVIM-DWI and clinical parameters to construct nomograms for predicting the risk factors of cervical cancer, with internal and external validation. RESULTS The diagnostic efficacy of the nomograms based on clinical and imaging parameters was significantly better than MRI assessment alone. The area under the curve (AUC) of nomograms and MRI for the assessment of PI, LNM, and DMI were 0.981 vs 0.868, 0.848 vs 0.639, and 0.896 vs 0.780, respectively. Nomograms also performed well in the assessment of LVSI, PT, DD, and Ki-67 expression levels, with AUC of 0.796, 0.854, 0.806, 0.839 and 0.840, 0.856, 0.810, 0.832 in the training and validation groups. CONCLUSION Machine learning-based nomograms can serve as a useful tool for assessing postoperative risk factors in patients with cervical cancer.
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Affiliation(s)
- Zhang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 81 Meishan Road, Hefei, Anhui 230000, China (Z.Y., Q.Z., L.L., W.Q.); Department of Radiology, West Branch of the First Affiliated Hospital of the University of Science and Technology of China, Hefei, Anhui 230001, China (Z.Y., L.L.)
| | - Qin Zhihui
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 81 Meishan Road, Hefei, Anhui 230000, China (Z.Y., Q.Z., L.L., W.Q.)
| | - Li Linrui
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 81 Meishan Road, Hefei, Anhui 230000, China (Z.Y., Q.Z., L.L., W.Q.); Department of Radiology, West Branch of the First Affiliated Hospital of the University of Science and Technology of China, Hefei, Anhui 230001, China (Z.Y., L.L.)
| | - Liu Long
- Department of Hepatobiliary and Pancreatic Surgery, The Second Hospital of Zhejiang University, Binjiang District, Zhejiang 310000, China (L.L.)
| | - Wu Qibing
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, 81 Meishan Road, Hefei, Anhui 230000, China (Z.Y., Q.Z., L.L., W.Q.).
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Zhang Z, Liu J, Zhang Y, Qu F, Grimm R, Cheng J, Wang W, Zhu J, Li S. T1 mapping as a quantitative imaging biomarker for diagnosing cervical cancer: a comparison with diffusion kurtosis imaging. BMC Med Imaging 2024; 24:16. [PMID: 38200447 PMCID: PMC10782683 DOI: 10.1186/s12880-024-01191-x] [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: 02/01/2023] [Accepted: 01/01/2024] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND T1 mapping can potentially quantitatively assess the intrinsic properties of tumors. This study was conducted to explore the ability of T1 mapping in distinguishing cervical cancer type, grade, and stage and compare the diagnostic performance of T1 mapping with diffusion kurtosis imaging (DKI). METHODS One hundred fifty-seven patients with pathologically confirmed cervical cancer were enrolled in this prospectively study. T1 mapping and DKI were performed. The native T1, difference between native and postcontrast T1 (T1diff), mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) were calculated. Cervical squamous cell carcinoma (CSCC) and adenocarcinoma (CAC), low- and high-grade carcinomas, and early- and advanced-stage groups were compared using area under the receiver operating characteristic (AUROC) curves. RESULTS The native T1 and MK were higher, and the MD and ADC were lower for CSCC than for CAC (all p < 0.05). Compared with low-grade CSCC, high-grade CSCC had decreased T1diff, MD, ADC, and increased MK (p < 0.05). Compared with low-grade CAC, high-grade CAC had decreased T1diff and increased MK (p < 0.05). Native T1 was significantly higher in the advanced-stage group than in the early-stage group (p < 0.05). The AUROC curves of native T1, MK, ADC and MD were 0,772, 0.731, 0.715, and 0.627, respectively, for distinguishing CSCC from CAC. The AUROC values were 0.762 between high- and low-grade CSCC and 0.835 between high- and low-grade CAC, with T1diff and MK showing the best discriminative values, respectively. For distinguishing between advanced-stage and early-stage cervical cancer, only the AUROC of native T1 was statistically significant (AUROC = 0.651, p = 0.002). CONCLUSIONS Compared with DKI-derived parameters, native T1 exhibits better efficacy for identifying cervical cancer subtype and stage, and T1diff exhibits comparable discriminative value for cervical cancer grade.
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Affiliation(s)
- Zanxia Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, 450052, Zhengzhou, Henan, China
| | - Jie Liu
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, 450052, Zhengzhou, Henan, China
| | - Yong Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, 450052, Zhengzhou, Henan, China
| | - Feifei Qu
- MR Collaboration, Siemens Healthcare Ltd, Beijing, China
| | - Robert Grimm
- MR Application, Siemens Healthcare GmbH, Predevelopment, Erlangen, Germany
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, 450052, Zhengzhou, Henan, China
| | - Weijian Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, 450052, Zhengzhou, Henan, China
| | - Jinxia Zhu
- MR Collaboration, Siemens Healthcare Ltd, Beijing, China
| | - Shujian Li
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, 450052, Zhengzhou, Henan, China.
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Li S, Liu J, Zhang Z, Wang W, Lu H, Lin L, Zhang Y, Cheng J. Added-value of 3D amide proton transfer MRI in assessing prognostic factors of cervical cancer: a comparative study with multiple model diffusion-weighted imaging. Quant Imaging Med Surg 2023; 13:8157-8172. [PMID: 38106243 PMCID: PMC10722001 DOI: 10.21037/qims-23-324] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 09/22/2023] [Indexed: 12/19/2023]
Abstract
Background Amide proton transfer (APT) imaging has been gradually applied to cervical cancer, yet the relationships between APT and multiple model diffusion-weighted imaging (DWI) have yet to be investigated. This study attempted to evaluate the added value of 3-dimensional (3D) APT imaging to multiple model DWI for assessing prognostic factors of cervical cancer. Methods This prospective diagnostic study was conducted in The First Affiliated Hospital of Zhengzhou University. A total of 88 consecutive patients with cervical cancer underwent APT imaging and DWI with 11 b-values (0-2,000 s/mm2). The apparent diffusion coefficient (ADC), pure molecular diffusion (D), perfusion fraction (f), pseudo-diffusion (D*), mean kurtosis (MK), and mean diffusivity (MD) were calculated based on mono-exponential, bi-exponential, and kurtosis models. The mean, minimum, and maximum values of APT signal intensity (APT SI) and DWI-derived metrics were compared based on tumor stages, subtypes, grades, and lymphovascular space invasion status by Student's t-test or Mann-Whitney U test. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the parameters. Results APT SImax, APT SImin, MKmean, and MKmax showed significant differences between adenocarcinoma (AC) and squamous cell carcinoma (SCC) (all P<0.05). APT SImean, APT SImax, and MKmax were higher and ADCmin, Dmean, Dmin, and MDmin were lower in the high-grade tumor than in low-grade tumor (all P<0.05). For distinguishing lymphovascular space invasion, only MKmean showed significant difference (P=0.010). APT SImax [odds ratio (OR) =2.347, P=0.029], APT SImin (OR =0.352; P=0.024), and MKmean (OR =6.523; P=0.001) were the independent predictors for tumor subtype, and APT SImax (OR =2.885; P=0.044), MDmin (OR =0.155, P=0.012) were the independent predictors for histological grade of cervical cancer. When APT SImin and APT SImax was combined with MKmean and MKmax, the diagnostic performance was significantly improved for differentiating AC and AC [area under the curve (AUC): 0.908, sensitivity: 87.5%; specificity: 83.3%; P<0.001]. The combination of APT SImean, APT SImax, ADCmin, MKmax, and MDmin demonstrated the highest diagnostic performance for predicting tumor grade (AUC: 0.903, sensitivity: 78.6%; specificity: 88.9%; P<0.001). Conclusions Addition of APT to DWI may improve the ability to noninvasively predict poor prognostic factors of cervical cancer.
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Affiliation(s)
- Shujian Li
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jie Liu
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zanxia Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Weijian Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Huifang Lu
- Department of Gynecology and Obstetrics, Huaihe Hospital of Henan University, Kaifeng, China
| | - Liangjie Lin
- Advanced Technical Support, Philips Healthcare, Beijing, China
| | - Yong Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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He Y, Wang M, Yi S, Lu Y, Ren J, Zhou P, Xu K. Diffusion-weighted imaging in the assessment of cervical cancer: comparison of reduced field-of-view diffusion-weighted imaging and conventional techniques. Acta Radiol 2023; 64:2485-2491. [PMID: 37545177 DOI: 10.1177/02841851231183870] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
BACKGROUND Cervical cancer (CC) is the second most common cancer in women worldwide. Diffusion-weighted imaging (DWI) plays an important role in the diagnosis of CC, but the conventional techniques are affected by many factors. PURPOSE To compare reduced-field-of-view (r-FOV) and full-field-of-view (f-FOV) DWI in the diagnosis of CC. MATERIAL AND METHODS Preoperative magnetic resonance imaging (MRI) with r-FOV and f-FOV DWI images were collected. Two radiologists reviewed the images using a subjective 4-point scale for anatomical features, magnetic susceptibility artifacts, visual distortion, and overall diagnostic confidence for r-FOV and f-FOV DWI. The objective features included the region of interest (ROI) signal intensity of the cervical lesion (SIlesion) and gluteus maximus muscle (SIgluteus), standard deviation of the background noise (SDbackground), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The differences of measured apparent diffusion coefficient (ADC) values between the two examinations in pathological grades and FIGO tumor stages were compared. RESULTS A total of 200 patients were included (170 with squamous cell carcinoma and 30 with adenocarcinoma). The scores of anatomical features, magnetic susceptibility artifacts, visual distortion, and overall diagnostic confidence for r-FOV DWI were significantly higher than those for f-FOV DWI. There was no difference in SNR and CNR between r-FOV DWI and f-FOV DWI. There were significant differences in ADC values between the two groups in all comparisons (P < 0.05). CONCLUSION Compared with f-FOV DWI, r-FOV DWI might provide clearer imaging, fewer artifacts, less distortion, and higher image quality for the diagnosis of CC and might assist in the detection of CC.
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Affiliation(s)
- Yakun He
- Department of radiology, Sichuan Cancer Hospital, Chengdu, PR China
| | - Min Wang
- Department of radiology, Sichuan Cancer Hospital, Chengdu, PR China
| | - Siqi Yi
- Department of radiology, Sichuan Cancer Hospital, Chengdu, PR China
| | - Yujie Lu
- Department of radiology, Sichuan Cancer Hospital, Chengdu, PR China
| | - Jing Ren
- Department of radiology, Sichuan Cancer Hospital, Chengdu, PR China
| | - Peng Zhou
- Department of radiology, Sichuan Cancer Hospital, Chengdu, PR China
| | - Ke Xu
- Department of Otolaryngology-Head & Neck Surgery, West China Hospital, Sichuan University, Chengdu, PR China
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Li S, Liu J, Zhang W, Lu H, Wang W, Lin L, Zhang Y, Cheng J. T1 mapping and multimodel diffusion-weighted imaging in the assessment of cervical cancer: a preliminary study. Br J Radiol 2023; 96:20220952. [PMID: 37183908 PMCID: PMC10392640 DOI: 10.1259/bjr.20220952] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 03/22/2023] [Accepted: 04/23/2023] [Indexed: 05/16/2023] Open
Abstract
OBJECTIVE To evaluate the clinical feasibility of T1 mapping and multimodel diffusion-weighted imaging (DWI) for assessing the histological type, grade, and lymphovascular space invasion (LVSI) of cervical cancer. METHODS Eighty patients with cervical cancer and 43 patients with a normal cervix underwent T1 mapping and DWI with 11 b-values (0-2000 s/mm2). Monoexponential, biexponential, and kurtosis models were fitted to calculate the apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion (D*), perfusion fraction (f), mean diffusivity (MD), and mean kurtosis (MK). Native T1 and DWI-derived parameters (ADCmean, ADCmin, Dmean, Dmin, D*, f, MDmean, MDmin, MKmean, and MKmax) were compared based on histological type, grade, and LVSI status. RESULTS Native T1 and DWI-derived parameters differed significantly between cervical cancer and normal cervix (all p < 0.05), except D* (p = 0.637). Native T1 and MKmean varied significantly between squamous cell carcinoma (SCC) and adenocarcinoma (both p < 0.05). ADCmin, Dmin, and MDmin were significantly lower while MKmax was significantly higher in the high-grade SCC group than in the low-grade SCC group (all p < 0.05). LVSI-positive SCC had a significantly higher MKmean than LVSI-negative SCC (p < 0.05). CONCLUSION Both T1 mapping and multimodel DWI can effectively differentiate cervical cancer from a normal cervix and cervical adenocarcinoma from SCC. Furthermore, multimodel DWI may provide quantitative metrics for non-invasively predicting histological grade and LVSI status in SCC patients. ADVANCES IN KNOWLEDGE Combined use of T1 mapping and multimodel DWI may provide more comprehensive information for non-invasive pre-operative evaluation of cervical cancer.
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Affiliation(s)
- Shujian Li
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jie Liu
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Wenhua Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Huifang Lu
- Department of Gynecology and Obstetrics, Huaihe Hospital of Henan University, Kaifeng, China
| | - Weijian Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Liangjie Lin
- Advanced Technical Support, Philips Healthcare, Beijing, China
| | - Yong Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Zhang Z, Shen S, Ma J, Qi T, Gao C, Hu X, Han D, Huang Y. Sequential multi-parametric MRI in assessment of the histological subtype and features in the malignant pleural mesothelioma xenografts. Heliyon 2023; 9:e15237. [PMID: 37123972 PMCID: PMC10130770 DOI: 10.1016/j.heliyon.2023.e15237] [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: 10/27/2022] [Revised: 02/05/2023] [Accepted: 03/30/2023] [Indexed: 05/02/2023] Open
Abstract
Objective It is still a challenge to find a noninvasive technique to distinguish the histological subtypes of malignant pleural mesothelioma (MPM) and characterize the development of related histological features. We investigated the potential value of multiparametric MRI in the assessment of the histological subtype and development of histologic features in the MPM xenograft model. Methods MPM xenograft models were developed by injecting tumour cells into the right axillary space of nude mice. The T1, T2, R2*, T2*, apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), and perfusion fraction (f) at 14 d, 28 d, and 42 d were measured and compared between the epithelial and biphasic MPM. Correlations between multiparametric MRI parameters and histologic features, including necrotic fraction (NF) and microvessel density (MVD), were analysed. Results This study found that T2, T2* and IVIM-DWI parameters can reflect the spatial and temporal heterogeneity of MPM. Compared to the epithelial MPM, T2 and T2* were higher and ADC, D, D*, and f were lower in the biphasic MPM (P < 0.05). MRI parameters were different in different stages of epithelial and biphasic MPM. Moderate correlations were found between ADC and tumor volume and NF in the epithelial MPM, and there was a correlation between f and tumor volume and NF and MVD in the two groups. Conclusion MRI parameters changed with tumor progression in a xenograft model of MPM. MRI parameters may provide useful biomarkers for evaluating the histological subtype and histological features development of MPM.
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Affiliation(s)
- Zhenghua Zhang
- Medical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, 650000, China
| | - Shasha Shen
- Medical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, 650000, China
| | - Jiyao Ma
- Medical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, 650000, China
| | - Tianfu Qi
- Medical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, 650000, China
| | - Chao Gao
- Medical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, 650000, China
| | - Xiong Hu
- Pathology Department, First Affiliated Hospital of Kunming Medical University, Kunming, 650000, China
| | - Dan Han
- Medical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, 650000, China
- Corresponding author.
| | - Yilong Huang
- Medical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, 650000, China
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Utility of mono-exponential, bi-exponential, and stretched exponential signal models of intravoxel incoherent motion (IVIM) to predict prognosis and survival risk in laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) patients after chemoradiotherapy. Jpn J Radiol 2023:10.1007/s11604-023-01399-x. [PMID: 36847996 DOI: 10.1007/s11604-023-01399-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 02/03/2023] [Indexed: 03/01/2023]
Abstract
PURPOSE To investigate the predictive power of mono-exponential, bi-exponential, and stretched exponential signal models of intravoxel incoherent motion (IVIM) in prognosis and survival risk of laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) patients after chemoradiotherapy. MATERIALS AND METHODS Forty-five patients with laryngeal or hypopharyngeal squamous cell carcinoma were retrospectively enrolled. All patients had undergone pretreatment IVIM examination, subsequently, mean apparent diffusion coefficient (ADCmean), maximum ADC (ADCmax), minimum ADC (ADCmin) and ADCrange (ADCmax - ADCmean) by mono-exponential model, true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f) by bi-exponential model, distributed diffusion coefficient (DDC), and diffusion heterogeneity index (α) by stretched exponential model were measured. Survival data were collected for 5 years. RESULTS Thirty-one cases were in the treatment failure group and fourteen cases were in the local control group. Significantly lower ADCmean, ADCmax, ADCmin, D, f, and higher D* values were observed in the treatment failure group than in the local control group (p < 0.05). D* had the greatest AUC of 0.802, with sensitivity and specificity of 77.4 and 85.7% when D* was 38.85 × 10-3 mm2/s. Kaplan-Meier survival analysis showed that the curves of N stage, ADCmean, ADCmax, ADCmin, D, D*, f, DDC, and α values were significant. Multivariate Cox regression analysis showed ADCmean and D* were independently correlated with progression-free survival (PFS) (hazard ratio [HR] = 0.125, p = 0.001; HR = 1.008, p = 0.002, respectively). CONCLUSION The pretreatment parameters of mono-exponential and bi-exponential models were significantly correlated with prognosis of LHSCC, ADCmean and D* values were independent factors for survival risk prediction.
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Duan Z, Fang S, Hu J, Tao J, Zhang K, Deng X, Wang S, Liu Y. Correlation of Intravoxel Incoherent Motion and Diffusion Kurtosis
MR
Imaging Models With Reactive Stromal Grade in Prostate Cancer. J Magn Reson Imaging 2022. [DOI: 10.1002/jmri.28546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 11/16/2022] [Accepted: 11/17/2022] [Indexed: 11/30/2022] Open
Affiliation(s)
- Zhiqing Duan
- Department of Radiology, The Second Hospital Dalian Medical University Dalian People's Republic of China
| | - Shaobo Fang
- Department of Medical Imaging Zhengzhou University People's Hospital & Henan Provincial People's Hospital Zhengzhou Henan People's Republic of China
- Academy of Medical Sciences Zhengzhou University Zhengzhou Henan People's Republic of China
| | - Jiawei Hu
- Department of Radiology, The Second Hospital Dalian Medical University Dalian People's Republic of China
| | - Juan Tao
- Department of Pathology, The Second Hospital Dalian Medical University Dalian People's Republic of China
| | - Kai Zhang
- Department of Radiology, The Second Hospital Dalian Medical University Dalian People's Republic of China
| | - Xiyang Deng
- Department of Radiology, The Second Hospital Dalian Medical University Dalian People's Republic of China
| | - Shaowu Wang
- Department of Radiology, The Second Hospital Dalian Medical University Dalian People's Republic of China
| | - Yajie Liu
- Department of Radiology, The Second Hospital Dalian Medical University Dalian People's Republic of China
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Qin YL, Wang S, Chen F, Liu HX, Yue KT, Wang XZ, Ning HF, Dong P, Yu XR, Wang GZ. Prediction of outcomes by diffusion kurtosis imaging in patients with large (≥5 cm) hepatocellular carcinoma after liver resection: A retrospective study. Front Oncol 2022; 12:939358. [DOI: 10.3389/fonc.2022.939358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 10/18/2022] [Indexed: 11/18/2022] Open
Abstract
PurposeTo evaluate preoperative diffusion kurtosis imaging (DKI) in predicting the outcomes of large hepatocellular carcinoma (HCC) after liver resection (LR).Materials and methodsFrom January 2015 to December 2017, patients with a large (≥5cm) HCC who underwent preoperative DKI were retrospectively reviewed. The correlations of the mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) with microvascular invasion (MVI) or histological grade were analyzed. Cox regression analyses were performed to identify the predictors of recurrence-free survival (RFS) and overall survival (OS). A nomogram to predict RFS was established. P<0.05 was considered as statistically significant.ResultsA total of 97 patients (59 males and 38 females, 56.0 ± 10.9 years) were included in this study. The MK, MD, and ADC values were correlated with MVI or histological grade (P<0.01). With a median follow-up time of 41.2 months (range 12-69 months), 67 patients (69.1%) experienced recurrence and 41 patients (42.3%) were still alive. The median RFS and OS periods after LR were 29 and 45 months, respectively. The 1-, 3-, and 5-year RFS and OS rates were 88.7%, 41.2%, and 21.7% and 99.0%, 68.3%, and 25.6%, respectively. MK (P<0.001), PVT (P<0.001), and ADC (P=0.033) were identified as independent predictor factors for RFS. A nomogram including the MK value for RFS showed the best performance, and the C-index was 0.895.ConclusionThe MK value obtained from DKI is a potential predictive factor for recurrence and poor survival, which could provide valuable information for guiding the efficacy of LR in patients with large HCC.
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Wang W, Jiao Y, Zhang L, Fu C, Zhu X, Wang Q, Gu Y. Multiparametric MRI-based radiomics analysis: differentiation of subtypes of cervical cancer in the early stage. Acta Radiol 2022; 63:847-856. [PMID: 33975448 DOI: 10.1177/02841851211014188] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND There are significant differences in outcomes for different histological subtypes of cervical cancer (CC). Yet, it is difficult to distinguish CC subtypes using non-invasive methods. PURPOSE To investigate whether multiparametric magnetic resonance imaging (MRI)-based radiomics analysis can differentiate CC subtypes and explore tumor heterogeneity. MATERIAL AND METHODS This study retrospectively analyzed 96 patients with CC (squamous cell carcinoma [SCC] = 50, adenocarcinoma [AC] = 46) who underwent pelvic MRI before surgery. Radiomics features were extracted from the tumor volumes on five sequences (sagittal T2-weighted imaging [T2SAG], transverse T2-weighted imaging [T2TRA], sagittal contrast-enhanced T1-weighted imaging [CESAG], transverse contrast-enhanced T1-weighted imaging [CETRA], and apparent diffusion coefficient [ADC]). Clustering and logistic regression were used to examine the distinguishing capabilities of radiomics features extracted from five different MR sequences. RESULTS Among the 105 extracted radiomics features, there were 51, 38, 37, and 2 features that showed intergroup differences for T2SAG, T2TRA, ADC, and CESAG, respectively (all P < 0.05). AC had greater textural heterogeneity than SCC (P < 0.05). Upon unsupervised clustering of significantly different features, T2SAG achieved the highest accuracy (0.844; sensitivity = 0.920; specificity = 0.761). The largest area under the curve (AUC) for classification ability was 0.86 for T2SAG. Hence, the radiomics model from five combined MR sequences (AUC = 0.89; accuracy = 0.81; sensitivity = 0.67; specificity = 0.94) exhibited better differentiation ability than any MR sequence alone. CONCLUSION Multiparametric MRI-based radiomics models may be a promising method to differentiate AC and SCC. AC showed more heterogeneous features than SCC.
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Affiliation(s)
- Wei Wang
- Department of Radiology, Fudan University Shanghai Cancer Center (FUSCC), Shanghai, PR China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, PR China
| | - YiNing Jiao
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, PR China
| | - LiChi Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, PR China
| | - Caixia Fu
- MR Applications Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, PR China
| | - XiaoLi Zhu
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, PR China
- Department of Pathology, Fudan University Shanghai Cancer Center (FUSCC), Shanghai, PR China
| | - Qian Wang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, PR China
| | - Yajia Gu
- Department of Radiology, Fudan University Shanghai Cancer Center (FUSCC), Shanghai, PR China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, PR China
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Shao X, An L, Liu H, Feng H, Zheng L, Dai Y, Yu B, Zhang J. Cervical Carcinoma: Evaluation Using Diffusion MRI With a Fractional Order Calculus Model and its Correlation With Histopathologic Findings. Front Oncol 2022; 12:851677. [PMID: 35480091 PMCID: PMC9036957 DOI: 10.3389/fonc.2022.851677] [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: 01/10/2022] [Accepted: 03/03/2022] [Indexed: 11/13/2022] Open
Abstract
Objective The objective of the study is to investigate the feasibility of using the fractional order calculus (FROC) model to reflect tumor subtypes and histological grades of cervical carcinoma. Methods Sixty patients with untreated cervical carcinoma underwent multi-b-value diffusion-weighted imaging (DWI) at 3.0T magnetic resonance imaging (MRI). The mono-exponential and the FROC models were fitted. The differences in the histological subtypes and grades were evaluated by the Mann–Whitney U test. Receiver operating characteristic (ROC) analyses were performed to assess the diagnostic performance and to determine the best predictor for both univariate analysis and multivariate analysis. Differences between ROC curves were tested using the Hanley and McNeil test, while the sensitivity, specificity, and accuracy were compared using the McNemar test. P-value <0.05 was considered as significant difference. The Bonferroni corrections were applied to reduce problems associated with multiple comparisons. Results Only the parameter β, derived from the FROC model could differentiate cervical carcinoma subtypes (P = 0.03) and the squamous cell carcinoma (SCC) lesions exhibited significantly lower β than that in the adenocarcinoma (ACA) lesions. All the individual parameters, namely, ADC, β, D, and μ derived from the FROC model, could differentiate low-grade cervical carcinomas from high-grade ones (P = 0.022, 0.009, 0.004, and 0.015, respectively). The combination of all the FROC parameters showed the best overall performance, providing the highest sensitivity (81.2%) and AUC (0.829). Conclusion The parameters derived from the FROC model were able to differentiate the subtypes and grades of cervical carcinoma.
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Affiliation(s)
- Xian Shao
- Department of Anesthesiology, The Fourth Hospital of Shijiazhuang, Shijiazhuang, China
| | - Li An
- Department of Anesthesiology, The Fourth Hospital of Shijiazhuang, Shijiazhuang, China
| | - Hui Liu
- Department of Radiology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Hui Feng
- Department of Radiology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Liyun Zheng
- MR Collaboration, Central Research Institute, United Imaging Healthcare, Shanghai, China
| | - Yongming Dai
- MR Collaboration, Central Research Institute, United Imaging Healthcare, Shanghai, China
| | - Bin Yu
- Department of Emergency, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Jin Zhang
- Department of Anesthesiology, The Fourth Hospital of Shijiazhuang, Shijiazhuang, China
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Dolciami M, Capuani S, Celli V, Maiuro A, Pernazza A, Palaia I, Di Donato V, Santangelo G, Rizzo SMR, Ricci P, Della Rocca C, Catalano C, Manganaro L. Intravoxel Incoherent Motion (IVIM) MR Quantification in Locally Advanced Cervical Cancer (LACC): Preliminary Study on Assessment of Tumor Aggressiveness and Response to Neoadjuvant Chemotherapy. J Pers Med 2022; 12:jpm12040638. [PMID: 35455755 PMCID: PMC9027075 DOI: 10.3390/jpm12040638] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 04/05/2022] [Accepted: 04/11/2022] [Indexed: 01/27/2023] Open
Abstract
The aim of this study was to determine whether quantitative parameters obtained from intravoxel incoherent motion (IVIM) model at baseline magnetic resonance imaging (MRI) correlate with histological parameters and response to neoadjuvant chemotherapy in patients with locally advanced cervical cancer (LACC). Methods: Twenty patients with biopsy-proven cervical cancer, staged as LACC on baseline MRI and addressed for neoadjuvant chemotherapy were enrolled. At treatment completion, tumor response was assessed with a follow-up MRI evaluated using the revised response evaluation criteria in solid tumors (RECIST; version 1.1), and patients were considered good responders (GR) if they had complete response or partial remission, and poor responders/non-responders (PR/NR) if they had stable or progressive disease. MRI protocol included conventional diffusion-weighted imaging (DWI; b = 0 and 1000 s/mm2) and IVIM acquisition using eight b-values (range: 0–1500 s/mm2). MR-images were analyzed using a dedicated software to obtain quantitative parameters: diffusion (D), pseudo-diffusion (D*), and perfusion fraction (fp) from the IVIM model; apparent diffusion coefficient (ADC) from conventional DWI. Histologic subtype, grading, and tumor-infiltrating lymphocytes (TILs) were assessed in each LACC. Results: D showed significantly higher values in GR patients (p = 0.001) and in moderate/high TILs (p = 0.018). Fp showed significantly higher values in squamous cell tumors (p = 0.006). Conclusions: D extracted from the IVIM model could represent a promising tool to identify tumor aggressiveness and predict response to therapy.
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Affiliation(s)
- Miriam Dolciami
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (M.D.); (V.C.); (A.P.); (P.R.); (C.D.R.); (C.C.)
| | - Silvia Capuani
- CNR Institute for Complex Systems (ISC), Physics Department, Sapienza University of Rome, 00161 Rome, Italy;
| | - Veronica Celli
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (M.D.); (V.C.); (A.P.); (P.R.); (C.D.R.); (C.C.)
| | | | - Angelina Pernazza
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (M.D.); (V.C.); (A.P.); (P.R.); (C.D.R.); (C.C.)
| | - Innocenza Palaia
- Department of Maternal and Child Health and Urological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (I.P.); (V.D.D.); (G.S.)
| | - Violante Di Donato
- Department of Maternal and Child Health and Urological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (I.P.); (V.D.D.); (G.S.)
| | - Giusi Santangelo
- Department of Maternal and Child Health and Urological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (I.P.); (V.D.D.); (G.S.)
| | - Stefania Maria Rita Rizzo
- Istituto di Imaging della Svizzera Italiana (IIMSI), Ente Ospedaliero Cantonale (EOC), 6900 Lugano, Switzerland;
- Facoltà di Scienze Biomediche, Università della Svizzera Italiana, 6900 Lugano, Switzerland
| | - Paolo Ricci
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (M.D.); (V.C.); (A.P.); (P.R.); (C.D.R.); (C.C.)
- Unit of Emergency Radiology, Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy
| | - Carlo Della Rocca
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (M.D.); (V.C.); (A.P.); (P.R.); (C.D.R.); (C.C.)
| | - Carlo Catalano
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (M.D.); (V.C.); (A.P.); (P.R.); (C.D.R.); (C.C.)
| | - Lucia Manganaro
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (M.D.); (V.C.); (A.P.); (P.R.); (C.D.R.); (C.C.)
- Correspondence: ; Tel.: +39-3338151295
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Malek M, Rahmani M, Pourashraf M, Amanpour-Gharaei B, Zamani N, Farsi M, Ahmadinejad N, Raminfard S. Prediction of lymphovascular space invasion in cervical carcinoma using diffusion kurtosis imaging. Cancer Treat Res Commun 2022; 31:100559. [PMID: 35460974 DOI: 10.1016/j.ctarc.2022.100559] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 04/02/2022] [Accepted: 04/06/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND This study aimed to investigate the potential relationship between diffusion kurtosis imaging (DKI)- derived parameters and lymphovascular space invasion (LVSI) in patients with cervical carcinoma. PATIENTS AND METHODS This prospective study included 30 patients with cervical carcinoma. The patients underwent MRI, diffusion-weighted imaging (DWI), and DKI prior to surgery. The surgical pathology results were accepted as the reference standard for determining the LVSI status. The DKI-derived parameters, including mean diffusivity (MD) and mean kurtosis (MK), were measured. The apparent diffusion coefficient (ADC) value was also assessed. RESULTS The MD value of LVSI positive cervical carcinomas was significantly lower than LVSI negative carcinomas (p-value = 0.01). MK value was significantly higher in LVSI positive tumors (p-value = 0.01). However, the ADC value did not show a significant difference between LVSI positive and LVSI negative tumors (p-value = 0.2). MD and MK parameters showed similar diagnostic accuracy in identifying the LVSI status, with the area under the curve of 0.77 and 0.78, respectively. CONCLUSION In this study, DKI-derived parameters were associated with the LVSI status in cervical carcinomas. Further studies with larger sample size are required to confirm these results.
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Affiliation(s)
- Mahrooz Malek
- Department of Radiology, Imam Khomeini Hospital Complex (IKHC), Tehran University of Medical Sciences (TUMS), Tehran, Iran; Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Maryam Rahmani
- Department of Radiology, Imam Khomeini Hospital Complex (IKHC), Tehran University of Medical Sciences (TUMS), Tehran, Iran; Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Maryam Pourashraf
- Department of Radiology, Imam Khomeini Hospital Complex (IKHC), Tehran University of Medical Sciences (TUMS), Tehran, Iran; Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences (TUMS), Tehran, Iran.
| | - Behzad Amanpour-Gharaei
- Omid Institute for Advanced Biomodels, Imam Khomeini Hospital Complex (IKHC), Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Narges Zamani
- Department of Gynecology Oncology, Vali-e-Asr Hospital, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Maryam Farsi
- Medical Imaging Center, Imam Khomeini Hospital Complex (IKHC), Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Nasrin Ahmadinejad
- Department of Radiology, Imam Khomeini Hospital Complex (IKHC), Tehran University of Medical Sciences (TUMS), Tehran, Iran; Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Samira Raminfard
- Department of Neuroimaging and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran
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Song J, Lu Y, Wang X, Peng W, Lin W, Hou Z, Yan Z. A comparative study of four diffusion-weighted imaging models in the diagnosis of cervical cancer. Acta Radiol 2022; 63:536-544. [PMID: 33745294 DOI: 10.1177/02841851211002017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
BACKGROUND Most commonly used diffusion-weighted imaging (DWI) models include intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), stretched exponential model (SEM), and mono-exponential model (MEM). Previous studies of the four models were inconsistent on which model was more effective in distinguishing cervical cancer from normal cervical tissue. PURPOSE To assess the performance of four DWI models in characterizing cervical cancer and normal cervical tissue. MATERIAL AND METHODS Forty-seven women with suspected cervical carcinoma underwent DWI using eight b-values before treatment. Imaging parameters, calculated using IVIM, SEM, DKI, and MEM, were compared between cervical cancer and normal cervical tissue. The diagnostic performance of the models was evaluated using independent t-test, Mann-Whitney U test, receiver operating characteristic (ROC) curve analysis, and multivariate logistic regression analysis. RESULTS All parameters except pseudo-diffusion coefficient (D*) differed significantly between cervical cancer and normal cervical tissue (P < 0.001). Through logistic regression analysis, all combined models showed a significant improvement in area under the ROC curve (AUC) compared to individual DWI parameters. The model with combined IVIM parameters had a larger AUC value compared to those of other combined models (P < 0.05). CONCLUSION All four DWI models are useful for differentiating cervical cancer from normal cervical tissue and IVIM may be the optimal model.
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Affiliation(s)
- Jiao Song
- Department of Radiology, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, PR China
| | - Yi Lu
- Department of Radiology, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, PR China
| | - Xue Wang
- Department of Radiology, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, PR China
| | - Wenwen Peng
- Department of Radiology, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, PR China
| | - Wenxiao Lin
- Department of Radiology, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, PR China
| | - Zujun Hou
- Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu, PR China
| | - Zhihan Yan
- Department of Radiology, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, PR China
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Shi B, Dong JN, Zhang LX, Li CP, Gao F, Li NY, Wang CB, Fang X, Wang PP. A Combination Analysis of IVIM-DWI Biomarkers and T2WI-Based Texture Features for Tumor Differentiation Grade of Cervical Squamous Cell Carcinoma. CONTRAST MEDIA & MOLECULAR IMAGING 2022; 2022:2837905. [PMID: 35360261 PMCID: PMC8947887 DOI: 10.1155/2022/2837905] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 02/18/2022] [Indexed: 11/18/2022]
Abstract
Purpose To explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and texture analysis on T2-weighted imaging (T2WI) for evaluating pathological differentiation of cervical squamous cell carcinoma. Method This retrospective study included a total of 138 patients with pathologically confirmed poor/moderate/well-differentiated (71/49/18) who underwent conventional MRI and IVIM-DWI scans. The values of ADC, D, D ∗ , and f and 58 T2WI-based texture features (18 histogram features, 24 gray-level co-occurrence matrix features, and 16 gray-level run length matrix features) were obtained. Multiple comparison, correlation, and regression analyses were used. Results For IVIM-DWI, the ADC, D, D ∗ , and f were significantly different among the three groups (p < 0.05). ADC, D, and D ∗ were positively correlated with pathological differentiation (r = 0.262, 0.401, 0.401; p < 0.05), while the correlation was negative for f (r = -0.221; p < 0.05). The comparison of 52 parameters of texture analysis on T2WI reached statistically significant levels (p < 0.05). Multivariate logistic regression analysis incorporated significant IVIM-DWI, and texture features on T2WI showed good diagnostic performance both in the four differentiation groups (poorly vs. moderately, area under the curve(AUC) = 0.797; moderately vs. well, AUC = 0.954; poorly vs. moderately and well, AUC = 0.795; and well vs. moderately and poorly, AUC = 0.952). The AUCs of each parameters alone were smaller than that of each regression model (0.503∼0.684, 0.547∼0.805, 0.511∼0.712, and 0.636∼0.792, respectively; pairwise comparison of ROC curves between regression model and individual variables, p < 0.05). Conclusions IVIM-DWI biomarkers and T2WI-based texture features had potential to evaluate the pathological differentiation of cervical squamous cell carcinoma. The combination of IVIM-DWI with texture analysis improved the predictive performance.
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Affiliation(s)
- Bin Shi
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Provincial Cancer Hospital, Hefei, 230031, China
| | - Jiang-Ning Dong
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Provincial Cancer Hospital, Hefei, 230031, China
| | - Li-Xiang Zhang
- Department of Radiology, The Third Affiliated Hospital of Xinxiang Medical College, Xinxiang, Henan 453003, China
| | - Cui-Ping Li
- Anhui Medical University, Hefei, Anhui 230000, China
| | - Fei Gao
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Provincial Cancer Hospital, Hefei, 230031, China
| | - Nai-Yu Li
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Provincial Cancer Hospital, Hefei, 230031, China
| | - Chuan-Bin Wang
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Provincial Cancer Hospital, Hefei, 230031, China
| | - Xin Fang
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Provincial Cancer Hospital, Hefei, 230031, China
| | - Pei-Pei Wang
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Provincial Cancer Hospital, Hefei, 230031, China
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Hou M, Song K, Ren J, Wang K, Guo J, Niu Y, Li Z, Han D. Comparative analysis of the value of amide proton transfer-weighted imaging and diffusion kurtosis imaging in evaluating the histological grade of cervical squamous carcinoma. BMC Cancer 2022; 22:87. [PMID: 35057777 PMCID: PMC8780242 DOI: 10.1186/s12885-022-09205-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 01/14/2022] [Indexed: 01/21/2023] Open
Abstract
Background Uterine cervical cancer (UCC) was the fourth leading cause of cancer death among women worldwide. The conventional MRI hardly revealing the microstructure information. This study aimed to compare the value of amide proton transfer-weighted imaging (APTWI) and diffusion kurtosis imaging (DKI) in evaluating the histological grade of cervical squamous carcinoma (CSC) in addition to routine diffusion-weighted imaging (DWI). Methods Forty-six patients with CSC underwent pelvic DKI and APTWI. The magnetization transfer ratio asymmetry (MTRasym), apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) were calculated and compared based on the histological grade. Correlation coefficients between each parameter and histological grade were calculated. Results The MTRasym and MK values of grade 1 (G1) were significantly lower than those of grade 2 (G2), and those parameters of G2 were significantly lower than those of grade 3 (G3). The MD and ADC values of G1 were significantly higher than those of G2, and those of G2 were significantly higher than those of G3. MTRasym and MK were both positively correlated with histological grade (r = 0.789 and 0.743, P < 0.001), while MD and ADC were both negatively correlated with histological grade (r = − 0.732 and - 0.644, P < 0.001). For the diagnosis of G1 and G2 CSCs, AUC (APTWI+DKI + DWI) > AUC (DKI + DWI) > AUC (APTWI+DKI) > AUC (APTWI+DWI) > AUC (MTRasym) > AUC (MK) > AUC (MD) > AUC (ADC), where the differences between AUC (APTWI+DKI + DWI), AUC (DKI + DWI) and AUC (ADC) were significant. For the diagnosis of G2 and G3 CSCs, AUC (APTWI+DKI + DWI) > AUC (APTWI+DWI) > AUC (APTWI+DKI) > AUC (DKI + DWI) > AUC (MTRasym) > AUC (MK) > AUC (MD > AUC (ADC), where the differences between AUC (APTWI+DKI + DWI), AUC (APTWI+DWI) and AUC (ADC) were significant. Conclusion Compared with DWI and DKI, APTWI is more effective in identifying the histological grades of CSC. APTWI is recommended as a supplementary scan to routine DWI in CSCs.
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Zheng RR, Cai MT, Lan L, Huang XW, Yang YJ, Powell M, Lin F. An MRI-based radiomics signature and clinical characteristics for survival prediction in early-stage cervical cancer. Br J Radiol 2022; 95:20210838. [PMID: 34797703 PMCID: PMC8722251 DOI: 10.1259/bjr.20210838] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
OBJECTIVES To investigate the prognostic role of magnetic resonance imaging (MRI)-based radiomics signature and clinical characteristics for overall survival (OS) and disease-free survival (DFS) in the early-stage cervical cancer. METHODS A total of 207 cervical cancer patients (training cohort: n = 144; validation cohort: n = 63) were enrolled. 792 radiomics features were extracted from T2W and diffusion-weighted imaging (DWI). 19 clinicopathological parameters were collected from the electronic medical record system. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to select significant features to construct prognostic model for OS and DFS. Kaplan-Meier (KM) analysis and log-rank test were applied to identify the association between the radiomics score (Rad-score) and survival time. Nomogram discrimination and calibration were evaluated as well. Associations between radiomics features and clinical parameters were investigated by heatmaps. RESULTS A radiomics signature derived from joint T2W and DWI images showed better prognostic performance than that from either T2W or DWI image alone. Higher Rad-score was associated with worse OS (p < 0.05) and DFS (p < 0.05) in the training and validation set. The joint models outperformed both radiomics model and clinicopathological model alone for 3-year OS and DFS estimation. The calibration curves reached an agreement. Heatmap analysis demonstrated significant associations between radiomics features and clinical characteristics. CONCLUSIONS The MRI-based radiomics nomogram showed a good performance on survival prediction for the OS and DFS in the early-stage cervical cancer. The prediction of the prognostic models could be improved by combining with clinical characteristics, suggesting its potential for clinical application. ADVANCES IN KNOWLEDGE This is the first study to build the radiomics-derived models based on T2W and DWI images for the prediction of survival outcomes on the early-stage cervical cancer patients, and further construct a combined risk scoring system incorporating the clinical features.
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Affiliation(s)
- Ru-ru Zheng
- Department of Gynecology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, PR China
| | - Meng-ting Cai
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, PR China
| | - Li Lan
- Department of Ultrasound Imaging, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, PR China
| | - Xiao Wan Huang
- Department of Gynecology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, PR China
| | - Yun Jun Yang
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, PR China
| | - Martin Powell
- Nottingham University Affiliated Hospital, Nottingham Treatment Centre, Nottingham, UK
| | - Feng Lin
- Department of Gynecology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, PR China
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21
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Huang Z, Li X, Wang Z, Meng N, Fu F, Han H, Li D, Bai Y, Wei W, Fang T, Feng P, Yuan J, Yang Y, Wang M. Application of Simultaneous 18 F-FDG PET With Monoexponential, Biexponential, and Stretched Exponential Model-Based Diffusion-Weighted MR Imaging in Assessing the Proliferation Status of Lung Adenocarcinoma. J Magn Reson Imaging 2021; 56:63-74. [PMID: 34888990 DOI: 10.1002/jmri.28010] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 11/18/2021] [Accepted: 11/18/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Ki-67 proliferation index (PI) is important for providing information on tumor behavior, treatment response, and prognosis. Integrated positron emission tomography/magnetic resonance (PET/MR) may have the potential to assess Ki-67 PI in patients with lung adenocarcinoma. PURPOSE To explore the value of simultaneous 18 F-fluorodeoxyglucose (18 F-FDG) PET/MR-derived parameters in assessing the proliferation status of lung adenocarcinoma and to determine the best combination of parameters. STUDY TYPE Prospective. POPULATION Seventy-eight patients with lung adenocarcinoma and with Ki-67 PI. FIELD STRENGTH/SEQUENCE 3.0 T, simultaneous PET/MRI including diffusion-weighted imaging (DWI) and 18 F-FDG PET. ASSESSMENT DWI-derived parameters, namely, apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), diffusion heterogeneity index (α), and distributed diffusion coefficient (DDC); and PET-derived parameters, namely, maximum standardized uptake value (SUVmax ), metabolic tumor volume (MTV), and total lesion glycolytic volume (TLG), were calculated and compared between the high (>25%) and low (≤25%) Ki-67 PI groups. The correlations between PET-derived parameters and DWI-derived parameters were analyzed. STATISTICAL TESTS Student's t-test, Mann-Whitney U test, chi-square test, and receiver operating characteristic (ROC) curves. A P-value <0.05 was considered statistically significant. RESULTS The SUVmax , MTV, TLG, ADC, D, and DDC values were significantly different between the high (N = 35) and low Ki-67 PI groups (N = 43). D, SUVmax , and MTV independently predicted the Ki-67 PI status. The combination of D, SUVmax , and MTV had the largest area under the ROC curve (AUC = 0.900), which was significantly larger than the AUC alone of DDC (AUC = 0.725), SUVmax (AUC = 0.815), MTV (AUC = 0.774), or TLG (AUC = 0.783). The perfusion fraction did not correlate with SUVmax , MTV, or TLG (r = -0.03, -0.11, and -0.04, respectively; P = 0.786, 0.348, and 0.733). DATA CONCLUSION The combination of D, SUVmax , and MTV may predict Ki-67 PI status. No correlation was observed between perfusion parameters and metabolic parameters. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Zhun Huang
- Department of Medical Imaging, Henan University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China
| | - Xiaochen Li
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Zhixue Wang
- Department of Radiology, The First Affiliated Hospital of Henan University, Kaifeng, China
| | - Nan Meng
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Fangfang Fu
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Hui Han
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Dujuan Li
- Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Yan Bai
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Wei Wei
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Ting Fang
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Pengyang Feng
- Department of Medical Imaging, Henan University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China
| | - Jianmin Yuan
- Central Research Institute, UIH Group, Shanghai, China
| | - Yang Yang
- Beijing United Imaging Research Institute of Intelligent Imaging, Beijing, China
| | - Meiyun Wang
- Department of Medical Imaging, Henan University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
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22
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Song J, Gu Y, Du T, Liu Q. Analysis of quantitative and semi-quantitative parameters of DCE-MRI in differential diagnosis of benign and malignant cervical tumors. Am J Transl Res 2021; 13:12228-12234. [PMID: 34956449 PMCID: PMC8661164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 06/28/2021] [Indexed: 06/14/2023]
Abstract
OBJECTIVE To explore and analyze the value of quantitative and semi-quantitative parameters of dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) in the differential diagnosis of benign and malignant cervical tumors. METHODS A total of 51 patients with cervical tumor who were treated in our hospital from April 2017 to October 2019 were recruited as the research subjects. All patients underwent conventional MRI plain scan and DCE-MRI examination. With histopathological results as the gold standard, the participants were classified into a malignant tumor group (n = 36) and a benign tumor group (n = 15) on the basis of the nature of the cervical tumor. The difference of quantitative and semi-quantitative parameters of DCE-MRI between the two groups was compared, and the specificity, sensitivity, negative and positive predictive values of quantitative and semi-quantitative parameters in differentiating benign from malignant cervical tumors were analyzed to evaluate the value of quantitative and semi-quantitative parameters of DCE-MRI in the differential diagnosis of benign and malignant cervical tumors. RESULTS The quantitative parameters Kep, Ktrans and Ve of DCE-MRI in the malignant-tumor-group were critically higher than that in the benign tumor group (P<0.05). When distinguishing between the benign and malignant cervical tumors, the specificity and sensitivity of kep, Ktrans and Ve were higher in the differential diagnosis of malignant cervical tumors than in the benign cervical tumors. The peak of the malignant tumor group was remarkably earlier than that of the benign tumor group, and SI60% of the malignant tumor group was dramatically higher than that of benign tumor group (P<0.05). In addition, compared with benign cervical tumors, the semi-quantitative parameters of DCE-MR TTP and SI60% were more sensitive to malignant cervical tumors. CONCLUSION The quantitative and semi-quantitative parameters of DCE-MRI have high value in differentiating benign and malignant cervical tumors. When adopting conventional MRI to diagnose oncologic cervical tumors, the differential diagnosis of quantitative and semi-quantitative parameters of DCE-MRI has demonstrated a high clinical value by avoiding unnecessary radical surgeries.
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Affiliation(s)
- Jun Song
- Department of Radiology, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of ChinaMianyang, Sichuan, China
| | - Yong Gu
- Department of Radiology, Santai Hospital, North Sichuan Medical College621100, Sichuan, China
| | - Tingting Du
- Department of Radiology, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of ChinaMianyang, Sichuan, China
| | - Qiyu Liu
- Department of Radiology, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of ChinaMianyang, Sichuan, China
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Papoutsaki MV, Sidhu HS, Dikaios N, Singh S, Atkinson D, Kanber B, Beale T, Morley S, Forster M, Carnell D, Mendes R, Punwani S. Utility of diffusion MRI characteristics of cervical lymph nodes as disease classifier between patients with head and neck squamous cell carcinoma and healthy volunteers. NMR IN BIOMEDICINE 2021; 34:e4587. [PMID: 34240782 DOI: 10.1002/nbm.4587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 06/10/2021] [Accepted: 06/11/2021] [Indexed: 06/13/2023]
Abstract
Diffusion MRI characteristics assessed by apparent diffusion coefficient (ADC) histogram analysis in head and neck squamous cell carcinoma (HNSCC) have been reported as helpful in classifying tumours based on diffusion characteristics. There is little reported on HNSCC lymph nodes classification by diffusion characteristics. The aim of this study was to determine whether pretreatment nodal microstructural diffusion MRI characteristics can classify diseased nodes of patients with HNSCC from normal nodes of healthy volunteers. Seventy-nine patients with histologically confirmed HNSCC prior to chemoradiotherapy, and eight healthy volunteers, underwent diffusion-weighted (DW) MRI at a 1.5-T MR scanner. Two radiologists contoured lymph nodes on DW (b = 300 s/m2 ) images. ADC, distributed diffusion coefficient (DDC) and alpha (α) values were calculated by monoexponential and stretched exponential models. Histogram analysis metrics of drawn volume were compared between patients and volunteers using a Mann-Whitney test. The classification performance of each metric between the normal and diseased nodes was determined by receiver operating characteristic (ROC) analysis. Intraclass correlation coefficients determined interobserver reproducibility of each metric based on differently drawn ROIs by two radiologists. Sixty cancerous and 40 normal nodes were analysed. ADC histogram analysis revealed significant differences between patients and volunteers (p ≤0.0001 to 0.0046), presenting ADC distributions that were more skewed (1.49 for patients, 1.03 for volunteers; p = 0.0114) and 'peaked' (6.82 for patients, 4.20 for volunteers; p = 0.0021) in patients. Maximum ADC values exhibited the highest area under the curve ([AUC] 0.892). Significant differences were revealed between patients and volunteers for DDC and α value histogram metrics (p ≤0.0001 to 0.0044); the highest AUC were exhibited by maximum DDC (0.772) and the 25th percentile α value (0.761). Interobserver repeatability was excellent for mean ADC (ICC = 0.88) and the 25th percentile α value (ICC = 0.78), but poor for all other metrics. These results suggest that pretreatment microstructural diffusion MRI characteristics in lymph nodes, assessed by ADC and α value histogram analysis, can identify nodal disease.
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Affiliation(s)
| | | | - Nikolaos Dikaios
- Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, UK
| | - Saurabh Singh
- Centre for Medical Imaging, University College London, London, UK
| | - David Atkinson
- Centre for Medical Imaging, University College London, London, UK
| | - Baris Kanber
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Timothy Beale
- Department of Radiology, University College London Hospital, London, UK
| | - Simon Morley
- Department of Radiology, University College London Hospital, London, UK
| | - Martin Forster
- Department of Oncology, University College London, Cancer Institute, London, UK
- Department of Oncology, University College London Hospital, London, UK
| | - Dawn Carnell
- Department of Oncology, University College London Hospital, London, UK
| | - Ruheena Mendes
- Department of Oncology, University College London Hospital, London, UK
| | - Shonit Punwani
- Centre for Medical Imaging, University College London, London, UK
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Wang M, Perucho JA, Vardhanabhuti V, Ip P, Ngan HY, Lee EY. Radiomic Features of T2-weighted Imaging and Diffusion Kurtosis Imaging in Differentiating Clinicopathological Characteristics of Cervical Carcinoma. Acad Radiol 2021; 29:1133-1140. [PMID: 34583867 DOI: 10.1016/j.acra.2021.08.018] [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: 06/23/2021] [Revised: 07/28/2021] [Accepted: 08/12/2021] [Indexed: 01/06/2023]
Abstract
RATIONALE AND OBJECTIVES Clinicopathological characteristics including histological subtypes, tumour grades and International Federation of Gynecology and Obstetrics (FIGO) stages are crucial factors in the clinical decision for cervical carcinoma (CC). The purpose of this study was to evaluate the ability of T2-weighted imaging (T2WI) and diffusion kurtosis imaging (DKI) radiomics in differentiating clinicopathological characteristics of CC. MATERIALS AND METHODS One hundred and seventeen histologically confirmed CC patients (mean age 56.5 ± 14.0 years) with pre-treatment magnetic resonance imaging were retrospectively reviewed. DKI was acquired with 4 b-values (0-1500 s/mm2). Volumes of interest were contoured around the tumours on T2WI and DKI. Radiomic features including shape, first-order and grey-level co-occurrence matrix with wavelet transforms were extracted. Intraclass correlation coeffient between 2 radiologists was used for features reduction. Feature selection was achieved by elastic net and minimum redundancy maximum relevance. Selected features were used to build random forest (RF) models. The performances for differentiating histological subtypes, tumour grades and FIGO stages were assessed by receiver operating characteristic analysis. RESULTS Area under the curves (AUCs) for T2WI-only RF models for discriminating histological subtypes, tumour grades and FIGO stages were 0.762, 0.686, and 0.719. AUCs for DWI-only models were 0.663, 0.645, and 0.868, respectively. AUCs of the combined T2WI and DKI models were 0.823, 0.790, and 0.850, respectively. CONCLUSION T2WI and DKI radiomic features could differentiate the clinicopathological characteristics of CC. A combined model showed excellent diagnostic discrimination for histological subtypes, while a DKI-only model presented the best performance in differentiating FIGO stages.
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Xia N, Li Y, Xue Y, Li W, Zhang Z, Wen C, Li J, Ye Q. Intravoxel incoherent motion diffusion-weighted imaging in the characterization of Alzheimer's disease. Brain Imaging Behav 2021; 16:617-626. [PMID: 34480258 DOI: 10.1007/s11682-021-00538-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/08/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVES Alzheimer's disease (AD) is the most common type of dementia, and characterizing brain changes in AD is important for clinical diagnosis and prognosis. This study was designed to evaluate the classification performance of intravoxel incoherent motion (IVIM) diffusion-weighted imaging in differentiating between AD patients and normal control (NC) subjects and to explore its potential effectiveness as a neuroimaging biomarker. METHODS Thirty-one patients with probable AD and twenty NC subjects were included in the prospective study. IVIM data were subjected to postprocessing, and parameters including the apparent diffusion coefficient (ADC), slow diffusion coefficient (Ds), fast diffusion coefficient (Df), perfusion fraction (fp) and Df*fp were calculated. The classification model was developed and confirmed with cross-validation (group A/B) using Support Vector Machine (SVM). Correlations between IVIM parameters and Mini-Mental State Examination (MMSE) scores in AD patients were investigated using partial correlation analysis. RESULTS Diffusion MRI revealed significant region-specific differences that aided in differentiating AD patients from controls. Among the analyzed regions and parameters, the Df of the right precuneus (PreR) (ρ = 0.515; P = 0.006) and the left cerebellum (CL) (ρ = 0.429; P = 0.026) demonstrated significant associations with the cognitive function of AD patients. An area under the receiver operating characteristics curve (AUC) of 0.84 (95% CI: 0.66, 0.99) was calculated for the validation in dataset B after the prediction model was trained on dataset A. When the datasets were reversed, an AUC of 0.90 (95% CI: 0.75, 1.00) was calculated for the validation in dataset A, after the prediction model trained in dataset B. CONCLUSION IVIM imaging is a promising method for the classification of AD and NC subjects, and IVIM parameters of precuneus and cerebellum might be effective biomarker for the diagnosis of AD.
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Affiliation(s)
- Nengzhi Xia
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China
| | - Yanxuan Li
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China
| | - Yingnan Xue
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China
| | - Weikang Li
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China
| | - Zhenhua Zhang
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China
| | - Caiyun Wen
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China
| | - Jiance Li
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China
| | - Qiong Ye
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China. .,High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, People's Republic of China.
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deSouza NM. Imaging to assist fertility-sparing surgery. Best Pract Res Clin Obstet Gynaecol 2021; 75:23-36. [PMID: 33722497 DOI: 10.1016/j.bpobgyn.2021.01.012] [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: 10/25/2020] [Accepted: 01/31/2021] [Indexed: 11/23/2022]
Abstract
Cytological screening and human papilloma virus testing has led to diagnosis of cervical cancer in young women at an earlier stage. Defining the full extent of the disease within the cervix with imaging aids the decision on feasibility of fertility-sparing surgical options, such as extended cone biopsy or trachelectomy. High spatial resolution images with maximal contrast between tumour and surrounding background are achieved with T2-weighted and diffusion-weighted (DW) magnetic resonance imaging (MRI) obtained using an endovaginal receiver coil. Tumour size and volume demonstrated in this way correlates between observers and with histology and differences between MRI and histology estimates of normal endocervical canal length are not significant. For planning fertility-sparing surgery, this imaging technique facilitates the best oncological outcome while minimising subsequent obstetric risks. Parametrial invasion may be assessed on large field of view T2-weighted MRI. The fat content of the parametrium limits the utility of DW imaging in this context, because fat typically shows diffusion restriction. The use of contrast-enhanced MRI for assessing the parametrium does not provide additional benefits to the T2-weighted images and the need for an extrinsic contrast agent merely adds additional complexity and cost. For nodal assessment, 18fluorodeoxyglucose positron emission tomography-computerised tomography (18FDG PET-CT) remains the gold standard.
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Affiliation(s)
- N M deSouza
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, 15 Cotswold Road, SM2 5NG, UK.
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Ind T. Overview of fertility sparing treatments for cervical cancer. Best Pract Res Clin Obstet Gynaecol 2021; 75:2-9. [PMID: 34053867 DOI: 10.1016/j.bpobgyn.2021.04.004] [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: 03/31/2021] [Accepted: 04/30/2021] [Indexed: 11/16/2022]
Abstract
Until the late 1980s, the mainstay of treatment for cervical cancer has been either hysterectomy or radiotherapy. From the mid to late 1990s, surgical treatments have been focussed more on sparing fertility by preserving the corpus of the womb with trachelectomy or even conserving part of the cervical stroma with a cone biopsy. In carefully selected cases, less radical treatment that preserves the uterus has been considered safe. However, these approaches can be associated with specific operative and obstetric complications such as stitch ulceration, cervical stenosis, late miscarriage, and premature labour. Most guidelines agree that the management of such patients should be centralised in a unit with specialist gynaecological oncology, radiology, and histopathology services supported by specialist cancer nurses.
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Affiliation(s)
- Thomas Ind
- Royal Marsden Hospital, London, SW3 6JA, UK; St George's University of London, Cranmer Terrace, Tooting, London SW17 0RE, UK.
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Li S, Zhang Z, Liu J, Zhang F, Yang M, Lu H, Zhang Y, Han F, Cheng J, Zhu J. The feasibility of a radial turbo-spin-echo T2 mapping for preoperative prediction of the histological grade and lymphovascular space invasion of cervical squamous cell carcinoma. Eur J Radiol 2021; 139:109684. [PMID: 33836336 DOI: 10.1016/j.ejrad.2021.109684] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 03/05/2021] [Accepted: 03/25/2021] [Indexed: 12/24/2022]
Abstract
PURPOSE The study aimed to analyze the feasibility of a radial turbo-spin-echo (TSE) T2 mapping to differentiate the histological grades and lymphovascular space invasion (LVSI) of cervical squamous cell carcinoma (CSCC) in comparison with diffusion-weighted imaging (DWI). METHODS A total of 58 patients with CSCC and 40 healthy volunteers underwent T2 mapping and DWI before therapy. The T2 and apparent diffusion coefficient (ADC) values were calculated using different tumor characteristics. The differences, efficacies and correlations between parameters were determined. RESULTS The T2 and ADC values were significantly different between CSCC and normal cervical stroma (both p < 0.05). Poorly differentiated (G3) tumor showed lower T2 and ADC values than well differentiated (G1) and moderately differentiated (G2) tumor (all p < 0.05). The T2 values were significantly lower in LVSI-positive CSCC than LVSI-negative CSCC (p < 0.05). No significant difference was found in ADC values for LVSI status (p = 0.561). The area under the ROC (AUC) for T2 and ADC values to distinguish G1/G2 and G3 tumor were 0.741 and 0.763, respectively. The AUC for T2 and ADC values to distinguish LVSI-positive and LVSI-negative CSCC were 0.877 and 0.537, respectively. The T2 and ADC values were negatively correlated with the tumor grades (r = -0.402 and r = -0.339, respectively). CONCLUSIONS Radial TSE T2 mapping is feasible for CSCC. Similar to ADC values, quantitative T2 values could serve as a noninvasive biomarker to predict histological grades preoperatively. Moreover, T2 values could determine the presence of LVSI better than ADC values.
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Affiliation(s)
- Shujian Li
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zanxia Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jie Liu
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Feifei Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Meng Yang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Huifang Lu
- Department of Gynecology and Obstetrics, Huaihe Hospital of Henan University, Kaifeng, China
| | - Yong Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Fei Han
- MR R&D Collaboration, Siemens Healthineers, Los Angeles, CA, USA
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Jinxia Zhu
- MR Collaboration, Siemens Healthcare Ltd., Beijing, China
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Association between IVIM parameters and treatment response in locally advanced squamous cell cervical cancer treated by chemoradiotherapy. Eur Radiol 2021; 31:7845-7854. [PMID: 33786654 DOI: 10.1007/s00330-021-07817-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 01/07/2021] [Accepted: 02/19/2021] [Indexed: 12/21/2022]
Abstract
OBJECTIVE To examine the associations of intravoxel incoherent motion (IVIM) parameters with treatment response in cervical cancer following concurrent chemoradiotherapy (CCRT). MATERIALS AND METHODS Forty-five patients, median age of 58 years (range: 28-82), with pre-CCRT and post-CCRT MRI, were retrospectively analysed. The IVIM parameters pure diffusion coefficient (D) and perfusion fraction (f) were estimated using the full b-value distribution (BVD) as well as an optimised subsample BVD. Dice similarity coefficient (DSC) and intraclass correlation coefficient (ICC) were used to measure observer repeatability in tumour delineation at both time points. Treatment response was determined by the response evaluation criteria in solid tumour (RECIST) 1.1 between MRI examinations. Mann-Whitney U tests were used to test for significant differences in IVIM parameters between treatment response groups. RESULTS Pre-CCRT tumour delineation repeatability was good (DSC = 0.81) while post-CCRT delineation repeatability was moderate (DSC = 0.67). Values of D and f had good repeatability at both time points (ICC > 0.80). Pre-CCRT f estimated using the full BVD and optimised subsample BVD were found to be significantly higher in patients with partial response compared to those with stable disease or disease progression (p = 0.01 and 95% CI = -0.02-0.00 for both cases). CONCLUSION Pre-CCRT f was associated with treatment response in cervical cancer with good observer repeatability. Similar discriminative ability was also observed in estimated pre-CCRT f from an optimised subsample BVD. KEY POINTS • Pre-treatment tumour delineation and IVIM parameters had good observer repeatability. • Post-treatment tumour delineation was worse than at pre-treatment, but IVIM parameters retained good ICC. • Pre-treatment perfusion fraction estimated from all b-values and an optimised subsample of b-values were associated with treatment response.
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Dong Y, Dong RT, Zhang XM, Song QL, Yu T, Hong Luo Y. Influence of menstrual status and pathological type on the apparent diffusion coefficient in cervical cancer: a primary study. Acta Radiol 2021; 62:430-436. [PMID: 32536261 DOI: 10.1177/0284185120926897] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Apparent diffusion coefficient (ADC) value is an important quantitative parameter in the research of cervical cancer, affected by some factors. PURPOSE To investigate the effect of pathological type and menstrual status on the ADC value of cervical cancer. MATERIAL AND METHODS A total of 352 individuals with pathologically confirmed cervical cancer between January 2015 to December 2017 were retrospectively enrolled in this study, including 317 cases with squamous cell carcinomas (SCC) and 35 cases with adenocarcinomas (AC); 177 patients were non-menopausal and 175 were menopausal. All patients underwent a routine 3.0-T magnetic resonance imaging (MRI) scan and diffusion-weighted imaging (DWI) examination using b-values of 0, 800, and 1000 s/mm2. Three parameters including mean ADC (ADCmean), maximum ADC (ADCmax), and minimum ADC (ADCmin) of cervical cancer lesions were measured and retrospectively analyzed. Independent samples t-test was used to compare the difference of ADC values in different menstrual status and pathological types. RESULTS In all menopausal and non-menopausal patients, the ADCmean and ADCmin values of SCC were lower than those of AC (P<0.05), the ADCmax of two pathological types showed no statistical difference (P > 0.05). In menopausal patients, the ADCmean, ADCmax, and ADCmin values of SCC were not statistically different compared with those of AC (P > 0.05). The ADCmean, ADCmax, and ADCmin values of different pathological types cervical cancers in non-menopausal patients were all higher than those in menopausal patients (P<0.05). CONCLUSION The ADC values of the cervical cancers were different in different pathological types and were also affected by menstrual status.
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Affiliation(s)
- Yue Dong
- Department of Radiology, Cancer Hospital of China Medical University, LiaoNing Cancer Hospital & Institute, Shenyang, Liaoning, PR China
| | - Rui Tong Dong
- Department of Radiology, Cancer Hospital of China Medical University, LiaoNing Cancer Hospital & Institute, Shenyang, Liaoning, PR China
| | - Xiao Miao Zhang
- Department of Radiology, Cancer Hospital of China Medical University, LiaoNing Cancer Hospital & Institute, Shenyang, Liaoning, PR China
| | - Qing Ling Song
- Department of Radiology, Cancer Hospital of China Medical University, LiaoNing Cancer Hospital & Institute, Shenyang, Liaoning, PR China
| | - Tao Yu
- Department of Radiology, Cancer Hospital of China Medical University, LiaoNing Cancer Hospital & Institute, Shenyang, Liaoning, PR China
| | - Ya Hong Luo
- Department of Radiology, Cancer Hospital of China Medical University, LiaoNing Cancer Hospital & Institute, Shenyang, Liaoning, PR China
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Uterine Cervical Carcinoma: Evaluation Using Non-Gaussian Diffusion Kurtosis Imaging and Its Correlation With Histopathological Findings. J Comput Assist Tomogr 2021; 45:29-36. [PMID: 32558770 DOI: 10.1097/rct.0000000000001042] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
OBJECTIVE The aim of the study was to assess non-Gaussian diffusion kurtosis imaging (DKI)'s usefulness as a noninvasive method to evaluate tumor invasion depth, histological grade, and lymph node metastasis in cervical carcinoma (CC) patients. METHODS Twenty-two consecutive patients with histologically confirmed CC were examined by 1.5-T MRI and non-Gaussian DKI with 4 b values of 0, 500, 1000, and 2000 s/mm2. Kurtosis (K), diffusivity (D), and apparent diffusion coefficient (ADC) maps were compared with histopathological findings. RESULTS Kurtosis maps revealed the fibrous stroma as a distinct high K zone (1.442 ± 0.373) that was significantly different from values of the cervical mucosa, outer stroma, and parametrium (0.648 ± 0.083, 0.715 ± 0.113, and 0.504 ± 0.060, respectively, P < 0.0001). Kurtosis (1.189 ± 0.228) and D (0.961 ± 0.198 × 10-3 mm2/s) values of all CCs were significantly different from those of all uterine cervical wall layers. Kurtosis and D values were significantly correlated with histological grades of CCs (r = 0.934, P < 0.0001, and r = -0.925, P < 0.0001, respectively), whereas no significant differences were found in ADC values between grades 2 and 3 CCs (P = 0.787). Metastatic and nonmetastatic lymph nodes showed significantly different K (P < 0.0001) and D (P < 0.0001) values; however, their ADC values did not show significant differences (P = 0.437). For differentiating grade 3 CCs from grade 1 or 2 CCs, the areas under the curve for K (0.991, P = 0.0375) and D (0.982, P = 0.0337) values were significantly higher than those for ADC values (0.759). For differentiating metastatic and nonmetastatic lymph nodes, the areas under the curve for K (0.974, P = 0.0028) and D (0.968, P = 0.0018) values were significantly higher than those for ADC (0.596). CONCLUSIONS Non-Gaussian DKI may be clinically useful for noninvasive evaluation of tumor invasion depth, histological grade, and lymph node metastasis in CC patients.
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Value of integrated PET-IVIM MRI in predicting lymphovascular space invasion in cervical cancer without lymphatic metastasis. Eur J Nucl Med Mol Imaging 2021; 48:2990-3000. [PMID: 33506309 DOI: 10.1007/s00259-021-05208-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 01/17/2021] [Indexed: 12/14/2022]
Abstract
PURPOSE To evaluate the contributory value of positron emission tomography (PET)-intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) in the prediction of lymphovascular space invasion (LVSI) in patients with cervical cancer without lymphatic metastasis. MATERIALS AND METHODS A total of 90 patients with cervical cancer without signs of lymph node metastasis on PET/MRI were enrolled in this study. The tumours were classified into LVSI-positive (n = 25) and LVSI-negative (n = 65) groups according to postoperative pathology. The PET-derived parameters (SUVmax, SUVmean, metabolic tumour volume (MTV) and total lesion glycolysis (TLG)) and IVIM-derived parameters (ADCmean, ADCmin, Dmean, Dmin, f, D* and gross tumour volume (GTV)) between the two groups were evaluated using a Student's t test (Mann-Whitney U test for variables with a nonnormal distribution) and receiver operating characteristic (ROC) curves. The optimal combination of PET/MR parameters for predicting LVSI was investigated using univariate and multivariate logistic regression models and evaluated by ROC curves. The optimal cutoff threshold values corresponded to the maximal values of the Youden index. A control model was established using 1000 bootstrapped samples, for which the performance was validated using calibration curves and ROC curves. RESULTS PET-derived parameters (SUVmax, SUVmean, MTV, TLG) and IVIM MRI-derived parameters (Dmin, ADCmin, GTV) were significantly different between patients with and without LVSI (P < 0.05). Logistic analyses showed that a combination of TLG and Dmin had the strongest predictive value for LVSI diagnosis (area under the curve (AUC), 0.861; sensitivity, 80.00; specificity, 86.15; P < 0.001). The optimal cutoff threshold values for Dmin and TLG were 0.58 × 10-3 mm2/s and 66.68 g/cm3, respectively. The verification model showed the combination of TLG and Dmin had the strongest predictive value, and its ROC curve and calibration curve showed good accuracy (AUC, 0.878) and consistency. CONCLUSIONS The combination of TLG and Dmin may be the best indicator for predicting LVSI in cervical cancer without lymphatic metastasis.
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Chen M, Feng C, Wang Q, Li J, Wu S, Hu D, Deng B, Li Z. Comparison of reduced field-of-view diffusion-weighted imaging (DWI) and conventional DWI techniques in the assessment of Cervical carcinoma at 3.0T: Image quality and FIGO staging. Eur J Radiol 2021; 137:109557. [PMID: 33549900 DOI: 10.1016/j.ejrad.2021.109557] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 01/06/2021] [Accepted: 01/18/2021] [Indexed: 12/24/2022]
Abstract
OBJECTIVE To evaluate imaging quality (IQ) and International Federation of Gynecology and Obstetrics (FIGO) staging of reduced field-of-view (r-FOV) diffusion-weighted imaging (DWI) in cervical carcinoma (CC). MATERIALS AND METHODS Sixty patients with pathologically proven CC who underwent both pre-treatment r-FOV DWI and full field-of-view (f-FOV) DWI on a 3.0T MRI scanner were retrospectively reviewed. The subjective qualitative image scores were compared using the Wilcoxon signed-rank test. Objective quality values and apparent diffusion coefficient (ADC) were estimated by paired t-test or Wilcoxon signed-rank test for the two DWI sequences according to Normality test. Spearman rank correlation analysis was used to evaluate the relationship between pathological results and mean ADC value. RESULTS The subjective IQ scores for r-FOV DWI were significantly higher than those for f-FOV DWI (P < 0.001). Similarly, the contrast-to-noise (CNR) value of r-FOV DWI was superior to that of f-FOV DWI (10.30 ± 3.676, 8.91 ± 3.008, P = 0.021). However, the signal-to-noise ratio (SNR) value of r-FOV DWI was considerably lower than that of f-FOV DWI (27.80 ± 6.056, 33.67 ± 7.833, P<0.001). No significant difference was found between mean ADC values of f-FOV DWI and r-FOV DWI. There was a significant tendency for a negative correlation between the ADC values and FIGO stages of CC for both two sequences (r=-0. 436, P<0.01; r=-0.470, P<0.01, respectively). CONCLUSIONS The rFOV DWI sequence provided significantly better IQ and lesion conspicuity than the fFOV DWI sequence. In addition, rFOV sequences can be used in evaluation of FIGO staging of cervical cancer.
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Affiliation(s)
- Mingzhen Chen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
| | - Cui Feng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
| | - Qiuxia Wang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
| | - Jiali Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
| | - Sisi Wu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
| | - Daoyu Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
| | - Baodi Deng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China.
| | - Zhen Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
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Zhang Q, Yu X, Ouyang H, Zhang J, Chen S, Xie L, Zhao X. Whole-tumor texture model based on diffusion kurtosis imaging for assessing cervical cancer: a preliminary study. Eur Radiol 2021; 31:5576-5585. [PMID: 33464399 DOI: 10.1007/s00330-020-07612-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 11/09/2020] [Accepted: 12/07/2020] [Indexed: 01/17/2023]
Abstract
OBJECTIVES To evaluate the diagnostic potential of diffusion kurtosis imaging (DKI) functional maps with whole-tumor texture analysis in differentiating cervical cancer (CC) subtype and grade. METHODS Seventy-six patients with CC were enrolled. First-order texture features of the whole tumor were extracted from DKI and DWI functional maps, including apparent kurtosis coefficient averaged over all directions (MK), kurtosis along the axial direction (Ka), kurtosis along the radial direction (Kr), mean diffusivity (MD), fractional anisotropy (FA), and ADC maps, respectively. The Mann-Whitney U test and ROC curve were used to select the most representative texture features. Models based on each individual and combined functional maps were established using multivariate logistic regression analysis. Conventional parameters-the average values of ADC and DKI parameters derived from the conventional ROI method-were also evaluated. RESULTS The combined model based on Ka, Kr, MD, and FA maps yielded the best diagnostic performance in discrimination of cervical squamous cell cancer (SCC) and cervical adenocarcinoma (CAC) with the highest AUC (0.932). Among individual functional map derived models, Kr map-derived model showed the best performance when differentiating tumor subtypes (AUC = 0.828). MK_90th percentile was useful for distinguishing high-grade and low-grade in SCC tumors with an AUC of 0.701. The average values of MD, FA, and ADC were significantly different between SCC and CAC, but no conventional parameters were useful for tumor grading. CONCLUSIONS The whole-tumor texture analysis applied to DKI functional maps can be used for differential diagnosis of cervical cancer subtypes and grading SCC. KEY POINTS • The whole-tumor texture analysis applied to DKI functional maps allows accurate differential diagnosis of CC subtype and grade. • The combined model derived from multiple functional maps performs significantly better than the single models when differentiating tumor subtypes. • MK_90th percentile was useful for distinguishing poorly and well-/moderately differentiated SCC tumors with an AUC of 0.701.
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Affiliation(s)
- Qi Zhang
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese 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, Chinese 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, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jieying Zhang
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese 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, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Lizhi Xie
- GE Healthcare, MR Research, Beijing, China
| | - Xinming Zhao
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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Soft tissue sarcomas: IVIM and DKI correlate with the expression of HIF-1α on direct comparison of MRI and pathological slices. Eur Radiol 2021; 31:4669-4679. [PMID: 33416975 DOI: 10.1007/s00330-020-07526-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Revised: 10/21/2020] [Accepted: 11/16/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE To investigate the correlation of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters with the expression of HIF-1α in soft tissue sarcoma (STS). METHODS This prospective study was approved by the institutional ethics committee. Written informed consent was obtained from all patients. Forty patients with STS who underwent 3.0 T MRI, including IVIM and DKI, were included in the study. Standard apparent diffusion coefficient (ADC), true ADC (Dslow), pseudo ADC (Dfast), perfusion fraction (f), mean kurtosis (MK), and mean diffusivity (MD) of each lesion were independently analyzed by two observers. An MRI-pathology control method was used to ensure correspondence between the MRI slices and the pathological sections. Spearman analysis, independent sample t test, Mann-Whitney U test, chi-squared test, and receiver operating characteristic (ROC) curve analysis were performed. RESULTS Dslow and MD values showed a negative correlation with HIF-1α expression (r = - 0.469, - 0.588). MK and f values showed a positive correlation with HIF-1α expression (r = 0.779, 0.572). Dslow, MD, MK, and f values showed significant differences between the high- and low-expression groups. The MK value showed the best diagnostic ability. The optimal cut-off MK value of 0.604 was associated with 78.3% sensitivity and 88.2% specificity (area under the curve, 0.867). CONCLUSIONS This preliminary study demonstrated the association of IVIM and DKI parameters with the expression of HIF-1α in STS. KEY POINTS • IVIM and DKI parameters are correlated with the expression of HIF-1α in STS. • The MRI-pathology control method can be used in clinical studies to ensure correspondence between MRI slices and pathology sections.
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Li S, Liu J, Zhang F, Yang M, Zhang Z, Liu J, Zhang Y, Hilbert T, Kober T, Cheng J, Zhu J. Novel T2 Mapping for Evaluating Cervical Cancer Features by Providing Quantitative T2 Maps and Synthetic Morphologic Images: A Preliminary Study. J Magn Reson Imaging 2020; 52:1859-1869. [PMID: 32798294 DOI: 10.1002/jmri.27297] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 07/04/2020] [Accepted: 07/07/2020] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND The application value of T2 mapping in evaluating cervical cancer (CC) features remains unclear. PURPOSE To investigate the role of T2 values in evaluating CC classification, grade, and lymphovascular space invasion (LVSI) in comparison to apparent diffusion coefficient (ADC), and to compare synthetic T2 -weighted (T2 W) images calculated from T2 values to conventional T2 W images for CC staging. STUDY TYPE Retrospective. POPULATION Sixty-three patients with histopathologically confirmed CC. FIELD STRENGTH/SEQUENCE 3T, conventional T2 W turbo spin-echo, diffusion-weighted echo-planar, and accelerated T2 mapping sequence. ASSESSMENT T2 and ADC values between different pathological features of CC were compared. The diagnostic accuracies of conventional and synthetic T2 W images in staging were also compared. STATISTICAL TESTS Parameters were compared using an independent t-test, Wilcoxon signed-rank test, and the chi-square test. Receiver operating characteristic analysis was performed. RESULTS The T2 values varied significantly between well/moderately differentiated and poorly differentiated tumors ([92.8 ± 9.5 msec] vs. [83.8 ± 9.5 msec], P < 0.05) and between LVSI-positive and LVSI-negative CC ([82.2 ± 8.2 msec] vs. [93.9 ± 9.1 msec], P < 0.05). The ADC values showed a significant difference for grade ([0.76 ± 0.10 × 10-3 mm2 /s] vs. [0.65 ± 0.11 × 10-3 mm2 /s], P < 0.05) and no difference for LVSI status ([0.71 ± 0.11× 10-3 mm2 /s] vs. [0.73 ± 0.12× 10-3 mm2 /s], P = 0.472). There was no significant difference in T2 and ADC values between squamous cell carcinoma and adenocarcinoma (P = 0.378 and P = 0.661, respectively). In MRI staging, the conventional and synthetic T2 W images resulted in a similar accuracy (71% vs. 68%, P = 0.698). DATA CONCLUSION The accelerated T2 mapping sequence may facilitate grading and staging of CC by providing quantitative T2 maps and synthetic T2 W images in one acquisition. T2 values may be superior to ADC in predicting LVSI. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 2 J. MAGN. RESON. IMAGING 2020;52:1859-1869.
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Affiliation(s)
- Shujian Li
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jie Liu
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Feifei Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Meng Yang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zanxia Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingjing Liu
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jinxia Zhu
- MR Collaboration, Siemens Healthcare Ltd., Beijing, China
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Liu B, Ma WL, Zhang GW, Sun Z, Wei MQ, Hou WH, Hou BX, Wei LC, Huan Y. Potentialities of multi-b-values diffusion-weighted imaging for predicting efficacy of concurrent chemoradiotherapy in cervical cancer patients. BMC Med Imaging 2020; 20:97. [PMID: 32799809 PMCID: PMC7429470 DOI: 10.1186/s12880-020-00496-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2019] [Accepted: 08/06/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND To testify whether multi-b-values diffusion-weighted imaging (DWI) can be used to ultra-early predict treatment response of concurrent chemoradiotherapy (CCRT) in cervical cancer patients and to assess the predictive ability of concerning parameters. METHODS Fifty-three patients with biopsy proved cervical cancer were retrospectively recruited in this study. All patients underwent pelvic multi-b-values DWI before and at the 3rd day during treatment. The apparent diffusion coefficient (ADC), true diffusion coefficient (Dslow), perfusion-related pseudo-diffusion coefficient (Dfast), perfusion fraction (f), distributed diffusion coefficient (DDC) and intravoxel diffusion heterogeneity index(α) were generated by mono-exponential, bi-exponential and stretched exponential models. Treatment response was assessed based on Response Evaluation Criteria in Solid Tumors (RECIST v1.1) at 1 month after the completion of whole CCRT. Parameters were compared using independent t test or Mann-Whitney U test as appropriate. Receiver operating characteristic (ROC) curves was used for statistical evaluations. RESULTS ADC-T0 (p = 0.02), Dslow-T0 (p < 0.01), DDC-T0 (p = 0.03), ADC-T1 (p < 0.01), Dslow-T1 (p < 0.01), ΔADC (p = 0.04) and Δα (p < 0.01) were significant lower in non-CR group patients. ROC analyses showed that ADC-T1 and Δα exhibited high prediction value, with area under the curves of 0.880 and 0.869, respectively. CONCLUSIONS Multi-b-values DWI can be used as a noninvasive technique to assess and predict treatment response in cervical cancer patients at the 3rd day of CCRT. ADC-T1 and Δα can be used to differentiate good responders from poor responders.
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Affiliation(s)
- Bing Liu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, 127 Changle Western Road, Xi'an, P. R. China, 710032
| | - Wan-Ling Ma
- Department of radiology, Longgang District People's Hospital, Shenzhen, Guangdong, P. R. China, 518172
| | - Guang-Wen Zhang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, 127 Changle Western Road, Xi'an, P. R. China, 710032
| | - Zhen Sun
- Department of Orthopaedics, Xijing Hospital, Fourth Military Medical University, 127 Changle Western Road, Xi'an, P. R. China, 710032
| | - Meng-Qi Wei
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, 127 Changle Western Road, Xi'an, P. R. China, 710032
| | - Wei-Huan Hou
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, 127 Changle Western Road, Xi'an, P. R. China, 710032
| | - Bing-Xin Hou
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, 127 Changle Western Road, Xi'an, P. R. China, 710032
| | - Li-Chun Wei
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, 127 Changle Western Road, Xi'an, P. R. China, 710032
| | - Yi Huan
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, 127 Changle Western Road, Xi'an, P. R. China, 710032.
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Wang GZ, Guo LF, Gao GH, Li Y, Wang XZ, Yuan ZG. Magnetic Resonance Diffusion Kurtosis Imaging versus Diffusion-Weighted Imaging in Evaluating the Pathological Grade of Hepatocellular Carcinoma. Cancer Manag Res 2020; 12:5147-5158. [PMID: 32636677 PMCID: PMC7334009 DOI: 10.2147/cmar.s254371] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 05/21/2020] [Indexed: 12/27/2022] Open
Abstract
Purpose To investigate the diagnostic efficacy of diffusion kurtosis imaging (DKI) and conventional diffusion-weighted imaging (DWI) for pathological grading. Methods From December 2015 to January 2017, consecutive patients suspected of having hepatocellular carcinoma (HCC) without prior treatment were prospectively enrolled in this study. MRI examinations were performed before surgical treatment. HCC patients confirmed by surgical pathology were included in the study. The mean diffusivity (MD) values, mean kurtosis (MK) values, and apparent diffusion coefficient (ADC) were calculated. The differences and correlations of these parameters among different pathological grades were analyzed. The diagnostic efficiency of DKI and DWI for predicting high-grade HCC was evaluated by receiver operating characteristic (ROC) curves. Logistic regression analyses were used to evaluate the predictive factors for pathological grade. Results A total of 128 patients (79 males and 49 females, age: 56.9±10.9 years, range, 32–80) with primary HCC were included: grade I: 22 (17.2%) patients, grade II: 37 (28.9%) patients, grade III: 43 (33.6%) patients, grade IV: 26 (20.3%) patients. The MK values of stage I, II, III, and IV were 0.86±0.13, 1.06±0.11, 1.27±0.17, and 1.57±0.13, respectively. The MK values were significantly higher in the high-grade group than in the low-grade group and were positively correlated with pathological grade (rho =0.7417, P<0.001). The MK value demonstrated a larger area under the curve (AUC), with a value of 0.93 than the MD value, which had an AUC of 0.815 (P<0.001), and ADC, which had an AUC of 0.662 (P=0.01). The MK value (>1.19), ADC (≤1.29×10–3 mm2/s), and HBV (+) were independent predictors for the pathological grade of HCCs. Conclusion The MK values derived from DKI and the ADC values obtained from traditional DWI were more valuable than the MD values in predicting the histological grade of HCCs and could potentially guide clinical treatment before surgery.
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Affiliation(s)
- Guang-Zhi Wang
- Cheeloo College of Medicine, Shandong University, Jinan 250021, People's Republic of China.,Department of Medical Imaging Center, Affiliated Hospital, Weifang Medical University, Weifang 261053, People's Republic of China
| | - Ling-Fei Guo
- Department of MRI, Shandong Medical Imaging Research Institute, Cheeloo College of Medicine, Shandong University, Jinan 250021, People's Republic of China
| | - Gui-Hua Gao
- Department of MRI, Shandong Medical Imaging Research Institute, Cheeloo College of Medicine, Shandong University, Jinan 250021, People's Republic of China
| | - Yao Li
- Zhucheng People's Hospital Affiliated to Weifang Medical University, Weifang 262200, People's Republic of China
| | - Xi-Zhen Wang
- Department of Medical Imaging Center, Affiliated Hospital, Weifang Medical University, Weifang 261053, People's Republic of China
| | - Zhen-Guo Yuan
- Cheeloo College of Medicine, Shandong University, Jinan 250021, People's Republic of China.,Department of MRI, Shandong Medical Imaging Research Institute, Cheeloo College of Medicine, Shandong University, Jinan 250021, People's Republic of China
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Iima M. Perfusion-driven Intravoxel Incoherent Motion (IVIM) MRI in Oncology: Applications, Challenges, and Future Trends. Magn Reson Med Sci 2020; 20:125-138. [PMID: 32536681 PMCID: PMC8203481 DOI: 10.2463/mrms.rev.2019-0124] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Recent developments in MR hardware and software have allowed a surge of interest in intravoxel incoherent motion (IVIM) MRI in oncology. Beyond diffusion-weighted imaging (and the standard apparent diffusion coefficient mapping most commonly used clinically), IVIM provides information on tissue microcirculation without the need for contrast agents. In oncology, perfusion-driven IVIM MRI has already shown its potential for the differential diagnosis of malignant and benign tumors, as well as for detecting prognostic biomarkers and treatment monitoring. Current developments in IVIM data processing, and its use as a method of scanning patients who cannot receive contrast agents, are expected to increase further utilization. This paper reviews the current applications, challenges, and future trends of perfusion-driven IVIM in oncology.
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Affiliation(s)
- Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine.,Department of Clinical Innovative Medicine, Institute for Advancement of Clinical and Translational Science (iACT), Kyoto University Hospital
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Wang M, Perucho JA, Chan Q, Sun J, Ip P, Tse KY, Lee EY. Diffusion Kurtosis Imaging in the Assessment of Cervical Carcinoma. Acad Radiol 2020; 27:e94-e101. [PMID: 31324577 DOI: 10.1016/j.acra.2019.06.022] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Revised: 06/27/2019] [Accepted: 06/27/2019] [Indexed: 02/06/2023]
Abstract
RATIONALE AND OBJECTIVES To evaluate the additional value of diffusion kurtosis imaging (DKI) in the characterization of cervical carcinoma. MATERIALS AND METHODS Seventy-five patients (56.9 ± 13.4 years) with histologic-confirmed cervical carcinoma were included. Diffusion-weighted imaging (DWI) was acquired on a 3T MRI with five b values (0, 500, 800, 1000, and 1500 s/mm2). Data were analyzed based on DKI model (5 b values) and conventional DWI (0 and 1000 s/mm2). Largest single-slice region of interest (ROI) and volume of interest (VOI) were drawn around the tumor. Mean diffusivity (MD), mean kurtosis (MK), and apparent diffusion coefficient (ADC) of cervical carcinoma and normal myometrium were measured and compared. MD, MK, and ADC of cervical carcinoma were compared among histologic subtypes, tumor grades, and FIGO stages. RESULTS ROI- and VOI-derived DKI parameters and ADC were all in excellent consistency (intraclass correlation coefficient, ICC > 0.90, respectively). Cervical carcinoma had significantly lower MD, ADC, and higher MK than normal myometrium (p < 0.001). MD and ADC showed significant differences between histologic subtypes and FIGO stages, lower in squamous cell carcinoma than adenocarcinoma and higher in FIGO I-II than FIGO III-IV (p < 0.050), but not with tumor grade. No difference was observed in MK for different clinicopathologic features tested. CONCLUSION ROI and VOI analyses were in excellent consistency. MD and ADC were able to distinguish histologic subtypes and separating FIGO stages, MK could not. DKI showed no clear added value over conventional DWI in the characterization of cervical carcinoma.
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Reinhold C, Nougaret S. Radiomic ADC Metrics as a Tool to Better Understand Tumor Biology. Radiol Imaging Cancer 2020; 2:e200051. [PMID: 33779655 PMCID: PMC7983656 DOI: 10.1148/rycan.2020200051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Revised: 04/28/2020] [Accepted: 04/28/2020] [Indexed: 11/11/2022]
Affiliation(s)
- Caroline Reinhold
- From the Departments of Radiology and Obstetrics and Gynecology, McGill University Health Centre, Montreal, Canada (C.R.); Augmented Intelligence Precision Laboratory, Department of Radiology, MUHC Research Institute, 1001 Decarie Blvd, Montreal, QC, Canada H4A 3J1 (C.R.); Department of Radiology, Montpellier Cancer Institute, Montpellier, France (S.N.); and IRCM, Institut de Recherche en Cancérologie de Montpellier, INSERM, U1194, Montpellier, France (S.N.)
| | - Stephanie Nougaret
- From the Departments of Radiology and Obstetrics and Gynecology, McGill University Health Centre, Montreal, Canada (C.R.); Augmented Intelligence Precision Laboratory, Department of Radiology, MUHC Research Institute, 1001 Decarie Blvd, Montreal, QC, Canada H4A 3J1 (C.R.); Department of Radiology, Montpellier Cancer Institute, Montpellier, France (S.N.); and IRCM, Institut de Recherche en Cancérologie de Montpellier, INSERM, U1194, Montpellier, France (S.N.)
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Wormald BW, Doran SJ, Ind TE, D'Arcy J, Petts J, deSouza NM. Radiomic features of cervical cancer on T2-and diffusion-weighted MRI: Prognostic value in low-volume tumors suitable for trachelectomy. Gynecol Oncol 2020; 156:107-114. [PMID: 31685232 PMCID: PMC7001101 DOI: 10.1016/j.ygyno.2019.10.010] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2019] [Revised: 10/07/2019] [Accepted: 10/08/2019] [Indexed: 12/19/2022]
Abstract
BACKGROUND Textural features extracted from MRI potentially provide prognostic information additional to volume for influencing surgical management of cervical cancer. PURPOSE To identify textural features that differ between cervical tumors above and below the volume threshold of eligibility for trachelectomy and determine their value in predicting recurrence in patients with low-volume tumors. METHODS Of 378 patients with Stage1-2 cervical cancer imaged prospectively (3T, endovaginal coil), 125 had well-defined, histologically-confirmed squamous or adenocarcinomas with >100 voxels (>0.07 cm3) suitable for radiomic analysis. Regions-of-interest outlined the whole tumor on T2-W images and apparent diffusion coefficient (ADC) maps. Textural features based on grey-level co-occurrence matrices were compared (Mann-Whitney test with Bonferroni correction) between tumors greater (n = 46) or less (n = 79) than 4.19 cm3. Clustering eliminated correlated variables. Significantly different features were used to predict recurrence (regression modelling) in surgically-treated patients with low-volume tumors and compared with a model using clinico-pathological features. RESULTS Textural features (Dissimilarity, Energy, ClusterProminence, ClusterShade, InverseVariance, Autocorrelation) in 6 of 10 clusters from T2-W and ADC data differed between high-volume (mean ± SD 15.3 ± 11.7 cm3) and low-volume (mean ± SD 1.3 ± 1.2 cm3) tumors. (p < 0.02). In low-volume tumors, predicting recurrence was indicated by: Dissimilarity, Energy (ADC-radiomics, AUC = 0.864); Dissimilarity, ClusterProminence, InverseVariance (T2-W-radiomics, AUC = 0.808); Volume, Depth of Invasion, LymphoVascular Space Invasion (clinico-pathological features, AUC = 0.794). Combining ADC-radiomic (but not T2-radiomic) and clinico-pathological features improved prediction of recurrence compared to the clinico-pathological model (AUC = 0.916, p = 0.006). Findings were supported by bootstrap re-sampling (n = 1000). CONCLUSION Textural features from ADC maps and T2-W images differ between high- and low-volume tumors and potentially predict recurrence in low-volume tumors.
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Affiliation(s)
- Benjamin W Wormald
- MRI Unit, Division of Radiotherapy and Imaging, The Institute of Cancer Research and the Royal Marsden NHS Foundation Trust, Sutton, UK
| | - Simon J Doran
- MRI Unit, Division of Radiotherapy and Imaging, The Institute of Cancer Research and the Royal Marsden NHS Foundation Trust, Sutton, UK
| | - Thomas Ej Ind
- Department of Gynaecological Oncology, The Royal Marsden NHS Foundation Trust, London, UK; St George's University of London, Tooting, London, UK
| | - James D'Arcy
- MRI Unit, Division of Radiotherapy and Imaging, The Institute of Cancer Research and the Royal Marsden NHS Foundation Trust, Sutton, UK
| | - James Petts
- MRI Unit, Division of Radiotherapy and Imaging, The Institute of Cancer Research and the Royal Marsden NHS Foundation Trust, Sutton, UK
| | - Nandita M deSouza
- MRI Unit, Division of Radiotherapy and Imaging, The Institute of Cancer Research and the Royal Marsden NHS Foundation Trust, Sutton, UK.
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Lee J, Kim CK, Park SY. Histogram analysis of apparent diffusion coefficients for predicting pelvic lymph node metastasis in patients with uterine cervical cancer. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2019; 33:283-292. [DOI: 10.1007/s10334-019-00777-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Revised: 07/29/2019] [Accepted: 09/16/2019] [Indexed: 10/25/2022]
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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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Zhou Y, Zhang HX, Zhang XS, Sun YF, He KB, Sang XQ, Zhu YM, Kuai ZX. Non-mono-exponential diffusion models for assessing early response of liver metastases to chemotherapy in colorectal Cancer. Cancer Imaging 2019; 19:39. [PMID: 31217036 PMCID: PMC6585014 DOI: 10.1186/s40644-019-0228-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Accepted: 06/13/2019] [Indexed: 02/08/2023] Open
Abstract
Background Preoperative chemotherapy is becoming standard therapy for liver metastasis from colorectal cancer, so early assessment of treatment response is crucial to make a reasonable therapeutic regimen and avoid overtreatment, especially for patients with severe side effects. The role of three non-mono-exponential diffusion models, such as the kurtosis model, the stretched exponential model and the statistical model, were explored in this study to early assess the response to chemotherapy in patients with liver metastasis from colorectal cancer. Methods Thirty-three patients diagnosed as colorectal liver metastasis were evaluated in this study. Diffusion-weighted images with b values (0, 200, 500, 1000, 1500, 2000 s/mm2) were acquired at 3.0 T. The parameters (ADCk, K, DDC,α, Dsand σ) were derived from three non-mono-exponential models (the kurtosis, stretched exponential and statistical models) as well as their corresponding percentage changes before and after chemotherapy. The difference in above parameters between the response and non-response groups were analyzed with independent-samples T-test (normality) and Mann–Whitney U-test (non-normality). Meanwhile, receiver operating characteristic curve (ROC) analyses were performed to assess the response to chemotherapy. Results Significantly lower values of K (the kurtosis coefficient derived from the kurtosis model) and σ (the width of diffusion coefficient distribution in the statistical model) (P < 0.05) were observed in the respond group before treatment, as well as higher ΔK and Δσ values (P < 0.05) after the first cycle of chemotherapy were also found compared with the non-respond group. ROC analyses showed the K value acquired before treatment had the highest diagnostic performance (0.746) in distinguishing responders from non-responders. Furthermore, the high sensitivity (100%) and accuracy (76.3%) from the K value before treatment was found in assessing the response of colorectal liver metastasis to chemotherapy. Conclusions The non-mono-exponential diffusion models may be able to predict early response to chemotherapy in patients with colorectal liver metastasis.
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Affiliation(s)
- Yang Zhou
- Imaging Center, Harbin Medical University Cancer Hospital, Haping Road No.150, Nangang District, Harbin, 150081, China
| | - Hong-Xia Zhang
- Imaging Center, Harbin Medical University Cancer Hospital, Haping Road No.150, Nangang District, Harbin, 150081, China
| | - Xiu-Shi Zhang
- Imaging Center, Harbin Medical University Cancer Hospital, Haping Road No.150, Nangang District, Harbin, 150081, China
| | - Yun-Feng Sun
- Imaging Center, Harbin Medical University Cancer Hospital, Haping Road No.150, Nangang District, Harbin, 150081, China
| | - Kuang-Bang He
- Imaging Center, Harbin Medical University Cancer Hospital, Haping Road No.150, Nangang District, Harbin, 150081, China
| | - Xi-Qiao Sang
- Division of Respiratory Disease, The Fourth Hospital of Harbin Medical University, Harbin, 150001, China
| | - Yue-Min Zhu
- CREATIS, CNRS UMR 5220-INSERM U1206, University Lyon 1-INSA Lyon-University Jean Monnet Saint-Etienne, 69621, Lyon, France
| | - Zi-Xiang Kuai
- Imaging Center, Harbin Medical University Cancer Hospital, Haping Road No.150, Nangang District, Harbin, 150081, China.
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Winfield JM, Miah AB, Strauss D, Thway K, Collins DJ, deSouza NM, Leach MO, Morgan VA, Giles SL, Moskovic E, Hayes A, Smith M, Zaidi SH, Henderson D, Messiou C. Utility of Multi-Parametric Quantitative Magnetic Resonance Imaging for Characterization and Radiotherapy Response Assessment in Soft-Tissue Sarcomas and Correlation With Histopathology. Front Oncol 2019; 9:280. [PMID: 31106141 PMCID: PMC6494941 DOI: 10.3389/fonc.2019.00280] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Accepted: 03/27/2019] [Indexed: 02/05/2023] Open
Abstract
Purpose: To evaluate repeatability of quantitative multi-parametric MRI in retroperitoneal sarcomas, assess parameter changes with radiotherapy, and correlate pre-operative values with histopathological findings in the surgical specimens. Materials and Methods: Thirty patients with retroperitoneal sarcoma were imaged at baseline, of whom 27 also underwent a second baseline examination for repeatability assessment. 14/30 patients were treated with pre-operative radiotherapy and were imaged again after completing radiotherapy (50.4 Gy in 28 daily fractions, over 5.5 weeks). The following parameter estimates were assessed in the whole tumor volume at baseline and following radiotherapy: apparent diffusion coefficient (ADC), parameters of the intra-voxel incoherent motion model of diffusion-weighted MRI (D, f, D*), transverse relaxation rate, fat fraction, and enhancing fraction after gadolinium-based contrast injection. Correlation was evaluated between pre-operative quantitative parameters and histopathological assessments of cellularity and fat fraction in post-surgical specimens (ClinicalTrials.gov, registration number NCT01902667). Results: Upper and lower 95% limits of agreement were 7.1 and -6.6%, respectively for median ADC at baseline. Median ADC increased significantly post-radiotherapy. Pre-operative ADC and D were negatively correlated with cellularity (r = -0.42, p = 0.01, 95% confidence interval (CI) -0.22 to -0.59 for ADC; r = -0.45, p = 0.005, 95% CI -0.25 to -0.62 for D), and fat fraction from Dixon MRI showed strong correlation with histopathological assessment of fat fraction (r = 0.79, p = 10-7, 95% CI 0.69-0.86). Conclusion: Fat fraction on MRI corresponded to fat content on histology and therefore contributes to lesion characterization. Measurement repeatability was excellent for ADC; this parameter increased significantly post-radiotherapy even in disease categorized as stable by size criteria, and corresponded to cellularity on histology. ADC can be utilized for characterizing and assessing response in heterogeneous retroperitoneal sarcomas.
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Affiliation(s)
- Jessica M. Winfield
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Aisha B. Miah
- Sarcoma Unit, Department of Radiotherapy and Physics, The Royal Marsden NHS Foundation Trust, London, United Kingdom
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
| | - Dirk Strauss
- Department of Surgery, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Khin Thway
- Sarcoma Unit, Department of Radiotherapy and Physics, The Royal Marsden NHS Foundation Trust, London, United Kingdom
- Department of Histopathology, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - David J. Collins
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Nandita M. deSouza
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Martin O. Leach
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
| | - Veronica A. Morgan
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Sharon L. Giles
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Eleanor Moskovic
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Andrew Hayes
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Surgery, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Myles Smith
- Department of Surgery, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Shane H. Zaidi
- Sarcoma Unit, Department of Radiotherapy and Physics, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Daniel Henderson
- Sarcoma Unit, Department of Radiotherapy and Physics, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Christina Messiou
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
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Gu KW, Kim CK, Choi CH, Yoon YC, Park W. Prognostic value of ADC quantification for clinical outcome in uterine cervical cancer treated with concurrent chemoradiotherapy. Eur Radiol 2019; 29:6236-6244. [PMID: 30980126 DOI: 10.1007/s00330-019-06204-w] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Revised: 02/15/2019] [Accepted: 03/26/2019] [Indexed: 01/30/2023]
Abstract
OBJECTIVES To investigate the prognostic value of diffusion-weighted imaging (DWI) in predicting clinical outcome in patients with cervical cancer after concurrent chemoradiotherapy (CCRT). METHODS We enrolled 124 cervical cancer patients who received definitive CCRT and underwent 3 T-MRI before and 1 month after initiating treatment. The mean apparent diffusion coefficient (ADC) value was measured on the tumor and the changes in ADC percentage (ΔADCmean) between the two time points were calculated. The Cox proportion hazard model was used to evaluate the associations between imaging or clinical variables and progression-free survival (PFS), cancer-specific survival (CSS), and overall survival (OS). RESULTS In multivariate analysis, ΔADCmean was the only independent predictor of PFS (hazard ratio [HR] = 0.2379, p = 0.005), CSS (HR = 0.310, p = 0.024), and OS (HR = 0.217, p = 0.002). Squamous cell carcinoma antigen, histology, and pretreatment tumor size were significantly independent predictors of PFS. Tumor size response was significantly independent predictor of CSS and OS. Using the cutoff values of ΔADCmean, the PFS was significantly lower for ΔADCmean < 27.8% (p = 0.001). The CSS and OS were significantly lower for ΔADCmean < 16.1% (p = 0.002 and p < 0.001, respectively). CONCLUSION The percentage change in tumor ADC may be a useful predictor of disease progression and survival in patients with cervical cancer treated with CCRT. KEY POINTS • DWI is widely used as a potential marker of tumor viability. • Percentage change in tumor ADC (ΔADC mean ) was an independent marker of PFS, CSS, and OS. • Survival was better in patients with ≥ ΔADC mean cutoff value than with < the cutoff value.
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Affiliation(s)
- Kyo-Won Gu
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Chan Kyo Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea. .,Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea. .,Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea.
| | - Chel Hun Choi
- Departments of Obstetrics and Gynecology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Young Cheol Yoon
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Won Park
- Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
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Wang T, Gao T, Yang J, Yan X, Wang Y, Zhou X, Tian J, Huang L, Zhang M. Preoperative prediction of pelvic lymph nodes metastasis in early-stage cervical cancer using radiomics nomogram developed based on T2-weighted MRI and diffusion-weighted imaging. Eur J Radiol 2019; 114:128-135. [PMID: 31005162 DOI: 10.1016/j.ejrad.2019.01.003] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 12/29/2018] [Accepted: 01/04/2019] [Indexed: 12/13/2022]
Abstract
OBJECTIVE To explore an MRI-based radiomics nomogram for preoperatively predicting of pelvic lymph node (PLN) metastasis in patients with early-stage cervical cancer (ECC). METHODS Ninety-six patients with ECC were enrolled in this study. All patients underwent T2WI and DWI scans before radical hysterectomy with PLN dissection surgery. Radiomics features extracted from T2WI and DWI were selected by least absolute shrinkage and selection operation regression for further radimoics signature calculation. The discrimination of this radiomics signature for PLN metastasis was then assessed using a support vector machine (SVM) model. Subsequently, a radiomics nomogram was constructed based on the radiomics signature and clinicopathologic risk factors using a multivariable logistic regression method. The performance of the radiomics nomogram for the preoperative prediction of PLN metastasis was evaluated for discrimination and calibration. RESULTS The radiomics signatures demonstrated a good discrimination for PLN metastasis. A radiomics signature derived from joint T2WI and DWI yielded higher AUC than the signatures derived from T2WI or DWI alone. The radiomics nomogram integrating the radiomics signature with clinicopathologic risk factors showed a significant improvement over the nomogram based only on clinicopathologic risk factors in the primary cohort(C-index, 0.893 vs. 0.616; P = 4.311×10-5) and validation cohort(C-index, 0.922 vs. 0.799; P = 3.412 ×10-2).The calibration curves also showed good agreement. CONCLUSIONS The radiomics nomogram based on joint T2WI and DWI demonstrated an improved prediction ability for PLN metastasis in ECC. This noninvasive and convenient tool may be used to facilitate preoperative identification of PLN metastasis in patients with ECC.
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Affiliation(s)
- Tao Wang
- Department of Medical Imaging, First Affiliated Hospital of Xi'an Jiaotong University, No.277, West Yanta Road, Xi'an, 710061, Shaanxi, People's Republic of China; Department of Radiology, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, 710068, People's Republic of China
| | - Tingting Gao
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, People's Republic of China
| | - Jingbo Yang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, People's Republic of China
| | - Xuejiao Yan
- Room of MRI, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, 710068, People's Republic of China
| | - Yubo Wang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, People's Republic of China
| | - Xiaobo Zhou
- Department of Radiology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157, USA
| | - Jie Tian
- Key Laboratory of Molecular Imaging, Chinese Academy of Sciences, Beijing, 100080, People's Republic of China
| | - Liyu Huang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, People's Republic of China.
| | - Ming Zhang
- Department of Medical Imaging, First Affiliated Hospital of Xi'an Jiaotong University, No.277, West Yanta Road, Xi'an, 710061, Shaanxi, People's Republic of China.
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Kim HC, Seo N, Chung YE, Park MS, Choi JY, Kim MJ. Characterization of focal liver lesions using the stretched exponential model: comparison with monoexponential and biexponential diffusion-weighted magnetic resonance imaging. Eur Radiol 2019; 29:5111-5120. [PMID: 30796578 DOI: 10.1007/s00330-019-06048-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2018] [Revised: 12/23/2018] [Accepted: 01/25/2019] [Indexed: 01/17/2023]
Abstract
OBJECTIVE To compare the stretched exponential model of diffusion-weighted imaging (DWI) with monoexponential and biexponential models in terms of the ability to characterize focal liver lesions (FLLs). METHODS This retrospective study included 180 patients with FLLs who underwent magnetic resonance imaging including DWI with nine b values at 3.0 T. The distributed diffusion coefficient (DDC) and intravoxel diffusion heterogeneity index (α) from a stretched exponential model; true diffusion coefficient (Dt), pseudo-diffusion coefficient (Dp), and perfusion fraction (f) from a biexponential model; and apparent diffusion coefficient (ADC) were calculated for each lesion. Diagnostic performances of the parameters were assessed through receiver operating characteristic (ROC) analysis. For 20 patients with treated hepatic metastases, the correlation between the DWI parameters and the percentage of tumor necrosis on pathology was evaluated using the Spearman correlation coefficient. RESULTS DDC had the highest area under the ROC curve (AUC, 0.905) for differentiating malignant from benign lesions, followed by Dt (0.903) and ADC (0.866), without significant differences among them (DDC vs. Dt, p = 0.946; DDC vs. ADC, p = 0.157). For distinguishing hypovascular from hypervascular lesions, and hepatocellular carcinoma from metastasis, f had a significantly higher AUC than the other DWI parameters (p < 0.05). The α had the strongest correlation with the degree of tumor necrosis (ρ = 0.655, p = 0.002). CONCLUSION The DDC from stretched exponential model of DWI demonstrated excellent diagnostic performance for differentiating malignant from benign FLLs. The α is promising for evaluating the degree of necrosis in treated metastases. KEY POINTS • The stretched exponential DWI model is valuable for characterizing focal liver lesions. • The DDC from stretched exponential model shows excellent performance for differentiating malignant from benign focal liver lesions. • The α from stretched exponential model is promising for evaluating the degree of necrosis in hepatic metastases after chemotherapy.
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Affiliation(s)
- Hyung Cheol Kim
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Nieun Seo
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.
| | - Yong Eun Chung
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Mi-Suk Park
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Jin-Young Choi
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Myeong-Jin Kim
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
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Dregely I, Prezzi D, Kelly‐Morland C, Roccia E, Neji R, Goh V. Imaging biomarkers in oncology: Basics and application to MRI. J Magn Reson Imaging 2018; 48:13-26. [PMID: 29969192 PMCID: PMC6587121 DOI: 10.1002/jmri.26058] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Accepted: 03/26/2018] [Indexed: 12/12/2022] Open
Abstract
Cancer remains a global killer alongside cardiovascular disease. A better understanding of cancer biology has transformed its management with an increasing emphasis on a personalized approach, so-called "precision cancer medicine." Imaging has a key role to play in the management of cancer patients. Imaging biomarkers that objectively inform on tumor biology, the tumor environment, and tumor changes in response to an intervention complement genomic and molecular diagnostics. In this review we describe the key principles for imaging biomarker development and discuss the current status with respect to magnetic resonance imaging (MRI). LEVEL OF EVIDENCE 5 TECHNICAL EFFICACY: Stage 5 J. Magn. Reson. Imaging 2018;48:13-26.
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Affiliation(s)
- Isabel Dregely
- Biomedical Engineering, School of Biomedical Engineering & Imaging SciencesKing's Health Partners, St Thomas' HospitalLondon, UK
| | - Davide Prezzi
- Cancer Imaging, School of Biomedical Engineering & Imaging Sciences King's College London, King's Health Partners, St Thomas' Hospital, LondonUK
- RadiologyGuy's & St Thomas' NHS Foundation TrustLondonUK
| | - Christian Kelly‐Morland
- Cancer Imaging, School of Biomedical Engineering & Imaging Sciences King's College London, King's Health Partners, St Thomas' Hospital, LondonUK
- RadiologyGuy's & St Thomas' NHS Foundation TrustLondonUK
| | - Elisa Roccia
- Biomedical Engineering, School of Biomedical Engineering & Imaging SciencesKing's Health Partners, St Thomas' HospitalLondon, UK
| | - Radhouene Neji
- Biomedical Engineering, School of Biomedical Engineering & Imaging SciencesKing's Health Partners, St Thomas' HospitalLondon, UK
- MR Research CollaborationsSiemens HealthcareFrimleyUK
| | - Vicky Goh
- Cancer Imaging, School of Biomedical Engineering & Imaging Sciences King's College London, King's Health Partners, St Thomas' Hospital, LondonUK
- RadiologyGuy's & St Thomas' NHS Foundation TrustLondonUK
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