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Li X, Yuan F, Ni L, Li X. Meta-Analysis of MRI in Predicting Early Response to Radiotherapy and Chemotherapy in Esophageal Cancer. Acad Radiol 2024:S1076-6332(24)00619-6. [PMID: 39266443 DOI: 10.1016/j.acra.2024.08.055] [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: 04/28/2024] [Revised: 07/20/2024] [Accepted: 08/26/2024] [Indexed: 09/14/2024]
Abstract
RATIONALE AND OBJECTIVES At present, the application of magnetic resonance imaging (MRI) in the prediction of response to neoadjuvant therapy and concurrent chemoradiotherapy for the treatment of esophageal cancer still needs to be further explored, and its early differential value remains controversial, thus we carried out this systematic review with a meta-analysis. In the application, different MRI sequences and corresponding parameters are used for the differential diagnosis of the response to neoadjuvant therapy and concurrent chemoradiotherapy. METHODS All relevant studies evaluated the efficacy and response to MRI in neoadjuvant therapy or concurrent chemoradiotherapy for esophageal cancer on Pubmed, Embase, Cohrane Library, and Web of Science databases published before October 10, 2023 (inclusive) were systematically searched. A revised tool was used to assess the quality of diagnostic accuracy studies (QUADAS-2) to assess the risk of bias in the included original studies. A subgroup analysis of MRI sequences diffusion weighted imaging (DWI), dynamic contrast enhanced (DCE) and their corresponding different parameters, as well as the acquisition timepoints (before and after treatment) for different parameters, was performed during the meta-analysis. The bivariate mixed-effects model was used for meta-analysis. RESULTS 21 studies were finally included, involving 1128 patients with esophageal cancer. The sensitivity, specificity, and area under receiver operating characteristic curve (ROC curve) of DWI sequence for identifying response to concurrent chemoradiotherapy were 0.82 (95% CI: 0.74-0.87), 0.81 (95% CI: 0.72-0.87) and 0.88 (95% CI: 0.56-0.98), respectively. The sensitivity, specificity, and area under ROC curve of DCE sequence for identifying response to concurrent chemoradiotherapy were 0.78 (95% CI: 0.70-0.84), 0.65 (95% CI: 0.59-0.70) and 0.73 (95% CI: 0.50-0.88), respectively. In patients with esophageal cancer, the sensitivity, specificity, and area under the ROC curve of DWI sequences for identifying response to neoadjuvant therapy were 0.80 (95% CI: 0.69 - 0.88), 0.81 (95% CI: 0.69 - 0.89), and 0.88 (95% CI: 0.34 - 0.99), respectively; the sensitivity, specificity, and area under the ROC curve of DCE sequences for identifying response to neoadjuvant therapy were 0.84 (95% CI: 0.76 - 0.90), 0.61 (95% CI: 0.53 - 0.68), and 0.70 (95% CI: 0.27 - 0.94), respectively. CONCLUSIONS Based on the available evidence, MRI had a very good value in the early identification of response to neoadjuvant therapy and concurrent chemoradiotherapy for esophageal cancer, especially DWI. Apparent diffusion coefficient (ADC) value changes before and after treatment could be used as predictors of pathological response. Also, ADC value changes before and after treatment could be used as a tool to guide clinical decision-making.
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Affiliation(s)
- Xinyu Li
- lmaging Center, The First Affiliated Hospital College of Clinical Medicine of Henan University of Science and Technology, Henan Luoyang 471000, China (X.L., F.Y., L.N., X.L.).
| | - Fang Yuan
- lmaging Center, The First Affiliated Hospital College of Clinical Medicine of Henan University of Science and Technology, Henan Luoyang 471000, China (X.L., F.Y., L.N., X.L.)
| | - Li Ni
- lmaging Center, The First Affiliated Hospital College of Clinical Medicine of Henan University of Science and Technology, Henan Luoyang 471000, China (X.L., F.Y., L.N., X.L.)
| | - Xiaopan Li
- lmaging Center, The First Affiliated Hospital College of Clinical Medicine of Henan University of Science and Technology, Henan Luoyang 471000, China (X.L., F.Y., L.N., X.L.)
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Song T, Lu S, Qu J, Zhang H, Wang Z, Jia Z, Li H, Zhao Y, Qin J, Feng W, Wang S, Yan X. Intravoxel incoherent motion diffusion-weighted imaging in evaluating preoperative staging of esophageal squamous cell carcinoma : Evaluation of preoperative stage of primary tumour and prediction of lymph node metastases from esophageal cancer using IVIM: a prospective study. Cancer Imaging 2024; 24:116. [PMID: 39210470 PMCID: PMC11363402 DOI: 10.1186/s40644-024-00765-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 08/26/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND The aim of this research is to prospectively investigate the diagnostic performance of intravoxel incoherent motion (IVIM) using the integrated slice-specific dynamic shimming (iShim) technique in staging primary esophageal squamous cell carcinoma (ESCC) and predicting presence of lymph node metastases from ESCC. METHODS Sixty-three patients with ESCC were prospectively enrolled from April 2016 to April 2019. MR and IVIM using iShim technique (b = 0, 25, 50, 75, 100, 200, 400, 600, 800 s/mm2) were performed on 3.0T MRI system before operation. Primary tumour apparent diffusion coefficient (ADC) and IVIM parameters, including true diffusion coefficient (D), pseudodiffusion coefficient (D*), pseudodiffusion fraction (f) were measured by two independent radiologists. The differences in D, D*, f and ADC values of different T and N stages were assessed. Intraclass correlation coefficients (ICCs) were calculated to evaluate the interobserver agreement between two readers. The diagnostic performances of D, D*, f and ADC values in primary tumour staging and prediction of lymph node metastasis of ESCC were determined using receiver operating characteristic (ROC) curve analysis. RESULTS The inter-observer consensus was excellent for IVIM parameters and ADC (D: ICC = 0.922; D*: ICC = 0.892; f: ICC = 0.948; ADC: ICC = 0.958). The ADC, D, D* and f values of group T1 + T2 were significantly higher than those of group T3 + T4a [ADC: (2.55 ± 0.43) ×10- 3 mm2/s vs. (2.27 ± 0.40) ×10- 3 mm2/s, t = 2.670, P = 0.010; D: (1.82 ± 0.39) ×10- 3 mm2/s vs. (1.53 ± 0.33) ×10- 3 mm2/s, t = 3.189, P = 0.002; D*: 46.45 (30.30,55.53) ×10- 3 mm2/s vs. 32.30 (18.60,40.95) ×10- 3 mm2/s, z=-2.408, P = 0.016; f: 0.45 ± 0.12 vs. 0.37 ± 0.12, t = 2.538, P = 0.014]. The ADC, D and f values of the lymph nodes-positive (N+) group were significantly lower than those of lymph nodes-negative (N0) group [ADC: (2.10 ± 0.33) ×10- 3 mm2/s vs. (2.55 ± 0.40) ×10- 3 mm2/s, t=-4.564, P < 0.001; D: (1.44 ± 0.30) ×10- 3 mm2/s vs. (1.78 ± 0.37) ×10- 3 mm2/s, t=-3.726, P < 0.001; f: 0.32 ± 0.10 vs. 0.45 ± 0.11, t=-4.524, P < 0.001]. The combination of D, D* and f yielded the highest area under the curve (AUC) (0.814) in distinguishing group T1 + T2 from group T3 + T4a. D combined with f provided the highest diagnostic performance (AUC = 0.849) in identifying group N + and group N0 of ESCC. CONCLUSIONS IVIM may be used as an effective functional imaging technique to evaluate preoperative stage of primary tumour and predict presence of lymph node metastases from ESCC.
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Affiliation(s)
- Tao Song
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Shuang Lu
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Jinrong Qu
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
- Henan Province, 127 Dongming road, Jinshui District, Zhengzhou city, 450008, China.
| | - Hongkai Zhang
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Zhaoqi Wang
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Zhengyan Jia
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Hailiang Li
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Yan Zhao
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Jianjun Qin
- Department of Thoracic Surgery, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Wen Feng
- Department of Pathology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Shaoyu Wang
- MR Scientific Marketing, Siemens Healthineers, XI'an, 710065, China
| | - Xu Yan
- MR Scientific Marketing, Siemens Healthineers, Shanghai, 201318, China
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Li Y, Su X, Shang Y, Liu H, Wang W, Zhang A, Shi G. Comparative evaluation of imaging methods for prognosis assessment in esophageal squamous cell carcinoma: focus on diffusion-weighted magnetic resonance imaging, computed tomography and esophagography. Front Oncol 2024; 14:1397266. [PMID: 39026975 PMCID: PMC11256006 DOI: 10.3389/fonc.2024.1397266] [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: 03/07/2024] [Accepted: 06/17/2024] [Indexed: 07/20/2024] Open
Abstract
Objective To identify the most sensitive imaging examination method to evaluate the prognosis of esophageal squamous cell carcinoma (ESCC). Materials and methods Thirty patients with esophageal squamous cell carcinoma (ESCC) participated in the study and underwent chemoradiotherapy (CRT). They were divided into two groups based on their survival status: the survival group and non-survival group. The diagnostic tests were utilized to determine the most effective imaging examination method for assessing the prognosis. Results 1. There were no significant differences in tumor length shown on esophagography or computed tomography (CT) or the maximal esophageal wall thickness shown on CT at the specified time points between the two groups. 2. The tumor length on diffusion-weighted imaging (DWI) in the survival group was significantly lower than in the non-survival group at the end of the sixth week of treatment (P=0.001). The area under the ROC curve was 0.840 (P=0.002), and the diagnostic efficiency was moderately accurate. 3. The apparent diffusion coefficient (ADC) values of the survival group were significantly higher than those in the non-survival group at the end of the fourth week and sixth week of treatment (both P<0.001). Areas under the curve were 0.866 and 0.970, with P values of 0.001 and <0.001 and good diagnostic accuracy. Cox regression analyses indicated the ADC at the end of the sixth week of treatment was an independent risk factor. Conclusions Compared with esophagography and CT, DW-MRI has certain advantages in predicting the prognosis of ESCC.
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Affiliation(s)
- Yang Li
- Department of Computed Tomography and Magnetic Resonance Imaging, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Xiaohua Su
- Department of Oncology, Hebei General Hospital, Shijiazhuang, China
| | - Yuguang Shang
- Department of Radiotherapy, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Hui Liu
- Department of Computed Tomography and Magnetic Resonance Imaging, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Weishuai Wang
- CS Service AP, Siemens Healthineers Digital Health Technology (Shanghai) Co., Ltd. Beijing Branch, Beijing, China
| | - Andu Zhang
- Department of Radiotherapy, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Gaofeng Shi
- Department of Computed Tomography and Magnetic Resonance Imaging, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
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Bai B, Cui L, Chu F, Wang Z, Zhao K, Wang S, Wang S, Yan X, Wang M, Kamel IR, Yang G, Qu J. Multiple diffusion models for predicting pathologic response of esophageal squamous cell carcinoma to neoadjuvant chemotherapy. Abdom Radiol (NY) 2024:10.1007/s00261-024-04474-7. [PMID: 38954001 DOI: 10.1007/s00261-024-04474-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 06/22/2024] [Accepted: 06/24/2024] [Indexed: 07/04/2024]
Abstract
BACKGROUND To assess the feasibility and diagnostic performance of the fractional order calculus (FROC), continuous-time random-walk (CTRW), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), mono-exponential (MEM) and stretched exponential models (SEM) for predicting response to neoadjuvant chemotherapy (NACT) in patients with esophageal squamous cell carcinoma (ESCC). MATERIALS AND METHODS This study prospectively included consecutive ESCC patients with baseline and follow up MR imaging and pathologically confirmed cT1-4aN + M0 or T3-4aN0M0 and underwent radical resection after neoadjuvant chemotherapy (NACT) between July 2019 and January 2023. Patients were divided into pCR (TRG 0) and non-pCR (TRG1 + 2 + 3) groups according to tumor regression grading (TRG). The Pre-, Post- and Delta-treatment models were built. 18 predictive models were generated according to different feature categories, based on six models by five-fold cross-validation. Areas under the curve (AUCs) of the models were compared by using DeLong method. RESULTS Overall, 90 patients (71 men, 19 women; mean age, 64 years ± 6 [SD]) received NACT and underwent baseline and Post-NACT esophageal MRI, with 29 patients in the pCR group and 61 patients in the non-pCR group. Among 18 predictive models, The Pre-, Post-, and Delta-CTRW model showed good predictive efficacy (AUC = 0.722, 0.833 and 0.790). Additionally, the Post-FROC model (AUC = 0.907) also exhibited good diagnostic performance. CONCLUSIONS Our study indicates that the CTRW model, along with the Post-FROC model, holds significant promise for the future of NACT efficacy prediction in ESCC patients.
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Affiliation(s)
- Bingmei Bai
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Long Cui
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, 200062, China
| | - Funing Chu
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Zhaoqi Wang
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Keke Zhao
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Shuting Wang
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Shaoyu Wang
- MR Scientific Marketing, Siemens Healthineers, Shanghai, 201318, China
| | - Xu Yan
- MR Scientific Marketing, Siemens Healthineers, Shanghai, 201318, China
| | - Mengzhu Wang
- MR Research Collaboration, Siemens Healthineers Ltd, Beijing, 100000, China
| | - Ihab R Kamel
- Department of Radiology, Anschutz Medical Campus, University of Colorado Denver, 12401 East 17Th Avenue, Aurora, CO, 80045, USA
| | - Guang Yang
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, 200062, China
| | - Jinrong Qu
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China.
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Lu S, Wang C, Liu Y, Chu F, Jia Z, Zhang H, Wang Z, Lu Y, Wang S, Yang G, Qu J. The MRI radiomics signature can predict the pathologic response to neoadjuvant chemotherapy in locally advanced esophageal squamous cell carcinoma. Eur Radiol 2024; 34:485-494. [PMID: 37540319 DOI: 10.1007/s00330-023-10040-4] [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: 03/08/2023] [Revised: 05/26/2023] [Accepted: 06/19/2023] [Indexed: 08/05/2023]
Abstract
OBJECTIVES To investigate the MRI radiomics signatures in predicting pathologic response among patients with locally advanced esophageal squamous cell carcinoma (ESCC), who received neoadjuvant chemotherapy (NACT). METHODS Patients who underwent NACT from March 2015 to October 2019 were prospectively included. Each patient underwent esophageal MR scanning within one week before NACT and within 2-3 weeks after completion of NACT, prior to surgery. Radiomics features extracted from T2-TSE-BLADE were randomly split into the training and validation sets at a ratio of 7:3. According to the progressive tumor regression grade (TRG), patients were stratified into two groups: good responders (GR, TRG 0 + 1) and poor responders (non-GR, TRG 2 + 3). We constructed the Pre/Post-NACT model (Pre/Post-model) and the Delta-NACT model (Delta-model). Kruskal-Wallis was used to select features, logistic regression was used to develop the final model. RESULTS A total of 108 ESCC patients were included, and 3/2/4 out of 107 radiomics features were selected for constructing the Pre/Post/Delta-model, respectively. The selected radiomics features were statistically different between GR and non-GR groups. The highest area under the curve (AUC) was for the Delta-model, which reached 0.851 in the training set and 0.831 in the validation set. Among the three models, Pre-model showed the poorest performance in the training and validation sets (AUC, 0.466 and 0.596), and the Post-model showed better performance than the Pre-model in the training and validation sets (AUC, 0.753 and 0.781). CONCLUSIONS MRI-based radiomics models can predict the pathological response after NACT in ESCC patients, with the Delta-model exhibiting optimal predictive efficacy. CLINICAL RELEVANCE STATEMENT MRI radiomics features could be used as a useful tool for predicting the efficacy of neoadjuvant chemotherapy in esophageal carcinoma patients, especially in selecting responders among those patients who may be candidates to benefit from neoadjuvant chemotherapy. KEY POINTS • The MRI radiomics features based on T2WI-TSE-BLADE could potentially predict the pathologic response to NACT among ESCC patients. • The Delta-model exhibited the best predictive ability for pathologic response, followed by the Post-model, which similarly had better predictive ability, while the Pre-model performed less well in predicting TRG.
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Affiliation(s)
- Shuang Lu
- Department of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Chenglong Wang
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, 200062, China
| | - Yun Liu
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, 200062, China
| | - Funing Chu
- Department of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Zhengyan Jia
- Department of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Hongkai Zhang
- Department of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Zhaoqi Wang
- Department of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Yanan Lu
- Department of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Shuting Wang
- Department of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Guang Yang
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, 200062, China.
| | - Jinrong Qu
- Department of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China.
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Bao X, Bian D, Yang X, Wang Z, Shang M, Jiang G, Shi J. Multiparametric MRI for evaluation of pathological response to the neoadjuvant chemo-immunotherapy in resectable non-small-cell lung cancer. Eur Radiol 2023; 33:9182-9193. [PMID: 37382618 DOI: 10.1007/s00330-023-09813-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 03/26/2023] [Accepted: 03/28/2023] [Indexed: 06/30/2023]
Abstract
OBJECTIVES This study aimed to explore the predictive value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and diffusion kurtosis imaging (DKI) quantitative parameters for the response to neoadjuvant chemo-immunotherapy (NCIT) in resectable non-small-cell lung cancer (NSCLC) patients, so as to provide a basis for clinical individualized precision treatment. METHODS Treatment naive locally advanced NSCLC patients who enrolled in 3 prospective, open-label, and single-arm clinical trials and received NCIT were retrospectively analyzed in this study. Functional MRI imaging was performed at baseline and following 3 weeks of treatment as an exploratory endpoint to evaluate treatment efficacy. Univariate and multivariate logistic regressions were used to identify independent predictive parameters for NCIT response. Prediction models were built with statistically significant quantitative parameters and their combinations. RESULTS In total of 32 patients, 13 were classified as complete pathological response (pCR) and 19 were non-pCR. Post-NCIT ADC, ΔADC, and ΔD values in the pCR group were significantly higher than those in the non-pCR group, while the pre-NCIT D, post-NCIT Kapp, and ΔKapp were significantly lower than those in non-pCR group. Multivariate logistic regression analysis demonstrated that pre-NCIT D and post-NCIT Kapp values were independent predictors for NCIT response. The combined predictive model, which consisted of IVIM-DWI and DKI, showed the best prediction performance with AUC of 0.889. CONCLUSIONS The pre-NCIT D, post-NCIT parameters (ADC and Kapp) and Δ parameters (ΔADC, ΔD, and ΔKapp) were effective biomarkers for predicting pathologic response, and pre-NCIT D and post-NCIT Kapp values were independent predictors of NCIT response for NSCLC patients. CLINICAL RELEVANCE STATEMENT This exploratory study indicated that IVIM-DWI and DKI MRI imaging would predict pathologic response of neoadjuvant chemo-immunotherapy in locally advanced NSCLC patients at initial state and early treatment, which could help make clinical individualized treatment strategies. KEY POINTS • Effective NCIT treatment resulted in increased ADC and D values for NSCLC patients. • The residual tumors in non-pCR group tend to have higher microstructural complexity and heterogeneity, as measured by Kapp. • Pre-NCIT D and post-NCIT Kapp values were independent predictors of NCIT response.
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Affiliation(s)
- Xiao Bao
- Department of Radiology, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China
| | - Dongliang Bian
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China
| | - Xing Yang
- Department of Radiology, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China
| | - Zheming Wang
- Department of Radiology, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China
| | - Mingdong Shang
- Department of Radiology, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China
| | - Gening Jiang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China.
| | - Jingyun Shi
- Department of Radiology, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China.
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Zhao D, Fang X, Fan W, Meng L, Luo Y, Chen N, Li J, Zang X, Li M, Guo X, Cao B, Wu C, Tan X, Cai B, Ma L. A comparative study of functional MRI in predicting response of regional nodes to induction chemotherapy in patients with nasopharyngeal carcinoma. Front Oncol 2022; 12:960490. [PMID: 36119537 PMCID: PMC9472652 DOI: 10.3389/fonc.2022.960490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeTo identify and compare the value of functional MRI (fMRI) in predicting the early response of metastatic cervical lymph nodes (LNs) to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC) patients.MethodsThis prospective study collected 94 metastatic LNs from 40 consecutive NPC patients treated with IC from January 2021 to May 2021. Conventional diffusion-weighted imaging, diffusion kurtosis imaging, intravoxel incoherent motion, and dynamic contrast-enhanced magnetic resonance imaging were performed before and after IC. The parameter maps apparent diffusion coefficient (ADC), mean diffusion coefficient (MD), mean kurtosis (MK), Dslow, Dfast, perfusion fraction (PF), Ktrans, Ve, and Kep) of the metastatic nodes were calculated by the Functool postprocessing software. All LNs were classified as the responding group (RG) and non-responding group (NRG) according to Response Evaluation Criteria in Solid Tumors 1.1. The fMRI parameters were compared before and after IC and between the RG and the NRG. The significant parameters are fitted by logistic regression analysis to produce new predictive factor (PRE)–predicted probabilities. Logistic regression analysis and receiver operating characteristic (ROC) curves were performed to further identify and compare the efficacy of the parameters.ResultsAfter IC, the mean values of ADC, MD, and Dslow significantly increased, while MK, Dfast, and Ktrans values decreased dramatically, while no significant difference was detected in Ve and Kep. Compared with NRG, PF-pre and Ktrans-pre values in the RG were higher statistically. The areas under the ROC for the pretreatment PF, Ktrans, and PRE were 0.736, 0.722, and 0.810, respectively, with the optimal cutoff value of 222 × 10-4, 934 × 10-3/min, and 0.6624, respectively.ConclusionsThe pretreatment fMRI parameters PF and Ktrans showed promising potential in predicting the response of the metastatic LNs to IC in NPC patients.Clinical Trial RegistrationThis study was approved by the ethics board of the Chinese PLA General Hospital, and registered on 30 January 2021, in the Chinese Clinical Trial Registry; http://www.chictr.org.cn/showproj.aspx?proj=121198, identifier (ChiCTR2100042863).
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Affiliation(s)
- Dawei Zhao
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
- Department of Radiology, Characteristic Medical Center of Chinese People’s Armed Police Force, Tianjin, China
| | - Xuemei Fang
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
- Department of Ultrasound, Tianjin Medical University General Hospital Airport Hospital, Tianjin, China
| | - Wenjun Fan
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
- Affiliated Foshan Maternity & Child Healthcare Hospital, Southern Medical University, Foshan, China
- Department of Oncology, Armed Police Forces Corps Hospital of Henan Province, Zhengzhou, China
| | - Lingling Meng
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yanrong Luo
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Nanxiang Chen
- Department of Otolaryngology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jinfeng Li
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xiao Zang
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Meng Li
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xingdong Guo
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Biyang Cao
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Chenchen Wu
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xin Tan
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Boning Cai
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
- Department of Radiation Oncology, Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
- *Correspondence: Boning Cai, ; Lin Ma,
| | - Lin Ma
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
- Department of Radiation Oncology, Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
- *Correspondence: Boning Cai, ; Lin Ma,
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Su R, Wu S, Shen H, Chen Y, Zhu J, Zhang Y, Jia H, Li M, Chen W, He Y, Gao F. Combining Clinicopathology, IVIM-DWI and Texture Parameters for a Nomogram to Predict Treatment Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Patients. Front Oncol 2022; 12:886101. [PMID: 35712519 PMCID: PMC9197196 DOI: 10.3389/fonc.2022.886101] [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: 02/28/2022] [Accepted: 04/25/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives This study aimed to create a nomogram for the risk prediction of neoadjuvant chemoradiotherapy (nCRT) resistance in locally advanced rectal cancer (LARC). Methods Clinical data in this retrospective study were collected from a total of 135 LARC patients admitted to our hospital from June 2016 to December 2020. After screening by inclusion and exclusion criteria, 62 patients were included in the study. Texture analysis (TA) was performed on T2WI and DWI images. Patients were divided into response group (CR+PR) and no-response group (SD+PD) according to efficacy assessment. Multivariate analysis was performed on clinicopathology, IVIM-DWI and texture parameters for screening of independent predictors. A nomogram was created and model fit and clinical net benefit were assessed. Results Multivariate analysis of clinicopathology parameters showed that the differentiation and T stage were independent predictors (OR values were 14.516 and 11.589, resp.; P<0.05). Multivariate analysis of IVIM-DWI and texture parameters showed that f value and Rads-score were independent predictors (OR values were 0.855, 2.790, resp.; P<0.05). In this study, clinicopathology together with IVIM-DWI and texture parameters showed the best predictive efficacy (AUC=0.979). The nomogram showed good predictive performance and stability in identifying high-risk LARC patients who are resistant to nCRT (C-index=0.979). Decision curve analyses showed that the nomogram had the best clinical net benefit. Ten-fold cross-validation results showed that the average AUC value was 0.967, and the average C-index was 0.966. Conclusions The nomogram combining the differentiation, T stage, f value and Rads-score can effectively estimate the risk of nCRT resistance in patients with LARC.
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Affiliation(s)
- Rixin Su
- Department of Medical Oncology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, China
| | - Shusheng Wu
- Department of Medical Oncology, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Provincial Cancer Hospital, Hefei, China
| | - Hao Shen
- Department of Medical Oncology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, China
| | - Yaolin Chen
- Department of Medical Oncology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, China
| | - Jingya Zhu
- Department of Medical Oncology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, China
| | - Yu Zhang
- Department of Medical Oncology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, China
| | - Haodong Jia
- Department of Radiology, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Provincial Cancer Hospital, Hefei, China
| | - Mengge Li
- Department of Medical Oncology, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Provincial Cancer Hospital, Hefei, China
| | - Wenju Chen
- Department of Medical Oncology, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Provincial Cancer Hospital, Hefei, China
| | - Yifu He
- Department of Medical Oncology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, China.,Department of Medical Oncology, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Provincial Cancer Hospital, Hefei, China
| | - Fei Gao
- Department of Radiology, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Provincial Cancer Hospital, Hefei, China
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9
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Zhu Y, Jiang Z, Wang B, Li Y, Jiang J, Zhong Y, Wang S, Jiang L. Quantitative Dynamic-Enhanced MRI and Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Prediction of the Pathological Response to Neoadjuvant Chemotherapy and the Prognosis in Locally Advanced Gastric Cancer. Front Oncol 2022; 12:841460. [PMID: 35425711 PMCID: PMC9001840 DOI: 10.3389/fonc.2022.841460] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 02/28/2022] [Indexed: 01/31/2023] Open
Abstract
Background This study aimed to explore the predictive value of quantitative dynamic contrast-enhanced MRI (DCE-MRI) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) quantitative parameters for the response to neoadjuvant chemotherapy (NCT) in locally advanced gastric cancer (LAGC) patients, and the relationship between the prediction results and patients’ prognosis, so as to provide a basis for clinical individualized precision treatment. Methods One hundred twenty-nine newly diagnosed LAGC patients who underwent IVIM-DWI and DCE-MRI pretreatment were enrolled in this study. Pathological tumor regression grade (TRG) served as the reference standard of NCT response evaluation. The differences in DCE-MRI and IVIM-DWI parameters between pathological responders (pR) and pathological non-responders (pNR) groups were analyzed. Univariate and multivariate logistic regressions were used to identify independent predictive parameters for NCT response. Prediction models were built with statistically significant quantitative parameters and their combinations. The performance of these quantitative parameters and models was evaluated using receiver operating characteristic (ROC) analysis. Clinicopathological variables, DCE-MRI and IVIM-DWI derived parameters, as well as the prediction model were analyzed in relation to 2-year recurrence-free survival (RFS) by using Cox proportional hazards model. RFS was compared using the Kaplan–Meier method and the log-rank test. Results Sixty-nine patients were classified as pR and 60 were pNR. Ktrans, kep, and ve values in the pR group were significantly higher, while ADCstandard and D values were significantly lower than those in the pNR group. Multivariate logistic regression analysis demonstrated that Ktrans, kep, ve, and D values were independent predictors for NCT response. The combined predictive model, which consisted of DCE-MRI and IVIM-DWI, showed the best prediction performance with an area under the curve (AUC) of 0.922. Multivariate Cox regression analysis showed that ypStage III and NCT response predicted by the IVIM-DWI model were independent predictors of poor RFS. The IVIM-DWI model could significantly stratify median RFS (52 vs. 15 months) and 2-year RFS rate (72.3% vs. 21.8%) of LAGC. Conclusion Pretreatment DCE-MRI quantitative parameters Ktrans, kep, ve, and IVIM-DWI parameter D value were independent predictors of NCT response for LAGC patients. The regression model based on baseline DCE-MRI, IVIM-DWI, and their combination could help RFS stratification of LAGC patients.
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Affiliation(s)
- Yongjian Zhu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhichao Jiang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Bingzhi Wang
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ying Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jun Jiang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuxin Zhong
- Department of Pancreatic and Gastric Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Sicong Wang
- Pharmaceutical Diagnostic Team, GE Healthcare, Life Sciences, Beijing, China
| | - Liming Jiang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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10
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Hou W, Xue Y, Qian Y, Pan H, Xu M, Shen Y, Li X, Yu Y. Application of Intravoxel Incoherent Motion Diffusion-Weighted Imaging in Predicting and Monitoring Early Efficacy of Anti-Angiogenic Therapy in the C6 Glioma Rat Model. Front Oncol 2022; 11:842169. [PMID: 35155219 PMCID: PMC8831888 DOI: 10.3389/fonc.2021.842169] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 12/31/2021] [Indexed: 12/30/2022] Open
Abstract
Objective To investigate the feasibility of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) in evaluating early effects of anti-angiogenic therapy in the C6 glioma rat model. Methods Twenty-six rats of the C6 glioma model were randomly divided into a treatment group (received bevacizumab) and a control group (physiological saline). IVIM-DWI was performed on days 0, 1, 3, 5, and 7 after anti-angiogenic therapy and tumor growth and IVIM-DWI parameters were dynamically observed. Hematoxylin and eosin, CD34 microvessel density (MVD), proliferation of cell nuclear antigen (PCNA), and Hif-α staining were performed on day 7. One-way ANOVA was used to compare intra-group differences and an independent-samples t-test was used to compare inter-group differences of MRI parameters. Correlations between IVIM-DWI parameters, tumor size, and pathological results were analyzed. Results The relative change in tumor volume (ΔVolume) in the two groups differed significantly on days 5 and 7 (p = 0.038 and p < 0.001). The perfusion-related parameters D*- and f-values decreased in the treatment group and demonstrated significant differences compared with the control group on days 3, 5, and 7 (p = 0.033, p < 0.001, and p < 0.001, respectively). The diffusion-related parameters ADC and D-values increased in the treatment group and were found to be significantly differently different from the control group on days 5 and 7 (both p < 0.001). The initial D-value showed a negative correlation with ΔVolume (γ = −0.744, p < 0.001), whereas the initial D*-value and relative change of D-value had a positive correlation with ΔVolume (γ = 0.718, p < 0.001 and γ = 0.800, p < 0.001, respectively). MVD was strongly positively correlated with D*-value (r = 0.886, p = 0.019), PCNA was negatively correlated with ADC- and D-values (r = −0.848, p = 0.033; and r = −0.928 p = 0.008, respectively), and Hif-1α was strongly negatively correlated with D*-value (r = −0.879, p = 0.010). Conclusion IVIM-DWI was sensitive and accurate in predicting and monitoring the effects of early anti-angiogenesis therapy in a C6 glioma rat model.
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Affiliation(s)
- Weishu Hou
- Department of Radiology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yangyang Xue
- Department of Radiology, First Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Nuclear Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yinfeng Qian
- Department of Radiology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Hongli Pan
- Department of Radiology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Man Xu
- Department of Radiology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yujun Shen
- Department of Basic Medical Sciences, School of Basic Medical Sciences, Anhui Medical University, Hefei, China
| | - Xiaohu Li
- Department of Radiology, First Affiliated Hospital of Anhui Medical University, Hefei, China
- *Correspondence: Xiaohu Li, ; Yongqiang Yu,
| | - Yongqiang Yu
- Department of Radiology, First Affiliated Hospital of Anhui Medical University, Hefei, China
- *Correspondence: Xiaohu Li, ; Yongqiang Yu,
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11
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Zhao DW, Fan WJ, Meng LL, Luo YR, Wei J, Liu K, Liu G, Li JF, Zang X, Li M, Zhang XX, Ma L. Comparison of the pre-treatment functional MRI metrics' efficacy in predicting Locoregionally advanced nasopharyngeal carcinoma response to induction chemotherapy. Cancer Imaging 2021; 21:59. [PMID: 34758876 PMCID: PMC8579637 DOI: 10.1186/s40644-021-00428-0] [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: 06/20/2021] [Accepted: 09/10/2021] [Indexed: 02/07/2023] Open
Abstract
Background Functional MRI (fMRI) parameters analysis has been proven to be a promising tool of predicting therapeutic response to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC). The study was designed to identify and compare the value of fMRI parameters in predicting early response to IC in patients with NPC. Methods This prospective study enrolled fifty-six consecutively NPC patients treated with IC from January 2021 to May 2021. Conventional diffusion weighted imaging (DWI), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) protocols were performed before and after IC. Parameters maps (ADC, MD, MK, Dslow, Dfast, PF, Ktrans, Ve and Kep) of the primary tumor were calculated by the Functool post-processing software. The participants were classified as responding group (RG) and non-responding group (NRG) according to Response Evaluation Criteria in Solid Tumors 1.1. The fMRI parameters were compared before and after IC and between RG with NRG. Logistic regression analysis and ROC were performed to further identify and compare the efficacy of the parameters. Results After IC, the mean values of ADC(p < 0.001), MD(p < 0.001), Dslow(p = 0.001), PF(p = 0.030) and Ve(p = 0.003) significantly increased, while MK(p < 0.001), Dfast(p = 0.009) and Kep(p = 0.003) values decreased dramatically, while no significant difference was detected in Ktrans(p = 0.130). Compared with NRG, ADC-pre(p < 0.001), MD-pre(p < 0.001) and Dslow-pre(p = 0.002) values in RG were lower, while MK-pre(p = 0.017) values were higher. The areas under the ROC curves for the ADC-pre, MD-pre, MK-pre, Dslow-pre and PRE were 0.885, 0.855, 0.809, 0.742 and 0.912, with the optimal cutoff value of 1210 × 10− 6 mm2/s, 1010 × 10− 6 mm2/s, 832 × 10− 6, 835 × 10− 6 mm2/s and 0.799 respectively. Conclusions The pretreatment conventional DWI (ADC), DKI (MD and MK), and IVIM (Dslow) values derived from fMRI showed a promising potential in predicting the response of the primary tumor to IC in NPC patients. Trial registration This study was approved by ethics board of the Chinese PLA General Hospital, and registered on January 30, 2021, in Chinese Clinical Trial Registry (ChiCTR2100042863). Supplementary Information The online version contains supplementary material available at 10.1186/s40644-021-00428-0.
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Affiliation(s)
- Da-Wei Zhao
- Medical School of Chinese PLA, No.28 Fuxing Road, Beijing, 100853, China.,Department of Radiology, Pingjin Hospital, Characteristic Medical center of Chinese People's Armed Police Force, Tianjin, China.,Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Wen-Jun Fan
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China.,Affiliated Foshan Maternity & Child Healthcare Hospital, Southern Medical University, Foshan, China.,Armed Police Forces Corps Hospital of Henan Province, No.1 Kangfu Road, Zhengzhou, 450052, China
| | - Ling-Ling Meng
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yan-Rong Luo
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jian Wei
- Department of Otolaryngology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Kun Liu
- Department of Otolaryngology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Gang Liu
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jin-Feng Li
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xiao Zang
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Meng Li
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xin-Xin Zhang
- Department of Otolaryngology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Lin Ma
- Department of Radiation Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China.
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Zhang HJ, Chen G, Chen SW, Fu ZW, Zhou HF, Feng ZB, Mo JX, Li CB, Liu J. Overexpression of cyclin-dependent kinase 1 in esophageal squamous cell carcinoma and its clinical significance. FEBS Open Bio 2021; 11:3126-3141. [PMID: 34586751 PMCID: PMC8564100 DOI: 10.1002/2211-5463.13306] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 09/04/2021] [Accepted: 09/28/2021] [Indexed: 12/25/2022] Open
Abstract
Cyclin‐dependent kinase 1 (CDK1) plays a significant role in certain malignancies. However, it remains unclear whether CDK1 plays a role in esophageal squamous cell carcinoma (ESCC). The aim of this study was to analyze the expression and clinical value of CDK1 in ESCC. CDK1 protein in 151 ESCC tissues and 138 normal esophageal tissues was detected by immunohistochemistry. RNA‐seq of eight pairs of ESCC and adjacent esophageal specimens was performed to evaluate the levels of CDK1 mRNA. Microarray and external RNA‐seq data from 664 cases of ESCC and 1733 cases of control tissues were used to verify the difference in CDK1 expression between the two groups. A comprehensive analysis of all data was performed to evaluate the difference in CDK1 between ESCC tissues and control tissues. Further, functional enrichment analyses were performed based on differentially expressed genes (DEGs) of ESCC and co‐expressed genes (CEGs) of CDK1. In addition, a lncRNA‐miRNA‐CDK1 network was constructed. The expression of CDK1 protein was obviously increased in ESCC tissues (3.540 ± 2.923 vs. 1.040 ± 1.632, P < 0.001). RNA‐seq indicated that the mRNA level of CDK1 was also highly expressed in ESCC tissues (5.261 ± 0.703 vs. 2.229 ± 1.161, P < 0.0001). Comprehensive analysis revealed consistent up‐regulation of CDK1 (SMD = 1.41; 95% CI 1.00–1.83). Further, functional enrichment analyses revealed that the functions of these genes were mainly concentrated in the cell cycle. A triple regulatory network of PVT1‐hsa‐miR‐145‐5p/hsa‐miR‐30c‐5p‐CDK1 was constructed using in silico analysis. In summary, overexpression of CDK1 is closely related to ESCC tumorigenesis.
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Affiliation(s)
- Han-Jie Zhang
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Gang Chen
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Shang-Wei Chen
- Department of Cardio-Thoracic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Zong-Wang Fu
- Department of Cardio-Thoracic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Hua-Fu Zhou
- Department of Cardio-Thoracic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Zhen-Bo Feng
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jun-Xian Mo
- Department of Cardio-Thoracic Surgery, The Seventh Affiliated Hospital of Guangxi Medical University, Wuzhou, China.,Wuzhou Gongren Hospital, Wuzhou, China
| | - Chang-Bo Li
- Department of Cardio-Thoracic Surgery, The Seventh Affiliated Hospital of Guangxi Medical University, Wuzhou, China.,Wuzhou Gongren Hospital, Wuzhou, China
| | - Jun Liu
- Department of Cardio-Thoracic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
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