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Cheng JM, Luo WX, Tan BG, Pan J, Zhou HY, Chen TW. Whole-tumor histogram analysis of apparent diffusion coefficients for predicting lymphovascular space invasion in stage IB-IIA cervical cancer. Front Oncol 2023; 13:1206659. [PMID: 37404753 PMCID: PMC10315646 DOI: 10.3389/fonc.2023.1206659] [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: 04/16/2023] [Accepted: 06/01/2023] [Indexed: 07/06/2023] Open
Abstract
Objectives To investigate the value of apparent diffusion coefficient (ADC) histogram analysis based on whole tumor volume for the preoperative prediction of lymphovascular space invasion (LVSI) in patients with stage IB-IIA cervical cancer. Methods Fifty consecutive patients with stage IB-IIA cervical cancer were stratified into LVSI-positive (n = 24) and LVSI-negative (n = 26) groups according to the postoperative pathology. All patients underwent pelvic 3.0T diffusion-weighted imaging with b-values of 50 and 800 s/mm2 preoperatively. Whole-tumor ADC histogram analysis was performed. Differences in the clinical characteristics, conventional magnetic resonance imaging (MRI) features, and ADC histogram parameters between the two groups were analyzed. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of ADC histogram parameters in predicting LVSI. Results ADCmax, ADCrange, ADC90, ADC95, and ADC99 were significantly lower in the LVSI-positive group than in the LVSI-negative group (all P-values < 0.05), whereas no significant differences were reported for the remaining ADC parameters, clinical characteristics, and conventional MRI features between the groups (all P-values > 0.05). For predicting LVSI in stage IB-IIA cervical cancer, a cutoff ADCmax of 1.75×10-3 mm2/s achieved the largest area under ROC curve (Az) of 0.750, followed by a cutoff ADCrange of 1.36×10-3 mm2/s and ADC99 of 1.75×10-3 mm2/s (Az = 0.748 and 0.729, respectively), and the cutoff ADC90 and ADC95 achieved an Az of <0.70. Conclusion Whole-tumor ADC histogram analysis has potential value for preoperative prediction of LVSI in patients with stage IB-IIA cervical cancer. ADCmax, ADCrange, and ADC99 are promising prediction parameters.
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Affiliation(s)
- Jin-mei Cheng
- Sichuan Key Laboratory of Medical Imaging, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Wei-xiao Luo
- Sichuan Key Laboratory of Medical Imaging, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Bang-guo Tan
- Department of Radiology, Panzhihua Central Hospital, Panzhihua, Sichuan, China
| | - Jian Pan
- Department of General Practice, Taiping Town Central Health Center, Leshan, Sichuan, China
| | - Hai-ying Zhou
- Sichuan Key Laboratory of Medical Imaging, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Tian-wu Chen
- Sichuan Key Laboratory of Medical Imaging, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
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Takada A, Yokota H, Nemoto MW, Horikoshi T, Matsumoto K, Habu Y, Usui H, Nasu K, Shozu M, Uno T. Prognosis prediction of uterine cervical cancer using changes in the histogram and texture features of apparent diffusion coefficient during definitive chemoradiotherapy. PLoS One 2023; 18:e0282710. [PMID: 37000854 PMCID: PMC10065283 DOI: 10.1371/journal.pone.0282710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 02/21/2023] [Indexed: 04/03/2023] Open
Abstract
OBJECTIVES We investigated prospectively whether, in cervical cancer (CC) treated with concurrent chemoradiotherapy (CCRT), the Apparent diffusion coefficient (ADC) histogram and texture parameters and their change rates during treatment could predict prognosis. METHODS Fifty-seven CC patients treated with CCRT at our institution were included. They underwent MRI scans up to four times during the treatment course (1st, before treatment [n = 41], 2nd, at the start of image-guided brachytherapy (IGBT) [n = 41], 3rd, in the middle of IGBT [n = 27], 4th, after treatment [n = 53]). The entire tumor was manually set as the volume of interest (VOI) manually in the axial images of the ADC map by two radiologists. A total of 107 image features (morphology features 14, histogram features 18, texture features 75) were extracted from the VOI. The recurrence prediction values of the features and their change rates were evaluated by Receiver operating characteristics (ROC) analysis. The presence or absence of local and distant recurrence within two years was set as an outcome. The intraclass correlation coefficient (ICC) was also calculated. RESULTS The change rates in kurtosis between the 1st and 3rd, and 1st and 2nd MRIs, and the change rate in grey level co-occurrence matrix_cluster shade between the 2nd and 3rd MRIs showed particularly high predictive powers (area under the ROC curve = 0.785, 0.759, and 0.750, respectively), which exceeded the predictive abilities of the parameters obtained from pre- or post-treatment MRI only. The change rate in kurtosis between the 1st and 2nd MRIs had good reliability (ICC = 0.765). CONCLUSIONS The change rate in ADC kurtosis between the 1st and 2nd MRIs was the most reliable parameter, enabling us to predict prognosis early in the treatment course.
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Affiliation(s)
- Akiyo Takada
- Department of Radiology, Chiba University Hospital, Chiba, Japan
- * E-mail:
| | - Hajime Yokota
- Department of Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Miho Watanabe Nemoto
- Department of Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Takuro Horikoshi
- Department of Radiology, Chiba University Hospital, Chiba, Japan
| | - Koji Matsumoto
- Department of Radiology, Chiba University Hospital, Chiba, Japan
| | - Yuji Habu
- Department of Reproductive Medicine, Obstetrics and Gynecology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Hirokazu Usui
- Department of Reproductive Medicine, Obstetrics and Gynecology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Katsuhiro Nasu
- Department of Radiology, Chiba University Hospital, Chiba, Japan
| | - Makio Shozu
- Department of Reproductive Medicine, Obstetrics and Gynecology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Takashi Uno
- Department of Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Chiba, Japan
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Holopainen E, Lahtinen O, Könönen M, Anttila M, Vanninen R, Lindgren A. Greater increases in intratumoral apparent diffusion coefficients after chemoradiotherapy predict better overall survival of patients with cervical cancer. PLoS One 2023; 18:e0285786. [PMID: 37167301 PMCID: PMC10174495 DOI: 10.1371/journal.pone.0285786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 04/28/2023] [Indexed: 05/13/2023] Open
Abstract
PURPOSE To evaluate whether 1) the intratumoral apparent diffusion coefficients (ADCs) change during cervical cancer treatment and 2) the pretreatment ADC values or their change after treatment predict the treatment outcome or overall survival of patients with cervical cancer. METHODS We retrospectively enrolled 52 patients with inoperable cervical cancer treated with chemoradiotherapy, who had undergone diffusion weighted MRI before treatment and post external beam radiotherapy (EBRT) and concurrent chemotherapy. A subgroup of patients (n = 28) underwent altogether six consecutive diffusion weighted MRIs; 1) pretreatment, 2) post-EBRT and concurrent chemotherapy; 3-5) during image-guided brachytherapy (IGBT) and 6) after completing the whole treatment course. To assess interobserver and intertechnique reproducibility two observers independently measured the ADCs by drawing freehand a large region of interest (L-ROI) covering the whole tumor and three small ROIs (S-ROIs) in areas with most restricted diffusion. RESULTS Reproducibility was equally good for L-ROIs and S-ROIs. The pretreatment ADCs were higher in L-ROIs (883 mm2/s) than in S-ROIs (687 mm2/s, P < 0.001). The ADCs increased significantly between the pretreatment and post-EBRT scans (L-ROI: P < 0.001; S-ROI: P = 0.001). The ADCs remained significantly higher than pretreatment values during the whole IGBT. Using S-ROIs, greater increases in ADCs between pretreatment and post-EBRT MRI predicted better overall survival (P = 0.018). CONCLUSION ADC values significantly increase during cervical cancer treatment. Greater increases in ADC values between pretreatment and post-EBRT predicted better overall survival using S-ROIs. Standardized methods for timing and delineation of ADC measurements are advocated in future studies.
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Affiliation(s)
- Erikka Holopainen
- Department of Radiology, Kuopio University Hospital, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Clinical Radiology, University of Eastern Finland, Kuopio, Finland
| | - Olli Lahtinen
- Department of Radiology, Kuopio University Hospital, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Clinical Radiology, University of Eastern Finland, Kuopio, Finland
| | - Mervi Könönen
- Department of Radiology, Kuopio University Hospital, Kuopio, Finland
- Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland
| | - Maarit Anttila
- Department of Gynecology and Obstetrics, Kuopio University Hospital, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Obstetrics and Gynecology, University of Eastern Finland, Kuopio, Finland
| | - Ritva Vanninen
- Department of Radiology, Kuopio University Hospital, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Clinical Radiology, University of Eastern Finland, Kuopio, Finland
| | - Auni Lindgren
- Department of Gynecology and Obstetrics, Kuopio University Hospital, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Obstetrics and Gynecology, University of Eastern Finland, Kuopio, Finland
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Ciulla S, Celli V, Aiello AA, Gigli S, Ninkova R, Miceli V, Ercolani G, Dolciami M, Ricci P, Palaia I, Catalano C, Manganaro L. Post treatment imaging in patients with local advanced cervical carcinoma. Front Oncol 2022; 12:1003930. [PMID: 36465360 PMCID: PMC9710522 DOI: 10.3389/fonc.2022.1003930] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 09/26/2022] [Indexed: 10/29/2023] Open
Abstract
Cervical cancer (CC) is the fourth leading cause of death in women worldwide and despite the introduction of screening programs about 30% of patients presents advanced disease at diagnosis and 30-50% of them relapse in the first 5-years after treatment. According to FIGO staging system 2018, stage IB3-IVA are classified as locally advanced cervical cancer (LACC); its correct therapeutic choice remains still controversial and includes neoadjuvant chemo-radiotherapy, external beam radiotherapy, brachytherapy, hysterectomy or a combination of these modalities. In this review we focus on the most appropriated therapeutic options for LACC and imaging protocols used for its correct follow-up. We explore the imaging findings after radiotherapy and surgery and discuss the role of imaging in evaluating the response rate to treatment, selecting patients for salvage surgery and evaluating recurrence of disease. We also introduce and evaluate the advances of the emerging imaging techniques mainly represented by spectroscopy, PET-MRI, and radiomics which have improved diagnostic accuracy and are approaching to future direction.
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Affiliation(s)
- S Ciulla
- Department of Radiological, Oncological and Pathological Sciences, Sapienza, University of Rome, Rome, Italy
| | - V Celli
- Department of Radiological, Oncological and Pathological Sciences, Sapienza, University of Rome, Rome, Italy
| | - A A Aiello
- Department of Medical Sciences, University of Cagliari, Cagliari, Italy
| | - S Gigli
- Department of Radiological, Oncological and Pathological Sciences, Sapienza, University of Rome, Rome, Italy
| | - R Ninkova
- Department of Radiological, Oncological and Pathological Sciences, Sapienza, University of Rome, Rome, Italy
| | - V Miceli
- Department of Radiological, Oncological and Pathological Sciences, Sapienza, University of Rome, Rome, Italy
| | - G Ercolani
- Department of Radiological, Oncological and Pathological Sciences, Sapienza, University of Rome, Rome, Italy
| | - M Dolciami
- Department of Radiological, Oncological and Pathological Sciences, Sapienza, University of Rome, Rome, Italy
| | - P Ricci
- Department of Radiological, Oncological and Pathological Sciences, Sapienza, University of Rome, Rome, Italy
| | - I Palaia
- Department of Maternal and Child Health and Urological Sciences, Sapienza, University of Rome, Rome, Italy
| | - C Catalano
- Department of Radiological, Oncological and Pathological Sciences, Sapienza, University of Rome, Rome, Italy
| | - L Manganaro
- Department of Radiological, Oncological and Pathological Sciences, Sapienza, University of Rome, Rome, Italy
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Zhang X, Zhang Q, Xie L, An J, Wang S, Yu X, Zhao X. The Value of Whole-Tumor Texture Analysis of ADC in Predicting the Early Recurrence of Locally Advanced Cervical Squamous Cell Cancer Treated With Concurrent Chemoradiotherapy. Front Oncol 2022; 12:852308. [PMID: 35669419 PMCID: PMC9165468 DOI: 10.3389/fonc.2022.852308] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 04/19/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives To investigate the value of whole-tumor texture analysis of apparent diffusion coefficient (ADC) map in predicting the early recurrence of patients with locally advanced cervical squamous cell cancer (LACSC) treated with concurrent chemoradiotherapy (CCRT) and establish a combined prediction model including clinical variables and first-order texture features. Methods In total, 219 patients (training: n = 153; testing: n = 66) with stage IIB-IVA LACSC treated by CCRT between January 2014 and December 2019 were retrospectively enrolled in this study. Clinical variables and 22 first-order texture features extracted from ADC map were collected. The Mann-Whitney U test or independent sample t test, chi-square test or Fisher’s exact were used to analyze statistically significant parameters, logistic regression analysis was used for multivariate analysis, and receiver operating characteristic analysis was used to compare the diagnostic performance. Results In the clinical variables, T stage and lymph node metastasis (LNM) were independent risk factors, and the areas under the curve (AUCs) of the clinical model were 0.697 and 0.667 in the training and testing cohorts, the sensitivity and specificity were 48.8% and 85.5% in the training cohort, and 84.1% and 51.1% in the testing cohort, respectively. In the first-order texture features, mean absolute deviation (MAD) was the independent protective factor, with an AUC of 0.756 in the training cohort and 0.783 in the testing cohort. The sensitivity and specificity were 95.3% and 52.7% in the training cohort and 94.7% and 53.2% in the testing cohort, respectively. The combined model (MAD, T stage, and LNM) was established, it exhibited the highest AUC of 0.804 in the training cohort and 0.821 in the testing cohort, which was significantly higher than the AUC of the clinical prediction model. The sensitivity and specificity were 67.4% and 85.5% in the training cohort and 94.7% and 70.2% in the testing cohort, respectively. Conclusions The first-order texture features of the ADC map could be used along with clinical predictive biomarkers to predict early recurrence in patients with LACSC treated by CCRT.
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Affiliation(s)
- Xiaomiao 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, China
| | - 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, China
| | - Lizhi Xie
- GE Healthcare, MR Research, Beijing, China
| | - Jusheng An
- Department of Gynecologic Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 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, 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, China
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6
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Yang M, Sun Y, Wang S, Wang G, Zhang W, He J, Sun W, Yang M, Sun Y, Peet A. MRI-based Whole-Tumor Radiomics to Classify the Types of Pediatric Posterior Fossa Brain Tumor. Neurochirurgie 2022; 68:601-607. [PMID: 35667473 DOI: 10.1016/j.neuchi.2022.05.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 03/23/2022] [Accepted: 05/06/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Differential diagnosis between medulloblastoma (MB), ependymoma (EP) and astrocytoma (PA) is important due to differing medical treatment strategies and predicted survival. The aim of this study was to investigate non-invasive MRI-based radiomic analysis of whole tumors to classify the histologic tumor types of pediatric posterior fossa brain tumor and improve the accuracy of discrimination, using a random forest classifier. METHODS MRI images of 99 patients, with 59 MBs, 13 EPs and 27 PAs histologically confirmed by surgery and pathology before treatment, were included in this retrospective study. Registration was performed between the three sequences, and high- throughput features were extracted from manually segmented tumors on MR images of each case. The forest-based feature selection method was adopted to select the top ten significant features. Finally, the results were compared and analyzed according to the classification. RESULTS The top ten contributions according to the classifier of wavelet features all came from the ADC sequence. The random forest classifier achieved 100% accuracy on the training data and validated the best accuracy (0.938): sensitivity = 1.000, 0.948 and 0.808, specificity = 0.952, 0.926 and 1.000 for EP, MB and PA, respectively. CONCLUSION A random forest classifier based on the ADC sequence of the whole tumor provides more quantitative information than TIWI and T2WI in differentiating pediatric posterior fossa brain tumors. In particular, the histogram percentile value showed great superiority, which added diagnostic value in pediatric neuro-oncology.
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Affiliation(s)
- Ming Yang
- Department of Radiology, Children's Hospital of Nanjing Medical University, 210008 Nanjing, China.
| | - Yu Sun
- International Laboratory for Children's Medical Imaging Research, School of Biology Science and Medical Engineering, Southeast University, 210096 Nanjing, China.
| | - Shujie Wang
- Department of Radiology, Children's Hospital of Nanjing Medical University, 210008 Nanjing, China
| | - Gang Wang
- Department of Neurosurgery, Children's Hospital of Nanjing Medical University, 210008 Nanjing, China
| | - Wei Zhang
- Department of Radiology, Children's Hospital of Nanjing Medical University, 210008 Nanjing, China
| | - Junping He
- Department of Neurosurgery, Children's Hospital of Nanjing Medical University, 210008 Nanjing, China
| | - Weihang Sun
- International Laboratory for Children's Medical Imaging Research, School of Biology Science and Medical Engineering, Southeast University, 210096 Nanjing, China
| | - Ming Yang
- Department of Radiology, Children's Hospital of Nanjing Medical University, 210008 Nanjing, China
| | - Yu Sun
- Institute of Cancer & Genomic Science, University of Birmingham, B152TT, Birmingham, United Kingdom; International Laboratory for Children's Medical Imaging Research, School of Biology Science and Medical Engineering, Southeast University, 210096 Nanjing, China
| | - Andrew Peet
- Institute of Cancer & Genomic Science, University of Birmingham, B152TT, Birmingham, United Kingdom
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Manganaro L, Nicolino GM, Dolciami M, Martorana F, Stathis A, Colombo I, Rizzo S. Radiomics in cervical and endometrial cancer. Br J Radiol 2021; 94:20201314. [PMID: 34233456 PMCID: PMC9327743 DOI: 10.1259/bjr.20201314] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Radiomics is an emerging field of research that aims to find associations between quantitative information extracted from imaging examinations and clinical data to support the best clinical decision. In the last few years, some papers have been evaluating the role of radiomics in gynecological malignancies, mainly focusing on ovarian cancer. Nonetheless, cervical cancer is the most frequent gynecological malignancy in developing countries and endometrial cancer is the most common in western countries. The purpose of this narrative review is to give an overview of the latest published papers evaluating the role of radiomics in cervical and endometrial cancer, mostly evaluating association with tumor prognostic factors, with response to therapy and with prediction of recurrence and distant metastasis.
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Affiliation(s)
- Lucia Manganaro
- Department of Radiological, Oncological and Pathological Sciences; University of Rome Sapienza (IT), Rome, Italy
| | - Gabriele Maria Nicolino
- Post-graduate School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, Milan, Italy
| | - Miriam Dolciami
- Department of Radiological, Oncological and Pathological Sciences; University of Rome Sapienza (IT), Rome, Italy
| | - Federica Martorana
- Oncology Institute of Southern Switzerland, San Giovanni Hospital, 6500 Bellinzona, (CH), Switzerland
| | - Anastasios Stathis
- Oncology Institute of Southern Switzerland, San Giovanni Hospital, 6500 Bellinzona, (CH), Switzerland.,Facoltà di Scienze biomediche, Università della Svizzera italiana (USI), Via Buffi 13, 6900, Lugano (CH), Switzerland
| | - Ilaria Colombo
- Oncology Institute of Southern Switzerland, San Giovanni Hospital, 6500 Bellinzona, (CH), Switzerland
| | - Stefania Rizzo
- Facoltà di Scienze biomediche, Università della Svizzera italiana (USI), Via Buffi 13, 6900, Lugano (CH), Switzerland.,Istituto di Imaging della Svizzera Italiana (IIMSI), Ente Ospedaliero Cantonale, Via Tesserete 46, Lugano (CH), Switzerland
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Whole-Lesion Apparent Diffusion Coefficient Histogram Analysis: Significance for Discriminating Lung Cancer from Pulmonary Abscess and Mycobacterial Infection. Cancers (Basel) 2021; 13:cancers13112720. [PMID: 34072867 PMCID: PMC8198705 DOI: 10.3390/cancers13112720] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 05/01/2021] [Accepted: 05/28/2021] [Indexed: 11/17/2022] Open
Abstract
Simple Summary Diffusion-weighted magnetic resonance imaging (DWI) can differentiate malignant from benign pulmonary nodules and masses. However, it is difficult to differentiate pulmonary abscesses and mycobacterium infections (PAMIs) from lung cancers because PAMIs show restricted diffusion in DWI. The purpose of this study was to establish the role of ADC histogram for differentiating lung cancer from PAMI. There were 41 lung cancers and 19 PAMIs. Parameters more than 60% of AUC were ADC, maximal ADC, mean ADC, median ADC, most frequency ADC, kurtosis of ADC, and volume of lesion. There were significant differences between lung cancer and PAMI in ADC, mean ADC, median ADC, and most frequency ADC. ADC histogram has the potential to be a valuable tool to differentiate PAMI from lung cancer. Abstract Diffusion-weighted magnetic resonance imaging (DWI) can differentiate malignant from benign pulmonary nodules. However, it is difficult to differentiate pulmonary abscesses and mycobacterial infections (PAMIs) from lung cancers because PAMIs show restricted diffusion in DWI. The study purpose is to establish the role of ADC histogram for differentiating lung cancer from PAMI. There were 41 lung cancers (25 adenocarcinomas, 16 squamous cell carcinomas), and 19 PAMIs (9 pulmonary abscesses, 10 mycobacterial infections). Parameters more than 60% of the area under the ROC curve (AUC) were ADC, maximal ADC, mean ADC, median ADC, most frequency ADC, kurtosis of ADC, and volume of lesion. There were significant differences between lung cancer and PAMI in ADC, mean ADC, median ADC, and most frequency ADC. The ADC (1.19 ± 0.29 × 10−3 mm2/s) of lung cancer obtained from a single slice was significantly lower than that (1.44 ± 0.54) of PAMI (p = 0.0262). In contrast, mean, median, or most frequency ADC of lung cancer which was obtained in the ADC histogram was significantly higher than the value of each parameter of PAMI. ADC histogram could discriminate PAMIs from lung cancers by showing that AUCs of several parameters were more than 60%, and that several parameters of ADC of PAMI were significantly lower than those of lung cancer. ADC histogram has the potential to be a valuable tool to differentiate PAMI from lung cancer.
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Staging, recurrence and follow-up of uterine cervical cancer using MRI: Updated Guidelines of the European Society of Urogenital Radiology after revised FIGO staging 2018. Eur Radiol 2021; 31:7802-7816. [PMID: 33852049 DOI: 10.1007/s00330-020-07632-9] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 10/31/2020] [Accepted: 12/14/2020] [Indexed: 02/06/2023]
Abstract
OBJECTIVES The recommendations cover indications for MRI examination including acquisition planes, patient preparation, imaging protocol including multi-parametric approaches such as diffusion-weighted imaging (DWI-MR), dynamic contrast-enhanced imaging (DCE-MR) and standardised reporting. The document also underscores the value of whole-body 18-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG-PET/CT) and highlights potential future methods. METHODS In 2019, the ESUR female pelvic imaging working group reviewed the revised 2018 FIGO staging system, the up-to-date clinical management guidelines, and the recent imaging literature. The RAND-UCLA Appropriateness Method (RAM) was followed to develop the current ESUR consensus guidelines following methodological steps: literature research, questionnaire developments, panel selection, survey, data extraction and analysis. RESULTS The updated ESUR guidelines are recommendations based on ≥ 80% consensus among experts. If ≥ 80% agreement was not reached, the action was indicated as optional. CONCLUSIONS The present ESUR guidelines focus on the main role of MRI in the initial staging, response monitoring and evaluation of disease recurrence. Whole-body FDG-PET plays an important role in the detection of lymph nodes (LNs) and distant metastases. KEY POINTS • T2WI and DWI-MR are now recommended for initial staging, monitoring of response and evaluation of recurrence. • DCE-MR is optional; its primary role remains in the research setting. • T2WI, DWI-MRI and whole-body FDG-PET/CT enable comprehensive assessment of treatment response and recurrence.
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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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van Houdt PJ, Kallehauge JF, Tanderup K, Nout R, Zaletelj M, Tadic T, van Kesteren ZJ, van den Berg CAT, Georg D, Côté JC, Levesque IR, Swamidas J, Malinen E, Telliskivi S, Brynolfsson P, Mahmood F, van der Heide UA. Phantom-based quality assurance for multicenter quantitative MRI in locally advanced cervical cancer. Radiother Oncol 2020; 153:114-121. [PMID: 32931890 DOI: 10.1016/j.radonc.2020.09.013] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 09/07/2020] [Accepted: 09/08/2020] [Indexed: 02/08/2023]
Abstract
BACKGROUND AND PURPOSE A wide variation of MRI systems is a challenge in multicenter imaging biomarker studies as it adds variation in quantitative MRI values. The aim of this study was to design and test a quality assurance (QA) framework based on phantom measurements, for the quantitative MRI protocols of a multicenter imaging biomarker trial of locally advanced cervical cancer. MATERIALS AND METHODS Fifteen institutes participated (five 1.5 T and ten 3 T scanners). Each institute optimized protocols for T2, diffusion-weighted imaging, T1, and dynamic contrast-enhanced (DCE-)MRI according to system possibilities, institutional preferences and study-specific constraints. Calibration phantoms with known values were used for validation. Benchmark protocols, similar on all systems, were used to investigate whether differences resulted from variations in institutional protocols or from system variations. Bias, repeatability (%RC), and reproducibility (%RDC) were determined. Ratios were used for T2 and T1 values. RESULTS The institutional protocols showed a range in bias of 0.88-0.98 for T2 (median %RC = 1%; %RDC = 12%), -0.007 to 0.029 × 10-3 mm2/s for the apparent diffusion coefficient (median %RC = 3%; %RDC = 18%), and 0.39-1.29 for T1 (median %RC = 1%; %RDC = 33%). For DCE a nonlinear vendor-specific relation was observed between measured and true concentrations with magnitude data, whereas the relation was linear when phase data was used. CONCLUSION We designed a QA framework for quantitative MRI protocols and demonstrated for a multicenter trial for cervical cancer that measurement of consistent T2 and apparent diffusion coefficient values is feasible despite protocol differences. For DCE-MRI and T1 mapping with the variable flip angle method, this was more challenging.
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Affiliation(s)
- Petra J van Houdt
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | | | - Kari Tanderup
- Department of Clinical Medicine, Aarhus University Hospital, Denmark
| | - Remi Nout
- Department of Radiation Oncology, Leiden University Medical Center, the Netherlands
| | - Marko Zaletelj
- Department of Radiotherapy, Institute of Oncology Ljubljana, Slovenia
| | - Tony Tadic
- Radiation Medicine Program, Princess Margaret Cancer Center, Toronto, Canada
| | - Zdenko J van Kesteren
- Department of Radiation Oncology, Amsterdam University Medical Center, the Netherlands
| | | | - Dietmar Georg
- Division of Medical Radiation Physics, Department of Radiation Oncology, Medical University Of Vienna, Austria
| | - Jean-Charles Côté
- Department of Radiation Oncology, Centre Hospitalier de l'Universite de Montreal, Canada
| | - Ives R Levesque
- Medical Physics Unit and Gerald Bronfman Department of Oncology, McGill University, Montreal, Canada
| | - Jamema Swamidas
- Department of Radiation Oncology, Tata Memorial Centre, Mumbai, India
| | - Eirik Malinen
- Department of Medical Physics, Oslo University Hospital, Norway
| | - Sven Telliskivi
- Department of Radiation Oncology, North-Estonia Medical Centre, Tallinn, Estonia
| | - Patrik Brynolfsson
- Department of Translational Sciences, Skåne University Hospital, Lund, Sweden
| | - Faisal Mahmood
- Department of Oncology, Odense University Hospital, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Uulke A van der Heide
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
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Valenzuela RF, Kundra V, Madewell JE, Costelloe CM. Advanced Imaging in Musculoskeletal Oncology: Moving Away From RECIST and Embracing Advanced Bone and Soft Tissue Tumor Imaging (ABASTI) - Part I - Tumor Response Criteria and Established Functional Imaging Techniques. Semin Ultrasound CT MR 2020; 42:201-214. [PMID: 33814106 DOI: 10.1053/j.sult.2020.08.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
According to the Revised Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, the majority of bone metastases are considered to be nonmeasurable disease. Traditional response criteria rely on physical measurements. New criteria would be valuable if they incorporated newly developed imaging features in order to provide a more comprehensive assessment of oncological status. Advanced magnetic resonance imaging (MRI) sequences such as diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) with dynamic contrast-enhanced (DCE) perfusion imaging are reviewed in the context of the initial and post-therapeutic assessment of musculoskeletal tumors. Particular attention is directed to the pseudoprogression phenomenon in which a successfully treated tumor enlarges from the pretherapeutic baseline, followed by regression without a change in therapy.
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Affiliation(s)
- Raul Fernando Valenzuela
- The University of Texas MD Anderson Cancer Center, Department of Musculoskeletal Imaging, Houston, Texas.
| | - Vikas Kundra
- The University of Texas MD Anderson Cancer Center, Department of Musculoskeletal Imaging, Houston, Texas
| | - John E Madewell
- The University of Texas MD Anderson Cancer Center, Department of Musculoskeletal Imaging, Houston, Texas
| | - Colleen M Costelloe
- The University of Texas MD Anderson Cancer Center, Department of Musculoskeletal Imaging, Houston, Texas
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Yamada I, Oshima N, Miyasaka N, Wakana K, Wakabayashi A, Sakamoto J, Saida Y, Tateishi U, Kobayashi D. Texture Analysis of Apparent Diffusion Coefficient Maps in Cervical Carcinoma: Correlation with Histopathologic Findings and Prognosis. Radiol Imaging Cancer 2020; 2:e190085. [PMID: 33778713 DOI: 10.1148/rycan.2020190085] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2019] [Revised: 02/17/2020] [Accepted: 02/28/2020] [Indexed: 12/29/2022]
Abstract
Purpose To determine the feasibility of texture analysis of apparent diffusion coefficient (ADC) maps and to assess the performance of texture analysis and ADC to predict histologic grade, parametrial invasion, lymph node metastasis, International Federation of Gynecology and Obstetrics (FIGO) stage, recurrence, and recurrence-free survival (RFS) in patients with cervical carcinoma. Materials and Methods This retrospective study included 58 patients with cervical carcinoma who were examined with a 1.5-T MRI system and diffusion-weighted imaging with b values of 0 and 1000 sec/mm2. Software with volumes of interest on ADC maps was used to extract 45 texture features, including higher-order texture features. Receiver operating characteristic (ROC) analysis was performed to compare the diagnostic performance of ADC map random forest models and of ADC values. Dunnett test, Spearman rank correlation coefficient, Kaplan-Meier analyses, log-rank test, and Cox proportional hazards regression analyses were also used for statistical analyses. Results The ADC map random forest models showed a significantly larger area under the ROC curve (AUC) than the AUC of ADC values for predicting high-grade cervical carcinoma (P = .0036), but not for parametrial invasion, lymph node metastasis, stages III-IV, and recurrence (P = .0602, .3176, .0924, and .5633, respectively). The random forest models predicted that the mean RFS rates were significantly shorter for high-grade cervical carcinomas, parametrial invasion, lymph node metastasis, stages III-IV, and recurrence (P = .0405, < .0001, .0344, .0001, and .0015, respectively); the random forest models for parametrial invasion and stages III-IV were more useful than ADC values (P = .0018) for predicting RFS. Conclusion The ADC map random forest models were more useful for noninvasively evaluating histologic grade, parametrial invasion, lymph node metastasis, FIGO stage, and recurrence and for predicting RFS in patients with cervical carcinoma than were ADC values.Keywords: Comparative Studies, Genital/Reproductive, MR-Diffusion Weighted Imaging, MR-Imaging, Neoplasms-Primary, Pathology, Pelvis, Tissue Characterization, UterusSupplemental material is available for this article.© RSNA, 2020See also the commentary by Reinhold and Nougaret in this issue.
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Affiliation(s)
- Ichiro Yamada
- Departments of Diagnostic Radiology and Nuclear Medicine (I.Y., Y.S., U.T.), Comprehensive Reproductive Medicine (N.O., N.M., K.W., A.W.), Oral and Maxillofacial Radiology (J.S.), and Human Pathology (D.K.), Graduate School, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan
| | - Noriko Oshima
- Departments of Diagnostic Radiology and Nuclear Medicine (I.Y., Y.S., U.T.), Comprehensive Reproductive Medicine (N.O., N.M., K.W., A.W.), Oral and Maxillofacial Radiology (J.S.), and Human Pathology (D.K.), Graduate School, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan
| | - Naoyuki Miyasaka
- Departments of Diagnostic Radiology and Nuclear Medicine (I.Y., Y.S., U.T.), Comprehensive Reproductive Medicine (N.O., N.M., K.W., A.W.), Oral and Maxillofacial Radiology (J.S.), and Human Pathology (D.K.), Graduate School, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan
| | - Kimio Wakana
- Departments of Diagnostic Radiology and Nuclear Medicine (I.Y., Y.S., U.T.), Comprehensive Reproductive Medicine (N.O., N.M., K.W., A.W.), Oral and Maxillofacial Radiology (J.S.), and Human Pathology (D.K.), Graduate School, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan
| | - Akira Wakabayashi
- Departments of Diagnostic Radiology and Nuclear Medicine (I.Y., Y.S., U.T.), Comprehensive Reproductive Medicine (N.O., N.M., K.W., A.W.), Oral and Maxillofacial Radiology (J.S.), and Human Pathology (D.K.), Graduate School, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan
| | - Junichiro Sakamoto
- Departments of Diagnostic Radiology and Nuclear Medicine (I.Y., Y.S., U.T.), Comprehensive Reproductive Medicine (N.O., N.M., K.W., A.W.), Oral and Maxillofacial Radiology (J.S.), and Human Pathology (D.K.), Graduate School, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan
| | - Yukihisa Saida
- Departments of Diagnostic Radiology and Nuclear Medicine (I.Y., Y.S., U.T.), Comprehensive Reproductive Medicine (N.O., N.M., K.W., A.W.), Oral and Maxillofacial Radiology (J.S.), and Human Pathology (D.K.), Graduate School, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan
| | - Ukihide Tateishi
- Departments of Diagnostic Radiology and Nuclear Medicine (I.Y., Y.S., U.T.), Comprehensive Reproductive Medicine (N.O., N.M., K.W., A.W.), Oral and Maxillofacial Radiology (J.S.), and Human Pathology (D.K.), Graduate School, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan
| | - Daisuke Kobayashi
- Departments of Diagnostic Radiology and Nuclear Medicine (I.Y., Y.S., U.T.), Comprehensive Reproductive Medicine (N.O., N.M., K.W., A.W.), Oral and Maxillofacial Radiology (J.S.), and Human Pathology (D.K.), Graduate School, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan
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Combined dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted imaging to predict neoadjuvant chemotherapy effect in FIGO stage IB2-IIA2 cervical cancers. Radiol Med 2020; 125:1233-1242. [PMID: 32424659 DOI: 10.1007/s11547-020-01214-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Accepted: 04/27/2020] [Indexed: 12/24/2022]
Abstract
PURPOSE To explore the value of histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) quantitative parameters and apparent diffusion coefficient (ADC) values in predicting the neoadjuvant chemotherapy (NACT) response for cervical cancers. METHODS Sixty-three patients with pathologically proved stage IB2-IIA2 cervical cancer from March 2013 to January 2017 were retrospectively analyzed. They were divided into two groups on the basis of therapeutic response: the significant response (SR) group, which contains complete response patients and partial response patients, and nonsignificant response (non-SR) group, which contains progressive diseases and stable diseases. Clinical characteristics, DCE-MRI parameters (Ktrans, Kep, Ve), and ADC values before NACT were analyzed and compared between the two groups. RESULTS SR group and non-SR group were documented in 35 and 28 patients. The mean Ktrans value, 90th percentile Ktrans value, maximal Ktrans value, and 90th percentile ADC value of tumors in SR were significantly higher than those in non-SR group (P = 0.012, P = 0.022, P = 0.005, P = 0.033, respectively), and the mean Ve value and 10th percentile Ve value of tumors were significantly lower in SR group (P = 0.041, P = 0.033, respectively). Kep values did not significantly differ between SR and non-SR. The 90th percentile Ktrans value combined with the 90th percentile ADC value had the highest area under the curve at 0.740 (P = 0.003) to predict NACT effectiveness. CONCLUSION Histogram analysis of DCE-MRI multi-parameters combined with ADC values may serve as sensitive indicators for predicting NACT effectiveness in cervical cancers.
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15
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MRI texture features differentiate clinicopathological characteristics of cervical carcinoma. Eur Radiol 2020; 30:5384-5391. [PMID: 32382845 DOI: 10.1007/s00330-020-06913-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 04/23/2020] [Indexed: 02/06/2023]
Abstract
OBJECTIVES To evaluate MRI texture analysis in differentiating clinicopathological characteristics of cervical carcinoma (CC). METHODS Patients with newly diagnosed CC who underwent pre-treatment MRI were retrospectively reviewed. Texture analysis was performed using commercial software (TexRAD). Largest single-slice ROIs were manually drawn around the tumour on T2-weighted (T2W) images, apparent diffusion coefficient (ADC) maps and contrast-enhanced T1-weighted (T1c) images. First-order texture features were calculated and compared among histological subtypes, tumour grades, FIGO stages and nodal status using the Mann-Whitney U test. Feature selection was achieved by elastic net. Selected features from different sequences were used to build the multivariable support vector machine (SVM) models and the performances were assessed by ROC curves and AUC. RESULTS Ninety-five patients with FIGO stage IB~IVB were evaluated. A number of texture features from multiple sequences were significantly different among all the clinicopathological subgroups (p < 0.05). Texture features from different sequences were selected to build the SVM models. The AUCs of SVM models for discriminating histological subtypes, tumour grades, FIGO stages and nodal status were 0.841, 0.850, 0.898 and 0.879, respectively. CONCLUSIONS Texture features derived from multiple sequences were helpful in differentiating the clinicopathological signatures of CC. The SVM models with selected features from different sequences offered excellent diagnostic discrimination of the tumour characteristics in CC. KEY POINTS • First-order texture features are able to differentiate clinicopathological signatures of cervical carcinoma. • Combined texture features from different sequences can offer excellent diagnostic discrimination of the tumour characteristics in cervical carcinoma.
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16
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Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer. Eur Radiol 2019; 30:1297-1305. [DOI: 10.1007/s00330-019-06467-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Revised: 08/20/2019] [Accepted: 09/19/2019] [Indexed: 12/13/2022]
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17
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Lu Z, Wang L, Xia K, Jiang H, Weng X, Jiang J, Wu M. Prediction of Clinical Pathologic Prognostic Factors for Rectal Adenocarcinoma: Volumetric Texture Analysis Based on Apparent Diffusion Coefficient Maps. J Med Syst 2019; 43:331. [DOI: 10.1007/s10916-019-1464-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Accepted: 09/26/2019] [Indexed: 12/14/2022]
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Sun NN, Ge XL, Liu XS, Xu LL. Histogram analysis of DCE-MRI for chemoradiotherapy response evaluation in locally advanced esophageal squamous cell carcinoma. Radiol Med 2019; 125:165-176. [PMID: 31605354 DOI: 10.1007/s11547-019-01081-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2019] [Accepted: 09/12/2019] [Indexed: 12/11/2022]
Abstract
AIMS The aim of the study was to predict and assess treatment response by histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to patients with locally advanced esophageal squamous cell carcinoma receiving chemoradiotherapy (CRT). MATERIALS AND METHODS Seventy-two patients with locally advanced esophageal squamous cell carcinoma who underwent DCE-MRI before and after chemoradiotherapy were enrolled and divided into the complete response (CR) group and the non-CR group based on RECIST. The histogram parameters (10th percentile, 90th percentile, median, mean, standard deviation, skewness, and kurtosis) of pre-CRT and post-CRT were compared using a paired Student's t test in the CR and non-CR groups, respectively. The histogram parameter differences between the CR and the non-CR groups were compared using an unpaired Student's t test. A receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic performance. RESULTS The histogram parameters of Ktrans values were observed to have significantly decreased after chemoradiotherapy in the CR group. The CR responders showed significantly higher median, mean, and 10th and 90th percentile of pre-Ktrans values than those of the non-CR group. The histogram analysis indicated the decreased heterogeneity in the CR group after CRT. Esophageal cancer with higher pre-Ktrans and lower post-Ktrans values indicated a good treatment response to CRT. Pre-Ktrans-10th showed the best diagnostic performance in predicting the chemoradiotherapy response. CONCLUSIONS The histogram parameters of Ktrans are useful in the assessment and prediction of the chemoradiotherapy response in patients with advanced esophageal squamous cell carcinoma. DCE-MRI could serve as an adjunctive imaging technique for treatment planning.
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Affiliation(s)
- Na-Na Sun
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, 210000, China
| | - Xiao-Lin Ge
- Department of Radiotherapy, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210000, China
| | - Xi-Sheng Liu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, 210000, China.
| | - Lu-Lu Xu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, 210000, China
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Meyer HJ, Hamerla G, Höhn AK, Surov A. Whole Lesion Histogram Analysis Derived From Morphological MRI Sequences Might be Able to Predict EGFR- and Her2-Expression in Cervical Cancer. Acad Radiol 2019; 26:e208-e215. [PMID: 30318289 DOI: 10.1016/j.acra.2018.09.008] [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: 08/13/2018] [Revised: 08/31/2018] [Accepted: 09/09/2018] [Indexed: 01/10/2023]
Abstract
RATIONALE AND OBJECTIVES Histogram analysis is an imaging analysis in which a whole tumor can be assessed, and every voxel of a radiological image is issued into a histogram. Thereby, statistically information about tumor can be obtained. The purpose of the study was to analyze possible relationships between histogram parameters derived from conventional MRI sequences and several histopathological features in cervical squamous cell carcinomas. METHODS A total of 18 female patients (age range 32-79 years) with squamous cell cervical carcinoma were retrospectively enrolled into the study. In all cases, pelvic MRI with a clinically protocol was performed. Histogram analysis was performed as a whole lesion measurement, calculating several percentils, minimum, mean, median, mode, maximum, kurtosis, skewness, and entropy. Histopathological parameters included expression of epidermal-growth factor (EGFR), vascular endothelial growth factor, hypoxia-inducible factor 1-alpha, Her2, and Histone 3. Spearman's correlation coefficient was used to analyze associations between investigated parameters. RESULTS Several pre- and postcontrast derived T1-weighted parameters correlated inversely with EGFR expression. For precontrast T1-weighted images, the strongest correlation was found for p90 (ρ = -0.77, p = 0.004). For postcontrast T1-weighted images, the strongest correlation was observed for minimum (ρ = -0.64, p = 0.021). Several parameters derived from T2-weighted images were statistically significant different between Her2-positive and Her2 negative tumors. Skewness had the best p-value ( p = 0.004). CONCLUSIONS Histogram analysis parameters of T1-weighted and T2-weighted images reflect HER2 status and EGFR expression in cervical cancer. Histogram parameters cannot predict cell count, proliferation index, or angiogenesis related histopathological features.
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Affiliation(s)
- Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany.
| | - Gordian Hamerla
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
| | | | - Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
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Abstract
PURPOSE OF REVIEW To briefly review the radiomics concept, its applications, and challenges in oncology in the era of precision medicine. RECENT FINDINGS Over the last 5 years, more than 500 studies have evaluated the role of radiomics to predict tumor diagnosis, genetic pattern, tumor response to therapy, and survival in multiple cancers. This new post-processing method is aimed at extracting multiple quantitative features from the image and converting them into mineable data. Radiomics models developed have shown promising results and may play a role in the near future in the daily patient management especially to assess tumor heterogeneity acting as a whole tumor virtual biopsy. For now, radiomics is limited by its lack of standardization; future challenges will be to provide robust and reproducible metrics extracted from large multicenter databases.
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de Boer P, Mandija S, Werensteijn-Honingh AM, van den Berg CAT, de Leeuw AAC, Jürgenliemk-Schulz IM. Cervical cancer apparent diffusion coefficient values during external beam radiotherapy. PHYSICS & IMAGING IN RADIATION ONCOLOGY 2019; 9:77-82. [PMID: 33458429 PMCID: PMC7807732 DOI: 10.1016/j.phro.2019.03.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Revised: 02/28/2019] [Accepted: 03/01/2019] [Indexed: 01/22/2023]
Abstract
Background and purpose Apparent diffusion coefficient (ADC) reflects micro-enviromental changes and therefore might be useful in predicting recurrence prior to brachytherapy. The purpose of this study is to evaluate change in ADC of the primary tumour and pathologic lymph nodes during treatment and to correlate this with clinical outcome. Material and methods Twenty patients were included who received chemoradiation for locally advanced cervical cancer between July 2016 and November 2017. All patients underwent magnetic resonance imaging (MRI) prior to treatment, and three MRIs in weeks 1/2, 3 and 4 of treatment, including T2 and diffusion weighted imaging (b-values 0, 200, 800 s/mm2) for determining an ADC-map. Primary tumour was delineated on T2 and ADC-map and pathologic lymph nodes were delineated only on ADC-map. Results At time of analysis median follow-up was 15 (range 7-22) months. From MRI one to four, primary tumour on ADC-map showed a significant signal increase of 0.94 (range 0.74-1.46) × 10-3 mm2/s to 1.13 (0.98-1.49) × 10-3 mm2/s (p < 0.001). When tumour was delineated on T2, ADC-value signal increase (in tumour according to T2) was similar. All 46 delineated pathologic lymph nodes showed an ADC-value increase on average from 0.79 (range 0.33-1.12) × 10-3 mm2/s to 1.14 (0.59-1.75) × 10-3 mm2/s (p < 0.001). The mean tumour/suspected lymph node volumes decreased respectively 51/40%. Four patients developed relapse (one local and three nodal), without clear relation with ΔADC. However, the median volume decrease of the primary tumour was substantially lower in the failing patients compared to the group without relapse (19 vs. 57%). Conclusions ADC values can be acquired using T2-based tumour delineations unless there are substantial shifts between ADC-mapping and T2 acquisition. It remains plausible that ΔADC is a predictor for response to EBRT. However, the correlation in this study was not statistically significant.
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Affiliation(s)
- Peter de Boer
- Department of Radiation Oncology, University Medical Centre Utrecht, The Netherlands.,Department of Radiation Oncology, Amsterdam University Medical Centres (Amsterdam UMC) - University of Amsterdam (UvA), The Netherlands
| | - Stefano Mandija
- Centre for Image Sciences, University Medical Centre Utrecht, Heidelberglaan 100, Utrecht 3584 CX, The Netherlands
| | | | - Cornelis A T van den Berg
- Centre for Image Sciences, University Medical Centre Utrecht, Heidelberglaan 100, Utrecht 3584 CX, The Netherlands
| | - Astrid A C de Leeuw
- Department of Radiation Oncology, University Medical Centre Utrecht, The Netherlands
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Hunt A, Hansen VN, Oelfke U, Nill S, Hafeez S. Adaptive Radiotherapy Enabled by MRI Guidance. Clin Oncol (R Coll Radiol) 2018; 30:711-719. [PMID: 30201276 DOI: 10.1016/j.clon.2018.08.001] [Citation(s) in RCA: 79] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Revised: 08/10/2018] [Accepted: 08/20/2018] [Indexed: 12/11/2022]
Abstract
Adaptive radiotherapy (ART) strategies systematically monitor variations in target and neighbouring structures to inform treatment-plan modification during radiotherapy. This is necessary because a single plan designed before treatment is insufficient to capture the actual dose delivered to the target and adjacent critical structures during the course of radiotherapy. Magnetic resonance imaging (MRI) provides superior soft-tissue image contrast over current standard X-ray-based technologies without additional radiation exposure. With integrated MRI and radiotherapy platforms permitting motion monitoring during treatment delivery, it is possible that adaption can be informed by real-time anatomical imaging. This allows greater treatment accuracy in terms of dose delivered to target with smaller, individualised treatment margins. The use of functional MRI sequences would permit ART to be informed by imaging biomarkers, so allowing both personalised geometric and biological adaption. In this review, we discuss ART solutions enabled by MRI guidance and its potential gains for our patients across tumour types.
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Affiliation(s)
- A Hunt
- The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK
| | - V N Hansen
- The Institute of Cancer Research, London, UK; Joint Department of Physics, The Royal Marsden NHS Foundation Trust, London, UK
| | - U Oelfke
- The Institute of Cancer Research, London, UK; Joint Department of Physics, The Royal Marsden NHS Foundation Trust, London, UK
| | - S Nill
- The Institute of Cancer Research, London, UK; Joint Department of Physics, The Royal Marsden NHS Foundation Trust, London, UK
| | - S Hafeez
- The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK.
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Meyer HJ, Gundermann P, Höhn AK, Hamerla G, Surov A. Associations between whole tumor histogram analysis parameters derived from ADC maps and expression of EGFR, VEGF, Hif 1-alpha, Her-2 and Histone 3 in uterine cervical cancer. Magn Reson Imaging 2018; 57:68-74. [PMID: 30367998 DOI: 10.1016/j.mri.2018.10.016] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 09/23/2018] [Accepted: 10/22/2018] [Indexed: 12/09/2022]
Abstract
OBJECTIVE Diffusion weighted imaging (DWI) can be quantified by apparent diffusion coefficient (ADC) and can predict tissue microstructure. The aim of the present study was to analyze possible associations between ADC histogram based parameters with different histopathological parameters in cervical squamous cell carcinoma. MATERIALS AND METHODS 18 female patients (age range 32-79 years) with squamous cell cervical carcinoma were retrospectively enrolled. In all cases, pelvic MRI was performed with a DWI (b-values 0 and 1000 s/mm2). Histogram analysis was performed as a whole lesion measurement. Histopathological parameters included expression of EGFR, VEGF, Hif1-alpha, Her2 and Histone 3. Spearman's correlation coefficient was used to analyze associations between investigated parameters. RESULTS Analyze of the investigated ADC histogram parameters showed a good interreader variability, ranging from 0.705 for entropy to 0.959 for ADCmedian. EGFR expression correlated statistically significant with several histogram parameters. The highest correlation was observed for p75 (p = -0.562, P = 0.015). There were several correlations with histone 3, the highest with p25 (p = -0.610, P = 0.007). None of the ADC related parameters correlated statistically significant with expression of VEGF, Hif1-alpha and Her2. CONCLUSION Histogram analysis showed a good interreader agreement. ADC histogram parameters might be able to reflect expression of EGFR and histone 3 in cervical squamous cell carcinomas, but not expression of VEGF, Hif1-alpha and Her2.
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Affiliation(s)
- Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Liebigstraße 20, D-04103 Leipzig, Germany.
| | - Peter Gundermann
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Liebigstraße 20, D-04103 Leipzig, Germany.
| | - Anne Kathrin Höhn
- Department of Pathology, University of Leipzig, Liebigstraße 20, D-04103 Leipzig, Germany.
| | - Gordian Hamerla
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Liebigstraße 20, D-04103 Leipzig, Germany.
| | - Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Liebigstraße 20, D-04103 Leipzig, Germany.
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Chen J, Hua H, Pang J, Shi X, Bi W, Li Y, Xu W. The Value of Diffusion-Weighted Magnetic Resonance Imaging in Predicting the Efficacy of Radiation and Chemotherapy in Cervical Cancer. Open Life Sci 2018; 13:305-311. [PMID: 33817097 PMCID: PMC7874687 DOI: 10.1515/biol-2018-0037] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Accepted: 05/08/2018] [Indexed: 01/22/2023] Open
Abstract
Background To analyze the application value of apparent diffusion coefficient (ADC) and exponent apparent diffusion coefficient (EADC) in evaluating the efficacy of radiation and chemotherapy in cervical cancer using pre- and posttreatment diffusion-weighted magnetic resonance imaging (DW-MRI) scans. Methods 52 patients with cervical cancer were administered radiation and chemotherapy. Both MRI and DW-MRI were obtained at different stages. The ADC and EADC values, as well as the maximum tumor diameter, were measured and analyzed. Results We found that the ADC value increased after treatment, and the EADC value decreased. Changes in the calculated ADC occurred earlier than the morphologic changes of the tumors. A negative correlation was detected between reduced rates in the maximum tumor diameter two months after treatment and pretreatment ADC value (r = –0.658, P < 0.05). An ROC curve and nonlinear regression analysis showed that the formula, y = (1525500.122x2 – 4689.962x + 3.482) × 100%, can be used to calculate the percentage of complete remission after treatment according to the pretreatment ADC value. Conclusion Our data suggest that pretreatment ADC and EADC values are predictive of the efficacy of radiation and chemotherapy. Both ADC and EADC values during treatment were instrumental in early monitoring and dynamic observation.
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Affiliation(s)
- Jingjing Chen
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
| | - Hui Hua
- Department of Thyroid Surgery, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
| | - Jing Pang
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
| | - Xianglong Shi
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
| | - Weiqun Bi
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
| | - Yingduan Li
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
| | - Wenjian Xu
- Department of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao 266000, Shandong Province, China
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25
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Cervical Cancer: Associations between Metabolic Parameters and Whole Lesion Histogram Analysis Derived from Simultaneous 18F-FDG-PET/MRI. CONTRAST MEDIA & MOLECULAR IMAGING 2018; 2018:5063285. [PMID: 30154687 PMCID: PMC6098855 DOI: 10.1155/2018/5063285] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 06/12/2018] [Accepted: 06/25/2018] [Indexed: 01/16/2023]
Abstract
Multimodal imaging has been increasingly used in oncology, especially in cervical cancer. By using a simultaneous positron emission (PET) and magnetic resonance imaging (MRI, PET/MRI) approach, PET and MRI can be obtained at the same time which minimizes motion artefacts and allows an exact imaging fusion, which is especially important in anatomically complex regions like the pelvis. The associations between functional parameters from MRI and 18F-FDG-PET reflecting different tumor aspects are complex with inconclusive results in cervical cancer. The present study correlates histogram analysis and 18F-FDG-PET parameters derived from simultaneous FDG-PET/MRI in cervical cancer. Overall, 18 female patients (age range: 32–79 years) with histopathologically confirmed squamous cell cervical carcinoma were retrospectively enrolled. All 18 patients underwent a whole-body simultaneous 18F-FDG-PET/MRI, including diffusion-weighted imaging (DWI) using b-values 0 and 1000 s/mm2. Apparent diffusion coefficient (ADC) histogram parameters included several percentiles, mean, min, max, mode, median, skewness, kurtosis, and entropy. Furthermore, mean and maximum standardized uptake values (SUVmean and SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were estimated. No statistically significant correlations were observed between SUVmax or SUVmean and ADC histogram parameters. TLG correlated inversely with p25 (r=−0.486, P=0.041), p75 (r=−0.490, P=0.039), p90 (r=−0.513, P=0.029), ADC median (r=−0.497, P=0.036), and ADC mode (r=−0.546, P=0.019). MTV also showed significant correlations with several ADC parameters: mean (r=−0.546, P=0.019), p10 (r=−0.473, P=0.047), p25 (r=−0.569, P=0.014), p75 (r=−0.576, P=0.012), p90 (r=−0.585, P=0.011), ADC median (r=−0.577, P=0.012), and ADC mode (r=−0.597, P=0.009). ADC histogram analysis and volume-based metabolic 18F-FDG-PET parameters are related to each other in cervical cancer.
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