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Takami Y, Norikane T, Kimura N, Mitamura K, Yamamoto Y, Miyake K, Miyoshi M, Nishiyama Y. Relationship between multi-pool model-based chemical exchange saturation transfer imaging, intravoxel incoherent motion MRI, and 11C-methionine uptake on PET/CT in patients with gliomas. Magn Reson Imaging 2024; 111:148-156. [PMID: 38729226 DOI: 10.1016/j.mri.2024.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 05/01/2024] [Accepted: 05/07/2024] [Indexed: 05/12/2024]
Abstract
PURPOSE Magnetization transfer ratio asymmetry (MTRasym) analysis is used for chemical exchange saturation transfer (CEST) in patients with gliomas; however, this approach has limitations. CEST imaging using a multi-pool model (MPM) may allow a more detailed assessment of gliomas; however, its mechanism remains unknown. This study aimed to assess the relationship between CEST imaging by MPM, intravoxel incoherent motion (IVIM), and 11C-methionine (11C-MET) uptake on positron emission tomography/computed tomography (PET/CT) to clarify the clinical significance of CEST imaging using MPM in gliomas. METHODS This retrospective study included 17 patients with gliomas who underwent 11C-MET PET/CT at our institution between January 2020 and January 2022. Two-dimensional axial CEST imaging was conducted using single-shot fast-spin echo acquisition at 3 T. The apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), f, MTRasym (3.5 ppm), parameters of MPM-based CEST imaging, and tumor-to-contralateral normal brain tissue (T/N) ratio were calculated using a region-of-interest analysis. Shapiro-Wilk test, weighted kappa coefficient, and Spearman's rank correlation coefficients were used for statistical analysis. RESULTS Significant correlations were found between APT_T1 and T/N ratio (ρ = 0.87, p < 0.001), APT_T2 and T/N ratio (ρ = 0.47, p < 0.05), MTRasym and T/N ratio (ρ = 0.55, p < 0.01), and T2/T1 and T/N ratio (ρ = -0.36, p < 0.05). Furthermore, significant correlations were observed between APT_T1 and ADC (ρ = -0.67, p < 0.001), APT_T1 and D (ρ = -0.70, p < 0.001), APT_T2 and D* (ρ = -0.45, p < 0.05), and T2/T1 and D (ρ = 0.39, p < 0.05). CONCLUSION These preliminary findings indicate that MPM-based CEST imaging parameters correlate with IVIM and 11C-MET uptake on PET/CT in patients with gliomas. In particular, the new parameter APT_T1 correlated more strongly with 11C-MET uptake compared to the traditional CEST parameter MTRasym.
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Affiliation(s)
- Yasukage Takami
- Department of Radiology, Faculty of Medicine, Kagawa University, Kagawa, Japan.
| | - Takashi Norikane
- Department of Radiology, Faculty of Medicine, Kagawa University, Kagawa, Japan
| | - Naruhide Kimura
- Department of Radiology, Faculty of Medicine, Kagawa University, Kagawa, Japan
| | - Katsuya Mitamura
- Department of Radiology, Faculty of Medicine, Kagawa University, Kagawa, Japan
| | - Yuka Yamamoto
- Department of Radiology, Faculty of Medicine, Kagawa University, Kagawa, Japan
| | - Keisuke Miyake
- Department of Neurological Surgery, Faculty of Medicine, Kagawa University, Kagawa, Japan
| | - Mitsuharu Miyoshi
- Global MR Clinical Solution and Research Collaboration, GE HealthCare, Tokyo, Japan
| | - Yoshihiro Nishiyama
- Department of Radiology, Faculty of Medicine, Kagawa University, Kagawa, Japan
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Zhong S, Ai C, Ding Y, Tan J, Jin Y, Wang H, Zhang H, Li M, Zhu R, Gu S, Zhang Y. Combining multimodal diffusion-weighted imaging and morphological parameters for detecting lymph node metastasis in cervical cancer. Abdom Radiol (NY) 2024:10.1007/s00261-024-04494-3. [PMID: 38990301 DOI: 10.1007/s00261-024-04494-3] [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: 05/15/2024] [Revised: 07/05/2024] [Accepted: 07/06/2024] [Indexed: 07/12/2024]
Abstract
BACKGROUND Accurate detection of lymph node metastasis (LNM) is crucial for determining the tumor stage, selecting optimal treatment, and estimating the prognosis for cervical cancer. This study aimed to assess the diagnostic efficacy of multimodal diffusion-weighted imaging (DWI) and morphological parameters alone or in combination, for detecting LNM in cervical cancer. METHODS In this prospective study, we enrolled consecutive cervical cancer patients who received multimodal DWI (conventional DWI, intravoxel incoherent motion DWI, and diffusion kurtosis imaging) before treatment from June 2022 to June 2023. The largest lymph node (LN) observed on each side on imaging was matched with that detected on pathology to improve the accuracy of LN matching. Comparison of the diffusion and morphological parameters of LNs and the primary tumor between the positive and negative LN groups. A combined diagnostic model was constructed using multivariate logistic regression, and the diagnostic performance was evaluated using receiver operating characteristic curves. RESULTS A total of 93 cervical cancer patients were enrolled: 35 with LNM (48 positive LNs were collected), and 58 without LNM (116 negative LNs were collected). The area under the curve (AUC) values for the apparent diffusion coefficient, diffusion coefficient, mean diffusivity, mean kurtosis, long-axis diameter, short-axis diameter of LNs, and the largest primary tumor diameter were 0.716, 0.720, 0.716, 0.723, 0.726, 0.798, and 0.744, respectively. Independent risk factors included the diffusion coefficient, mean kurtosis, short-axis diameter of LNs, and the largest primary tumor diameter. The AUC value of the combined model based on the independent risk factors was 0.920, superior to the AUC values of all the parameters mentioned above. CONCLUSION Combining multimodal DWI and morphological parameters improved the diagnostic efficacy for detecting cervical cancer LNM than using either alone.
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Affiliation(s)
- Suixing Zhong
- Department of Radiology, Yunnan Cancer Hospital, Third Affiliated Hospital of Kunming Medical University, No. 519, Kunzhou Road, Xishan District, Kunming, 650118, China
| | - Conghui Ai
- Department of Radiology, Yunnan Cancer Hospital, Third Affiliated Hospital of Kunming Medical University, No. 519, Kunzhou Road, Xishan District, Kunming, 650118, China
| | - Yingying Ding
- Department of Radiology, Yunnan Cancer Hospital, Third Affiliated Hospital of Kunming Medical University, No. 519, Kunzhou Road, Xishan District, Kunming, 650118, China
| | - Jing Tan
- Department of Radiology, Yunnan Cancer Hospital, Third Affiliated Hospital of Kunming Medical University, No. 519, Kunzhou Road, Xishan District, Kunming, 650118, China
| | - Yan Jin
- Department of Radiology, Yunnan Cancer Hospital, Third Affiliated Hospital of Kunming Medical University, No. 519, Kunzhou Road, Xishan District, Kunming, 650118, China
| | - Hongbo Wang
- Department of Radiology, Yunnan Cancer Hospital, Third Affiliated Hospital of Kunming Medical University, No. 519, Kunzhou Road, Xishan District, Kunming, 650118, China
| | - Huimei Zhang
- Department of Radiology, Yunnan Cancer Hospital, Third Affiliated Hospital of Kunming Medical University, No. 519, Kunzhou Road, Xishan District, Kunming, 650118, China
| | - Miaomiao Li
- Department of Radiology, Yunnan Cancer Hospital, Third Affiliated Hospital of Kunming Medical University, No. 519, Kunzhou Road, Xishan District, Kunming, 650118, China
| | - Rong Zhu
- Department of Radiology, Yunnan Cancer Hospital, Third Affiliated Hospital of Kunming Medical University, No. 519, Kunzhou Road, Xishan District, Kunming, 650118, China
| | - Shangwei Gu
- Department of Radiology, Yunnan Cancer Hospital, Third Affiliated Hospital of Kunming Medical University, No. 519, Kunzhou Road, Xishan District, Kunming, 650118, China
| | - Ya Zhang
- Department of Radiology, Yunnan Cancer Hospital, Third Affiliated Hospital of Kunming Medical University, No. 519, Kunzhou Road, Xishan District, Kunming, 650118, China.
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Liu X, Meng N, Zhou Y, Fu F, Yuan J, Wang Z, Yang Y, Xiong Z, Zou C, Wang M. Tri-Compartmental Restriction Spectrum Imaging Based on 18F-FDG PET/MR for Identification of Primary Benign and Malignant Lung Lesions. J Magn Reson Imaging 2024. [PMID: 38886922 DOI: 10.1002/jmri.29438] [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: 01/30/2024] [Revised: 04/25/2024] [Accepted: 04/25/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Restriction spectrum imaging (RSI), as an advanced quantitative diffusion-weighted magnetic resonance imaging technique, has the potential to distinguish primary benign and malignant lung lesions. OBJECTIVE To explore how well the tri-compartmental RSI performs in distinguishing primary benign from malignant lung lesions compared with diffusion-weighted imaging (DWI), and to further explore whether positron emission tomography/magnetic resonance imaging (PET/MRI) can improve diagnostic efficacy. STUDY TYPE Prospective. POPULATION 137 patients, including 108 malignant and 29 benign lesions (85 males, 52 females; average age = 60.0 ± 10.0 years). FIELD STRENGTH/SEQUENCE T2WI, T1WI, multi-b value DWI, MR-based attenuation correction, and PET imaging on a 3.0 T whole-body PET/MR system. ASSESSMENT The apparent diffusion coefficient (ADC), RSI-derived parameters (restricted diffusionf 1 $$ {f}_1 $$ , hindered diffusionf 2 $$ {f}_2 $$ , and free diffusionf 3 $$ {f}_3 $$ ) and the maximum standardized uptake value (SUVmax) were calculated and analyzed for diagnostic efficacy individually or in combination. STATISTICAL TESTS Student's t-test, Mann-Whitney U test, receiver operating characteristic (ROC) curves, Delong test, Spearman's correlation analysis. P < 0.05 was considered statistically significant. RESULTS Thef 1 $$ {f}_1 $$ , SUVmax were significantly higher, andf 3 $$ {f}_3 $$ , ADC were significantly lower in the malignant group [0.717 ± 0.131, 9.125 (5.753, 13.058), 0.194 ± 0.099, 1.240 (0.972, 1.407)] compared to the benign group [0.504 ± 0.236, 3.390 (1.673, 6.030), 0.398 ± 0.195, 1.485 ± 0.382]. The area under the ROC curve (AUC) values ranked from highest to lowest as follows: AUC (SUVmax) > AUC (f 3 $$ {f}_3 $$ ) > AUC (f 1 $$ {f}_1 $$ ) > AUC (ADC) > AUC (f 2 $$ {f}_2 $$ ) (AUC = 0.819, 0.811, 0.770, 0.745, 0549). The AUC (AUC = 0.900) of the combined model of RSI with PET was significantly higher than that of either single-modality imaging. CONCLUSION RSI-derived parameters (f 1 $$ {f}_1 $$ ,f 3 $$ {f}_3 $$ ) might help to distinguish primary benign and malignant lung lesions and the discriminatory utility off 2 $$ {f}_2 $$ was not observed. The RSI exhibits comparable or potentially enhanced performance compared with DWI, and the combined RSI and PET model might improve diagnostic efficacy. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY Stage 2.
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Affiliation(s)
- Xue Liu
- Department of Medical Imaging, Zhengzhou University People's Hospital, Zhengzhou, China
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China
| | - Nan Meng
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China
| | - Yihang Zhou
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China
- Department of Medical Imaging, Xinxiang Medical University Henan Provincial People's Hospital, Zhengzhou, China
| | - Fangfang Fu
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China
| | - Jianmin Yuan
- Central Research Institute, United Imaging Healthcare Group, Shanghai, China
| | - Zhe Wang
- Central Research Institute, United Imaging Healthcare Group, Shanghai, China
| | - Yang Yang
- Beijing United Imaging Research Institute of Intelligent Imaging, United Imaging Healthcare Group, Beijing, China
| | - Zhongyan Xiong
- Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Chao Zou
- Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Meiyun Wang
- Department of Medical Imaging, Zhengzhou University People's Hospital, Zhengzhou, China
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China
- Laboratory of Brain Science and Brain-Like Intelligence Technology, Biomedical Research Institute, Henan Academy of Sciences, Zhengzhou, China
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Parisi S, Sciacca M, Ferrantelli G, Chillari F, Critelli P, Venuti V, Lillo S, Arcieri M, Martinelli C, Pontoriero A, Minutoli F, Ercoli A, Pergolizzi S. Locally advanced squamous cervical carcinoma (M0): management and emerging therapeutic options in the precision radiotherapy era. Jpn J Radiol 2024; 42:354-366. [PMID: 37987880 DOI: 10.1007/s11604-023-01510-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 10/26/2023] [Indexed: 11/22/2023]
Abstract
Squamous cervical carcinoma (SCC) requires particular attention in diagnostic and clinical management. New diagnostic tools, such as (positron emission tomography-magnetic resonance imaging) PET-MRI, consent to ameliorate clinical staging accuracy. The availability of new technologies in radiation therapy permits to deliver higher dose lowering toxicities. In this clinical scenario, new surgical concepts could aid in general management. Lastly, new targeted therapies and immunotherapy will have more room in this setting. The aim of this narrative review is to focus both on clinical management and new therapies in the precision radiotherapy era.
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Affiliation(s)
- S Parisi
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
| | - M Sciacca
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
| | - G Ferrantelli
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy.
| | - F Chillari
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
| | - P Critelli
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
| | - V Venuti
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
| | - S Lillo
- Radiation Oncology Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - M Arcieri
- Obstetrics and Gynecology Unit, Department of Human Pathology of Adult and Childhood ``G. Baresi'', University Hospital ``G. Martino'', Messina, Italy
| | - C Martinelli
- Obstetrics and Gynecology Unit, Department of Human Pathology of Adult and Childhood ``G. Baresi'', University Hospital ``G. Martino'', Messina, Italy
| | - A Pontoriero
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
| | - F Minutoli
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
| | - A Ercoli
- Obstetrics and Gynecology Unit, Department of Human Pathology of Adult and Childhood ``G. Baresi'', University Hospital ``G. Martino'', Messina, Italy
| | - S Pergolizzi
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
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Wang T, Li YY, Ma NN, Wang PA, Zhang B. A MRI radiomics-based model for prediction of pelvic lymph node metastasis in cervical cancer. World J Surg Oncol 2024; 22:55. [PMID: 38365759 PMCID: PMC10873981 DOI: 10.1186/s12957-024-03333-5] [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: 10/12/2023] [Accepted: 02/06/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Cervical cancer (CC) is a common malignancy of the female reproductive tract, and preoperative prediction of lymph node metastasis (LNM) is essential. This study aims to design and validate a magnetic resonance imaging (MRI) radiomics-based predictive model capable of detecting LNM in patients diagnosed with CC. METHODS This retrospective analysis incorporated 86 and 38 CC patients into the training and testing groups, respectively. Radiomics features were extracted from MRI T2WI, T2WI-SPAIR, and axial apparent diffusion coefficient (ADC) sequences. Selected features identified in the training group were then used to construct a radiomics scoring model, with relevant LNM-related risk factors having been identified through univariate and multivariate logistic regression analyses. The resultant predictive model was then validated in the testing cohort. RESULTS In total, 16 features were selected for the construction of a radiomics scoring model. LNM-related risk factors included worse differentiation (P < 0.001), more advanced International Federation of Gynecology and Obstetrics (FIGO) stages (P = 0.03), and a higher radiomics score from the combined MRI sequences (P = 0.01). The equation for the predictive model was as follows: -0.0493-2.1410 × differentiation level + 7.7203 × radiomics score of combined sequences + 1.6752 × FIGO stage. The respective area under the curve (AUC) values for the T2WI radiomics score, T2WI-SPAIR radiomics score, ADC radiomics score, combined sequence radiomics score, and predictive model were 0.656, 0.664, 0.658, 0.835, and 0.923 in the training cohort, while these corresponding AUC values were 0.643, 0.525, 0.513, 0.826, and 0.82 in the testing cohort. CONCLUSIONS This MRI radiomics-based model exhibited favorable accuracy when used to predict LNM in patients with CC. Relative to the use of any individual MRI sequence-based radiomics score, this predictive model yielded superior diagnostic accuracy.
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Affiliation(s)
- Tao Wang
- Suzhou Medical College of Soochow University, Suzhou, China
- Department of Radiology, Xuzhou Central Hospital, Xuzhou, China
| | - Yan-Yu Li
- Department of Gynaecology and Obstetrics, Xuzhou Central Hospital, Xuzhou, China
| | - Nan-Nan Ma
- Department of Radiology, Xuzhou Central Hospital, Xuzhou, China
| | - Pei-An Wang
- Hospital Administration Office, Xuzhou Central Hospital, Xuzhou, China.
| | - Bei Zhang
- Suzhou Medical College of Soochow University, Suzhou, China.
- Department of Gynaecology and Obstetrics, Xuzhou Central Hospital, Xuzhou, China.
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Liu Y, Hua J, Liu L, Zhang W, Xu S, Chen X. The value of the SUV ratio between lymph node and bone marrow in predicting pelvic lymphatic metastasis of patients with locally advanced cervical cancer: an integrated PET/CT study. Nucl Med Commun 2022; 43:1155-1160. [PMID: 36003034 PMCID: PMC9575580 DOI: 10.1097/mnm.0000000000001613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 08/16/2022] [Indexed: 02/04/2023]
Abstract
PURPOSE This study aimed to evaluate the value of the standardized uptake value (SUV) ratio between lymph nodes and bone marrow (BM) measured by Fluorine-18-fluorodeoxyglucose PET and computed tomography ( 18 F-FDG PET/CT) for predicting pelvic lymph node (PLN) metastasis in patients with locally advanced cervical cancer (LACC). MATERIALS AND METHODS A total of 62 patients with pathological stage Ib-IVa cervical cancer who underwent 18 F-FDG PET/CT before treatment were reviewed retrospectively. We measured the metabolic and morphological parameters of lymph nodes and primary tumors, bone marrow SUV (SUVBM) and calculated the ratio of lymph nodes maximum SUV (SUVmax) to bone marrow SUV (SUVLN/BM) and the ratio of short-axis diameter to long-axis diameter (Ds/l) of lymph nodes. A receiver operating characteristic (ROC) curve was performed to evaluate the diagnostic efficacy of each parameter. RESULTS There were 180 lymph nodes with pathological evidence included in the study. Our results indicated that Ds/l, SUVmax of lymph nodes (SUVLN) and SUVLN/BM were independent risk factors for PLN metastasis in LACC ( P < 0.05), and SUVLN/BM showed the best diagnostic performance by ROC curve analysis. The SUVBM in the anemia group was significantly higher than that in the nonanemia group (3.05 vs. 2.40, P < 0.05); furthermore, false-positive cases decreased when the SUVLN/BM was used as the diagnostic criterion instead of SUVLN, especially in the anemia group. ROC curve analysis showed that the area under the curve value of the combination of SUVLN/BM and Ds/l was 0.884 ( P < 0.05), which was higher than Ds/l or SUVLN/BM alone. CONCLUSIONS SUVLN/BM could improve the ability to predicting PLN metastasis in patients with LACC, and the diagnostic efficacy of the combination of SUVLN/BM and Ds/l might be better than that of a single parameter.
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Affiliation(s)
- Ying Liu
- Department of Nuclear Medicine, Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, People’s Republic of China
| | - Jun Hua
- Department of Nuclear Medicine, Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, People’s Republic of China
| | - Lisheng Liu
- Department of Nuclear Medicine, Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, People’s Republic of China
| | - Wei Zhang
- Department of Nuclear Medicine, Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, People’s Republic of China
| | - Shufan Xu
- Department of Nuclear Medicine, Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, People’s Republic of China
| | - Xiaoliang Chen
- Department of Nuclear Medicine, Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, People’s Republic of China
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Ren J, Li Y, Liu XY, Zhao J, He YL, Jin ZY, Xue HD. Diagnostic performance of ADC values and MRI-based radiomics analysis for detecting lymph node metastasis in patients with cervical cancer: A systematic review and meta-analysis. Eur J Radiol 2022; 156:110504. [PMID: 36108474 DOI: 10.1016/j.ejrad.2022.110504] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 08/16/2022] [Accepted: 08/25/2022] [Indexed: 11/21/2022]
Abstract
OBJECTIVE To evaluate and compare the diagnostic performance of apparent diffusion coefficient (ADC) values and MRI-based radiomics analysis for lymph node metastasis (LNM) detection in patients with cervical cancer (CC). METHODS We searched relevant databases for studies on ADC values and MRI-based radiomics analysis for LNM detection in CC between January 2001 and December 2021. Methodological quality assessment of risk of bias using Quality Assessment of Diagnostic Accuracy Studies 2 and radiomics quality score (RQS) of the studies was conducted. The pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), diagnostic odds ratio (DOR), and area under the curve (AUC) were calculated. Diagnostic performance was compared between the two quantitative analyses using a two-sample Z-test. RESULTS In total, 22 studies including 2314 patients were included. Unclear risk of bias was observed in 4.5-36.4% of the studies. The 8 radiomics studies exhibited a median (interquartile range) RQS of 13.5 (5.5-15.75). The pooled sensitivity, specificity, LR+, LR-, DOR, and AUC of the ADC values vs radiomics analysis were 0.86 vs 0.84, 0.85 vs 0.73, 5.7 vs 3.1, 0.17 vs 0.22, 34 vs 14, and 0.91 vs 0.86, respectively. There was no threshold effect or publication bias, but significant heterogeneity existed among the studies. No significant difference was detected in the diagnostic performance of the two quantitative analyses using the Z-test. CONCLUSION ADC values are more clinically promising because they are more easily accessible and widely applied, and exhibit a non-statistically significant trend to outperform radiomics analysis.
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Affiliation(s)
- Jing Ren
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, PR China.
| | - Yuan Li
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, PR China.
| | - Xin-Yu Liu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, PR China.
| | - Jia Zhao
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, PR China.
| | - Yong-Lan He
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, PR China.
| | - Zheng-Yu Jin
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, PR China.
| | - Hua-Dan Xue
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, PR China.
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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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Dolciami M, Capuani S, Celli V, Maiuro A, Pernazza A, Palaia I, Di Donato V, Santangelo G, Rizzo SMR, Ricci P, Della Rocca C, Catalano C, Manganaro L. Intravoxel Incoherent Motion (IVIM) MR Quantification in Locally Advanced Cervical Cancer (LACC): Preliminary Study on Assessment of Tumor Aggressiveness and Response to Neoadjuvant Chemotherapy. J Pers Med 2022; 12:jpm12040638. [PMID: 35455755 PMCID: PMC9027075 DOI: 10.3390/jpm12040638] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 04/05/2022] [Accepted: 04/11/2022] [Indexed: 01/27/2023] Open
Abstract
The aim of this study was to determine whether quantitative parameters obtained from intravoxel incoherent motion (IVIM) model at baseline magnetic resonance imaging (MRI) correlate with histological parameters and response to neoadjuvant chemotherapy in patients with locally advanced cervical cancer (LACC). Methods: Twenty patients with biopsy-proven cervical cancer, staged as LACC on baseline MRI and addressed for neoadjuvant chemotherapy were enrolled. At treatment completion, tumor response was assessed with a follow-up MRI evaluated using the revised response evaluation criteria in solid tumors (RECIST; version 1.1), and patients were considered good responders (GR) if they had complete response or partial remission, and poor responders/non-responders (PR/NR) if they had stable or progressive disease. MRI protocol included conventional diffusion-weighted imaging (DWI; b = 0 and 1000 s/mm2) and IVIM acquisition using eight b-values (range: 0–1500 s/mm2). MR-images were analyzed using a dedicated software to obtain quantitative parameters: diffusion (D), pseudo-diffusion (D*), and perfusion fraction (fp) from the IVIM model; apparent diffusion coefficient (ADC) from conventional DWI. Histologic subtype, grading, and tumor-infiltrating lymphocytes (TILs) were assessed in each LACC. Results: D showed significantly higher values in GR patients (p = 0.001) and in moderate/high TILs (p = 0.018). Fp showed significantly higher values in squamous cell tumors (p = 0.006). Conclusions: D extracted from the IVIM model could represent a promising tool to identify tumor aggressiveness and predict response to therapy.
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Affiliation(s)
- Miriam Dolciami
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (M.D.); (V.C.); (A.P.); (P.R.); (C.D.R.); (C.C.)
| | - Silvia Capuani
- CNR Institute for Complex Systems (ISC), Physics Department, Sapienza University of Rome, 00161 Rome, Italy;
| | - Veronica Celli
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (M.D.); (V.C.); (A.P.); (P.R.); (C.D.R.); (C.C.)
| | | | - Angelina Pernazza
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (M.D.); (V.C.); (A.P.); (P.R.); (C.D.R.); (C.C.)
| | - Innocenza Palaia
- Department of Maternal and Child Health and Urological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (I.P.); (V.D.D.); (G.S.)
| | - Violante Di Donato
- Department of Maternal and Child Health and Urological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (I.P.); (V.D.D.); (G.S.)
| | - Giusi Santangelo
- Department of Maternal and Child Health and Urological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (I.P.); (V.D.D.); (G.S.)
| | - Stefania Maria Rita Rizzo
- Istituto di Imaging della Svizzera Italiana (IIMSI), Ente Ospedaliero Cantonale (EOC), 6900 Lugano, Switzerland;
- Facoltà di Scienze Biomediche, Università della Svizzera Italiana, 6900 Lugano, Switzerland
| | - Paolo Ricci
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (M.D.); (V.C.); (A.P.); (P.R.); (C.D.R.); (C.C.)
- Unit of Emergency Radiology, Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy
| | - Carlo Della Rocca
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (M.D.); (V.C.); (A.P.); (P.R.); (C.D.R.); (C.C.)
| | - Carlo Catalano
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (M.D.); (V.C.); (A.P.); (P.R.); (C.D.R.); (C.C.)
| | - Lucia Manganaro
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy; (M.D.); (V.C.); (A.P.); (P.R.); (C.D.R.); (C.C.)
- Correspondence: ; Tel.: +39-3338151295
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Fang T, Meng N, Feng P, Huang Z, Li Z, Fu F, Yuan J, Yang Y, Liu H, Roberts N, Wang M. A Comparative Study of Amide Proton Transfer Weighted Imaging and Intravoxel Incoherent Motion MRI Techniques Versus (18) F-FDG PET to Distinguish Solitary Pulmonary Lesions and Their Subtypes. J Magn Reson Imaging 2021; 55:1376-1390. [PMID: 34723413 DOI: 10.1002/jmri.27977] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 10/15/2021] [Accepted: 10/19/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Amide proton transfer weighted imaging (APTw), intravoxel incoherent motion (IVIM), and positron emission tomography (PET) imaging all have the potential to characterize solitary pulmonary lesions (SPLs). PURPOSE To compare APTw and IVIM with PET imaging for distinguishing between benign and malignant SPLs and their subtypes. STUDY TYPE Prospective. POPULATION Ninety-five patients, 78 with malignant SPLs (including 48 with adenocarcinoma [AC] and 17 with squamous cell carcinoma [SCC]), and 17 with benign SPLs. FIELD STRENGTH/SEQUENCE Fast spin-echo (FSE) T2WI, FSE APTw and echo-planar imaging IVIM, MR-base attenuation correction (MRAC), and PET imaging on a 3-T whole-body PET/MR system. ASSESSMENT The magnetization transfer ratio asymmetry (MTRasym) at 3.5 ppm, diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), and the maximum standardized uptake value (SUVmax) were analyzed. STATISTICAL TESTS Individual sample t-test, Delong test, Pearson's correlation analysis, and area under the receiver operating characteristic curve (AUC). P < 0.05 indicated statistical significance. RESULTS The MTRasym and SUVmax were significantly higher, and D was significantly lower in the malignant group (3.3 ± 2.6 [%], 7.8 ± 5, and 1.2 ± 0.3 [×10-3 mm2 /second]) compared to the benign group (-0.3 ± 1.6 [%], 3.1 ± 3.8, and 1.6 ± 0.3 [×10-3 mm2 /second]). The MTRasym and D were significantly lower, and SUVmax was significantly higher in the SCC group (0.8 ± 1.0 [%], 1.0 ± 0.2 [×10-3 mm2 /second] than in the AC group (4.1 ± 2.6 [%], 1.3 ± 0.3 [×10-3 mm2 /second], 6.7 ± 4.6). Besides, the combination (AUC = 0.964) of these three methods showed higher diagnostic efficacy than any individual method (AUC = 0.917, 0.851, 0.82, respectively) in identifying malignant and benign SPLs. However, APTw showed better diagnostic efficacy than the combination of three methods or PET imaging alone in distinguishing SCC and AC groups (AUC = 0.934, 0.781, 0.725, respectively). DATA CONCLUSION APTw, IVIM, and PET imaging are all effective methods to distinguish benign and malignant SPLs and their subtypes. APTw is potentially more capable than PET imaging of distinguishing lung SCC from AC. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Ting Fang
- Department of Medical Imaging, Zhengzhou University People's Hospital, Zhengzhou, China.,Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Nan Meng
- Department of Medical Imaging, Zhengzhou University People's Hospital, Zhengzhou, China.,Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Pengyang Feng
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China.,Department of Medical Imaging, Henan University People's Hospital, Zhengzhou, China
| | - Zhun Huang
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China.,Department of Medical Imaging, Henan University People's Hospital, Zhengzhou, China
| | - Ziqiang Li
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China.,Department of Medical Imaging, Xinxiang Medical University, Xinxiang, China
| | - Fangfang Fu
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Jianmin Yuan
- Central Research Institute, UIH Group, Shanghai, China
| | - Yang Yang
- Beijing United Imaging Research Institute of Intelligent Imaging, UIH Group, Beijing, China
| | - Hui Liu
- UIH America, Inc, Houston, Texas, USA
| | - Neil Roberts
- Clinical Research Imaging Centre, School of Clinical Sciences and Community Health, College of Medicine and Veterinary Medicine, The University of Edinburgh, Edinburgh, UK
| | - Meiyun Wang
- Department of Medical Imaging, Zhengzhou University People's Hospital, Zhengzhou, China.,Department of Medical Imaging, Henan University People's Hospital, Zhengzhou, China.,Department of Medical Imaging, Xinxiang Medical University, Xinxiang, China
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11
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Xu C, Ma T, Sun H, Li X, Gao S. Markers of Prognosis for Early Stage Cervical Cancer Patients (Stage IB1, IB2) Undergoing Surgical Treatment. Front Oncol 2021; 11:659313. [PMID: 34150626 PMCID: PMC8206539 DOI: 10.3389/fonc.2021.659313] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 05/17/2021] [Indexed: 12/28/2022] Open
Abstract
Background For individuals with cervical cancer, large tumor volume, lymph node metastasis, distant metastasis, and parauterine infiltration are usually associated with a poor prognosis. Individuals with stage 1B1 and 1B2 cervical cancer usually do not have these unfavorable prognostic factors. Once the disease progresses, the prognosis becomes extremely poor. Therefore, investigating the prognostic markers of these cervical cancer patients is necessary for treatment. Methods This retrospective study included 95 cervical cancer patients treated with surgery. The patients were divided into progressor and non-progressor groups according to postoperative follow-up results. T-test (or Mann−Whitney U test), chi-squared test (or Fisher’s exact test) and receiver operating characteristic (ROC) curves were used to evaluate imaging, hematology, and clinicopathological index differences between the two groups. Cox analysis was performed to select the independent markers of progression-free survival (PFS) when developing the nomogram. Validation of the nomogram was performed with 1000 bootstrapped samples. The performance of the nomogram was validated with ROC curves, generated calibration curves, and Kaplan-Meier and decision curve analysis (DCA). Results Cervical stromal invasion depth, lymphovascular space invasion (LVSI), human papilloma virus (HPV-16), Glut1, D-dimer, SUVmax and SUVpeak showed significant differences between the two groups. Multivariate Cox proportional hazard model showed SUVpeak (p = 0.012), and HPV-16 (p = 0.007) were independent risk factors and were used to develop the nomogram for predicting PFS. The ROC curves, Kaplan-Meier method, calibration curves and DCA indicated satisfactory accuracy, agreement, and clinical usefulness, respectively. Conclusions SUVpeak level (≥7.63 g/cm3) and HPV-16 negative status before surgery were associated with worse PFS for patients with cervical cancer. Based on this result, we constructed the nomogram and showed satisfactory performance. Clinically, individualized clinical decision-making can be performed on patients based on this result.
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Affiliation(s)
- Chen Xu
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China.,Liaoning Provincial Key Laboratory of Medical Imaging, Shengjing Hospital of China Medical University, Shenyang, China
| | - Tie Ma
- Department of Pathology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Hongzan Sun
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China.,Liaoning Provincial Key Laboratory of Medical Imaging, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xiaohan Li
- Department of Pathology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Song Gao
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
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12
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Value of integrated PET-IVIM MRI in predicting lymphovascular space invasion in cervical cancer without lymphatic metastasis. Eur J Nucl Med Mol Imaging 2021; 48:2990-3000. [PMID: 33506309 DOI: 10.1007/s00259-021-05208-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 01/17/2021] [Indexed: 12/14/2022]
Abstract
PURPOSE To evaluate the contributory value of positron emission tomography (PET)-intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) in the prediction of lymphovascular space invasion (LVSI) in patients with cervical cancer without lymphatic metastasis. MATERIALS AND METHODS A total of 90 patients with cervical cancer without signs of lymph node metastasis on PET/MRI were enrolled in this study. The tumours were classified into LVSI-positive (n = 25) and LVSI-negative (n = 65) groups according to postoperative pathology. The PET-derived parameters (SUVmax, SUVmean, metabolic tumour volume (MTV) and total lesion glycolysis (TLG)) and IVIM-derived parameters (ADCmean, ADCmin, Dmean, Dmin, f, D* and gross tumour volume (GTV)) between the two groups were evaluated using a Student's t test (Mann-Whitney U test for variables with a nonnormal distribution) and receiver operating characteristic (ROC) curves. The optimal combination of PET/MR parameters for predicting LVSI was investigated using univariate and multivariate logistic regression models and evaluated by ROC curves. The optimal cutoff threshold values corresponded to the maximal values of the Youden index. A control model was established using 1000 bootstrapped samples, for which the performance was validated using calibration curves and ROC curves. RESULTS PET-derived parameters (SUVmax, SUVmean, MTV, TLG) and IVIM MRI-derived parameters (Dmin, ADCmin, GTV) were significantly different between patients with and without LVSI (P < 0.05). Logistic analyses showed that a combination of TLG and Dmin had the strongest predictive value for LVSI diagnosis (area under the curve (AUC), 0.861; sensitivity, 80.00; specificity, 86.15; P < 0.001). The optimal cutoff threshold values for Dmin and TLG were 0.58 × 10-3 mm2/s and 66.68 g/cm3, respectively. The verification model showed the combination of TLG and Dmin had the strongest predictive value, and its ROC curve and calibration curve showed good accuracy (AUC, 0.878) and consistency. CONCLUSIONS The combination of TLG and Dmin may be the best indicator for predicting LVSI in cervical cancer without lymphatic metastasis.
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