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Lin Y, Huang H, Xiao Z, Shi S, Weng Q, Tu Z. The value of multiparametric functional MRI histogram features in assessing multiple myeloma activity. Eur Radiol 2025:10.1007/s00330-025-11507-2. [PMID: 40100399 DOI: 10.1007/s00330-025-11507-2] [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: 08/09/2024] [Revised: 01/13/2025] [Accepted: 02/10/2025] [Indexed: 03/20/2025]
Abstract
OBJECTIVE To investigate the application of histogram features of apparent diffusion coefficient (ADC), mean diffusion coefficient (MD), mean kurtosis (MK), and fat fraction (FF) for assessing multiple myeloma (MM) activity. MATERIALS AND METHODS From April 2023 to December 2023, 24 multiple myeloma patients who underwent zonally oblique multi-slice diffusion-weighted imaging (ZOOM-DWI), zonally oblique multi-slice diffusion kurtosis imaging (ZOOM-DKI), and modified Dixon quantification imaging (mDixon-Quant) were enrolled in this retrospective study. Histogram features of ADC, MD, MK, and FF were analyzed. Significant variables were selected for multivariate logistic regression analysis using a backward stepwise selection method. The diagnostic efficacies of individual histogram features and combined models were evaluated by the receiver operating characteristic curve (ROC) and the area under the curve (AUC). RESULTS A total of 24 participants were enrolled in this study, 12 males and 12 females, with an age range of 39-73 (57.88 ± 8.55) years. The ADC and MD histogram features did not correlate with the disease status in multiple myeloma, whereas the MK and FF histogram features were significantly associated with the disease status (p < 0.05). MK_InterquartileRange and FF_Median had the highest AUC values in multiple myeloma activity assessment. The differences in diagnostic efficacies between MK_InterquartileRange and FF_Median, MK_InterquartileRange and the MK model, FF_Median and the FF model, the MK model and the FF model were not statistically different (p = 0.70, 0.54, 0.09 and 0.09, respectively). CONCLUSION Histogram features of MK and FF are valuable in assessing disease activity in multiple myeloma patients. KEY POINTS Question Accurate assessment of the disease status of multiple myeloma is crucial for enhancing individualized treatment, yet current non-invasive tools remain inadequate. Findings Mean kurtosis (MK) and fat fraction (FF) histogram features are associated with disease activity of multiple myeloma, providing rich and accurate parameters for assessing the disease status. Clinical relevance The MK and FF histogram features facilitate non-invasive assessment of multiple myeloma activity, potentially guiding the development of personalized treatment strategies.
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Affiliation(s)
- Ying Lin
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
- Department of Radiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Hongjie Huang
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
- Department of Radiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Zebin Xiao
- Department of Biomedical Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Zhongda Hospital, Southeast University, Nanjing, China
| | - Shufang Shi
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
- Department of Radiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Qiang Weng
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
- Department of Radiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Zhanhai Tu
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
- Department of Radiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
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Gao Y, Wang Q, Zhang L, Li S, Liu D, Wang S, Zhu J, Zhang H, Xie S, Xia S, Huang W, Xue H, Li J. Treatment Response Assessment in Multiple Myeloma: Histogram Analysis of Total Tumor Apparent Diffusion Coefficient based on Whole-body Diffusion-weighted MR Imaging. J Magn Reson Imaging 2024; 60:1051-1060. [PMID: 38088500 DOI: 10.1002/jmri.29155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 11/14/2023] [Accepted: 11/15/2023] [Indexed: 08/02/2024] Open
Abstract
BACKGROUND The International Myeloma Working Group (IMWG) consensus criteria for response assessment in multiple myeloma (MM) has methodological limitations. Whole-body diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) histogram analysis may be complementary to response assessment of MM. PURPOSE To explore the role of histogram analysis of the ADC based on the total tumor volume (ttADC) in response assessment in patients with newly diagnosed MM (NDMM). STUDY TYPE Retrospective. POPULATION Thirty-six patients with NDMM. FIELD STRENGTH/SEQUENCE 3.0T/single-shot DWI echo planar imaging (EPI) sequence with an integrated slice-by-slice shimming (iShim) technique. ASSESSMENT Baseline (median: 1 day before treatment) and post-treatment (median: five cycles of therapy) whole-body DWI were analyzed. A region of interest (ROI) containing lesions on every section of baseline image was drawn to derive the per-patient total tumor data. Post-treatment image analysis was based on the same ROI as the corresponding baseline. Histogram metrics were extracted from both ROIs. Patients were categorized into the very good partial response or better (VGPR+) group and the less than VGPR group per the IMWG response criteria for response assessment. Progression-free survival (PFS) was also calculated. STATISTICAL TESTS Mann-Whitney test and Fisher's exact or Chi-squared tests, Receiver operating characteristic (ROC) analysis and DeLong test, Kaplan-Meier analysis and Cox proportional hazards model. A two-tailed P-value <0.05 was considered statistically significant. RESULTS Thirty patients were categorized into the VGPR+ group and six into the less than VGPR group. The ttADC histogram changes between post-treatment and baseline metrics (ΔttADC) revealed significant differences in all percentile values between the VGPR+ and less than VGPR groups. For distinguishing VGPR+, ΔttADC_5th percentile had the largest area under the curve (AUC) (0.950, 95% CI 0.821-0.995). Patients with lower ΔttADC_5th percentile values (cutoff point, 188.193) showed significantly longer PFS (HR = 34.911, 95% CI 6.392-190.677). DATA CONCLUSION ttADC histogram may facilitate response assessment in patients with NDMM. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY: Stage 4.
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Affiliation(s)
- Yuhan Gao
- Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Qin Wang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Lu Zhang
- Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Shuo Li
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Dong Liu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Shitian Wang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Jinxia Zhu
- MR Research Collaboration, Siemens Healthineers Ltd., Beijing, China
| | - Haibo Zhang
- Department of Radiology, China-Japan Friendship Hospital, Beijing, China
| | - Sheng Xie
- Department of Radiology, China-Japan Friendship Hospital, Beijing, China
| | - Shuang Xia
- Department of Radiology, Tianjin First Central Hospital, Nankai University, Tianjin, China
| | - Wenyang Huang
- Department of Lymphoma, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences, Tianjin, China
| | - Huadan Xue
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Jian Li
- Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
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Xiong X, Wang J, Hao Z, Fan X, Jiang N, Qian X, Hong R, Dai Y, Hu C. MRI-based bone marrow radiomics for predicting cytogenetic abnormalities in multiple myeloma. Clin Radiol 2024; 79:e491-e499. [PMID: 38238146 DOI: 10.1016/j.crad.2023.12.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 11/27/2023] [Accepted: 12/14/2023] [Indexed: 03/09/2024]
Abstract
AIM To develop a radiomics signature applied to magnetic resonance imaging (MRI)-images to predict cytogenetic abnormalities in multiple myeloma (MM). MATERIALS AND METHODS Patients with newly diagnosed MM were enrolled retrospectively from March 2019 to September 2022. They were categorised into the high-risk cytogenetics (HRC) group and standard-risk cytogenetics (SRC) group. The patients were allocated randomly at a ratio of 7:3 into training and validation cohorts. Volumes of interest (VOI) was drawn manually on fat suppression T2-weighted imaging (FS-T2WI) and copied to the same location of the T1-weighted imaging (T1WI) sequence. Radiomics features were extracted from two sequences and selected by reproducibility and redundant analysis. The least absolute shrinkage selection operation (LASSO) algorithm was applied to build the radiomics signatures. The performance of the radiomics signatures to distinguish HRC with SRC was evaluated by ROC curves. The area under the curve (AUC), specificity, and sensitivity were also calculated. RESULTS A total of 105 MM patients were enrolled in this study. The four and 11 most significant and relevant features were selected separately from T1WI and FS-T2WI sequences to build the radiomics signatures based on the training cohort. Compared to the T1WI sequence, the radiomics signature based on the FS-T2WI sequence achieved better performance with AUCs of 0.896 and 0.729 in the training and validation cohorts respectively. A sensitivity of 0.833, specificity of 0.667, and Youden index of 0.500 were achieved for the FS-T2WI radiomics signature in the validation cohort. CONCLUSIONS The radiomics signature based on MRI provides a non-invasive and convenient tool to predict cytogenetic abnormalities in MM patients.
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Affiliation(s)
- X Xiong
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China
| | - J Wang
- Department of Radiology, Northern Jiangsu People's Hospital, Yangzhou 225001, China
| | - Z Hao
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China
| | - X Fan
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China
| | - N Jiang
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China
| | - X Qian
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, 215163, China
| | - R Hong
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China
| | - Y Dai
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, 215163, China.
| | - C Hu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China.
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Xiong X, Ma Y, Dai Y, Hu C, Zhang Y. Apparent diffusion coefficient measurements of bone marrow infiltration patterns in multiple myeloma for the assessment of tumor burden - a feasibility study. Radiol Oncol 2023; 57:455-464. [PMID: 38038425 PMCID: PMC10690753 DOI: 10.2478/raon-2023-0048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 07/22/2023] [Indexed: 12/02/2023] Open
Abstract
BACKGROUND The purpose of our study was to explore and compare the tumor burden of different bone marrow infiltration patterns and evaluate the feasibility of apparent diffusion coefficient (ADC) value to identify patterns in multiple myeloma (MM). PATIENTS AND METHODS Ninety-three patients with newly diagnosed multiple myeloma and 23 controls had undergone routine magnetic resonance imaging (MRI) and diffusion-weighted MRI (DWI) from January 2019 to November 2020. Five bone marrow (BM) infiltration patterns were allocated according to routine MRI. The laboratory data and ADC values of patterns were analyzed and compared. ROC analysis was used to establish the best diagnostic ADC threshold value for identifying these patterns and distinguishing normal pattern from controls. Besides, the correlation between the ADC values of diffuse pattern and the plasma cells ratio was assessed. RESULTS The values of hemoglobin, beta-2 microglobulin (β2-MG), plasma cell, M protein, the percentages of stage, high-risk fluorescence in situ hybridization, and ADC values showed significant difference among patterns. ADCmean at a specific value (368.5×10-6 mm2/s) yielded a maximum specificity (95.5%) and sensitivity (92.0%) in diagnosing MM. A specific value (335.5×10-6mm2/s) yielded a maximum specificity (84.7%) and sensitivity (88.0%) in discriminating visually normal pattern in MM from controls. There was a moderate positive correlation between the plasma cells ratio and ADCs of diffuse infiltration patterns (r = 0.648, P < 0.001). CONCLUSIONS The bone marrow infiltration patterns in MM patients can indicate the tumor burden and ADC value has the ability to discriminate these patterns objectively.
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Affiliation(s)
- Xing Xiong
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Yuzhu Ma
- Department of Radiology, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, Jiangsu, China
| | - Yao Dai
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Chunhong Hu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Yu Zhang
- Department of Radiology, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, Jiangsu, China
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Xiong X, Zhu Q, Zhou Z, Qian X, Hong R, Dai Y, Hu C. Discriminating minimal residual disease status in multiple myeloma based on MRI: utility of radiomics and comparison of machine-learning methods. Clin Radiol 2023; 78:e839-e846. [PMID: 37586967 DOI: 10.1016/j.crad.2023.07.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 07/11/2023] [Accepted: 07/17/2023] [Indexed: 08/18/2023]
Abstract
AIM To explore the possibility of discriminating minimal residual disease (MRD) status in multiple myeloma (MM) based on magnetic resonance imaging (MRI) and identify optimal machine-learning methods to optimise the clinical treatment regimen. MATERIALS AND METHODS A total of 83 patients were analysed retrospectively. They were divided randomly into training and validation cohorts. The regions of interest were segmented and radiomics features were extracted and analysed on two sequences, including T1-weighted imaging (WI) and fat saturated (FS)-T2WI, and then radiomics models were built in the training cohort and evaluated in the validation cohort. Clinical characteristics were calculated to build a traditional model. A combined model was also built using the clinical characteristics and radiomics features. Classification accuracy was assessed using area under the curve (AUC) and F1 score. RESULTS In the training cohort, only the bone marrow (BM) infiltrate ratio (p=0.005) was retained after univariate and multivariable logistic regression analysis. In T1WI, the linear support vector machine (SVM) achieved the best performance compared to other classifiers, with AUCs of 0.811 and 0.708 and F1 scores of 0.792 and 0.696 in the training and validation cohorts, respectively. Similarly, in FS-T2WI sequence, linear SVM achieved the best performance with AUCs of 0.833 and 0.800 and F1 score of 0.833 and 0.800. The combined model constructed by the FS-T2WI-linear SVM and BM infiltrate ratio outperformed the traditional model (p=0.050 and 0.012, Delong test), but showed no significant difference compared with the radiomics model (p=0.798 and 0.855). CONCLUSION The linear SVM-based machine-learning method can offer a non-invasive tool for discriminating MRD status in MM.
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Affiliation(s)
- X Xiong
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China
| | - Q Zhu
- Department of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China
| | - Z Zhou
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, 215163, China
| | - X Qian
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, 215163, China; School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China
| | - R Hong
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China
| | - Y Dai
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, 215163, China
| | - C Hu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China.
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Keaveney S, Dragan A, Rata M, Blackledge M, Scurr E, Winfield JM, Shur J, Koh DM, Porta N, Candito A, King A, Rennie W, Gaba S, Suresh P, Malcolm P, Davis A, Nilak A, Shah A, Gandhi S, Albrizio M, Drury A, Pratt G, Cook G, Roberts S, Jenner M, Brown S, Kaiser M, Messiou C. Image quality in whole-body MRI using the MY-RADS protocol in a prospective multi-centre multiple myeloma study. Insights Imaging 2023; 14:170. [PMID: 37840055 PMCID: PMC10577121 DOI: 10.1186/s13244-023-01498-3] [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: 05/11/2023] [Accepted: 08/08/2023] [Indexed: 10/17/2023] Open
Abstract
BACKGROUND The Myeloma Response Assessment and Diagnosis System (MY-RADS) guidelines establish a standardised acquisition and analysis pipeline for whole-body MRI (WB-MRI) in patients with myeloma. This is the first study to assess image quality in a multi-centre prospective trial using MY-RADS. METHODS The cohort consisted of 121 examinations acquired across ten sites with a range of prior WB-MRI experience, three scanner manufacturers and two field strengths. Image quality was evaluated qualitatively by a radiologist and quantitatively using a semi-automated pipeline to quantify common artefacts and image quality issues. The intra- and inter-rater repeatability of qualitative and quantitative scoring was also assessed. RESULTS Qualitative radiological scoring found that the image quality was generally good, with 94% of examinations rated as good or excellent and only one examination rated as non-diagnostic. There was a significant correlation between radiological and quantitative scoring for most measures, and intra- and inter-rater repeatability were generally good. When the quality of an overall examination was low, this was often due to low quality diffusion-weighted imaging (DWI), where signal to noise ratio (SNR), anterior thoracic signal loss and brain geometric distortion were found as significant predictors of examination quality. CONCLUSIONS It is possible to successfully deliver a multi-centre WB-MRI study using the MY-RADS protocol involving scanners with a range of manufacturers, models and field strengths. Quantitative measures of image quality were developed and shown to be significantly correlated with radiological assessment. The SNR of DW images was identified as a significant factor affecting overall examination quality. TRIAL REGISTRATION ClinicalTrials.gov, NCT03188172 , Registered on 15 June 2017. CRITICAL RELEVANCE STATEMENT Good overall image quality, assessed both qualitatively and quantitatively, can be achieved in a multi-centre whole-body MRI study using the MY-RADS guidelines. KEY POINTS • A prospective multi-centre WB-MRI study using MY-RADS can be successfully delivered. • Quantitative image quality metrics were developed and correlated with radiological assessment. • SNR in DWI was identified as a significant predictor of quality, allowing for rapid quality adjustment.
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Affiliation(s)
- Sam Keaveney
- MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK.
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK.
| | - Alina Dragan
- MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK
| | - Mihaela Rata
- MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK
| | - Matthew Blackledge
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK
| | - Erica Scurr
- MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK
| | - Jessica M Winfield
- MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK
| | - Joshua Shur
- MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK
| | - Dow-Mu Koh
- MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK
| | - Nuria Porta
- Clinical Trials and Statistics Unit, The Institute of Cancer Research, London, UK
| | - Antonio Candito
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK
| | - Alexander King
- University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Winston Rennie
- University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Suchi Gaba
- University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, UK
| | - Priya Suresh
- University Hospitals Plymouth NHS Trust, Plymouth, UK
| | - Paul Malcolm
- Norfolk & Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Amy Davis
- Epsom & St. Helier University Hospitals NHS Trust, Epsom, UK
| | | | - Aarti Shah
- Hampshire Hospitals NHS Foundation Trust, Basingstoke, UK
| | | | - Mauro Albrizio
- Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Arnold Drury
- Royal Bournemouth and Christchurch Hospitals NHS Foundation Trust, Bournemouth, UK
| | - Guy Pratt
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Gordon Cook
- Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
- Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Sadie Roberts
- Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | - Matthew Jenner
- University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Sarah Brown
- Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK
| | - Martin Kaiser
- MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK
| | - Christina Messiou
- MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK
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Zhang B, Zhang L, Bian B, Lin F, Zhu Z, Wang J. Diagnostic value of WB-DWI versus 18F-FDG PET/CT for the detection of multiple myeloma. Indian J Cancer 2023; 60:303-309. [PMID: 37787189 DOI: 10.4103/ijc.ijc_1129_20] [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] [Indexed: 10/04/2023]
Abstract
Background Whole-body diffusion-weighted imaging (WB-DWI) is commonly used for the detection of multiple myeloma (MM). Comparative data on the efficiency of WB-DWI compared with F-18 fluoro-2-deoxy-d-glucose positron emission tomography-computed tomography (18F-FDG PET/CT) to detect MM is limited. Methods This was a retrospective, single-center study of 22 patients with MM enrolled from January 2018 to December 2019. All patients underwent WB-DWI and 18F-FDG PET/CT. Pathological and clinical manifestations, as well as radiologic follow-up, were used for diagnosis. The overall accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of both methods were compared. The apparent diffusion coefficient (ADC) values of MM lesions and false-positive lesions were estimated. Results A total of 214 MM bone lesions were evaluated. There was no significant difference in the accuracy of WB-DWI and PET/CT (86.92 versus 88.32%). Though WB-DWI had a higher sensitivity (99.26% versus84.56%) and PET-CT had a higher specificity (96.10% versus 64.56%), these differences were not statistically significant. There was a statistically significant difference in PPV (83.33% versus 96.64%) and NPV (98.08% versus 77.89%) of WB-DWI and PET/CT, respectively. The ADC value for MM lesions was significantly lower than that for false-positive lesions (P < 0.001). Receiver operating curve analysis showed that the AUC was 0.846, and when the cut-off value was 0.745 × 10-3 mm2/s, the sensitivity and specificity were 86.3 and 83.4%, respectively, which distinguished MM lesions from non-MM lesions. Conclusion WB-DWI and PET-CT scans have similar overall accuracy for detecting MM lesions. The higher PPV of PET-CT and NPV of WB-DWI make them complementary imaging modalities. The ADC value for MM lesions is significantly lower than that for false-positive lesions. An ADC cutoff value of 0.745 × 10-3 mm2/s results in sensitivity and specificity of 86.3 and 83.4%, respectively.
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Affiliation(s)
- Bei Zhang
- Department of Radiology, First Hospital of Jilin University, Changchun, China
| | - Li Zhang
- Department of Radiology, First Hospital of Jilin University, Changchun, China
| | - Bingyang Bian
- Department of Radiology, First Hospital of Jilin University, Changchun, China
| | - Fang Lin
- Department of Radiology, First Hospital of Jilin University, Changchun, China
| | - Zining Zhu
- Department of Radiology, First Hospital of Jilin University, Changchun, China
| | - Jiping Wang
- Department of Radiology, First Hospital of Jilin University, Changchun, China
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ElGendy K, Barwick TD, Auner HW, Chaidos A, Wallitt K, Sergot A, Rockall A. Repeatability and test-retest reproducibility of mean apparent diffusion coefficient measurements of focal and diffuse disease in relapsed multiple myeloma at 3T whole body diffusion-weighted MRI (WB-DW-MRI). Br J Radiol 2022; 95:20220418. [PMID: 35867890 PMCID: PMC9815750 DOI: 10.1259/bjr.20220418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
OBJECTIVE To assess the test-retest reproducibility and intra/interobserver agreement of apparent diffusion coefficient (ADC) measurements of myeloma lesions using whole body diffusion-weighted MRI (WB-DW-MRI) at 3T MRI. METHODS Following ethical approval, 11 consenting patients with relapsed multiple myeloma were prospectively recruited and underwent baseline WB-DW-MRI. For a single bed position, axial DWI was repeated after a short interval to permit test-retest measurements.Mean ADC measurement was performed by two experienced observers. Intra- and interobserver agreement and test-retest reproducibility were assessed, using coefficient of variation (CV) and interclass correlation coefficient (ICC) measures, for diffuse and focal lesions (small ≤10 mm and large >10 mm). RESULTS 47 sites of disease were outlined (23 focal, 24 diffuse) in different bed positions (pelvis = 22, thorax = 20, head and neck = 5). For all lesions, there was excellent intraobserver agreement with ICC of 0.99 (0.98-0.99) and COV of 5%. For interobserver agreement, ICC was 0.89 (0.8-0.934) and COV was 17%. There was poor interobserver agreement for diffuse disease (ICC = 0.46) and small lesions (ICC = 0.54).For test-retest reproducibility, excellent ICC (0.916) and COV (14.5%) values for mean ADC measurements were observed. ICCs of test-retest were similar between focal lesions (0.83) and diffuse infiltration (0.80), while ICCs were higher in pelvic (0.95) compared to thoracic (0.81) region and in small (0.96) compared to large (0.8) lesions. CONCLUSION ADC measurements of focal lesions in multiple myeloma are repeatable and reproducible, while there is more variation in ADC measurements of diffuse disease in patients with multiple myeloma. ADVANCES IN KNOWLEDGE Mean ADC measurements are repeatable and reproducible in focal lesions in multiple myeloma, while the ADC measurements of diffuse disease in multiple myeloma are more subject to variation. The evidence supports the future potential role of ADC measurements as predictive quantitative biomarker in multiple myeloma.
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Affiliation(s)
| | | | | | | | - Kathryn Wallitt
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Antoni Sergot
- Imperial College Healthcare NHS Trust, London, United Kingdom
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Advanced Imaging in Multiple Myeloma: New Frontiers for MRI. Diagnostics (Basel) 2022; 12:diagnostics12092182. [PMID: 36140583 PMCID: PMC9497462 DOI: 10.3390/diagnostics12092182] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 08/17/2022] [Accepted: 09/03/2022] [Indexed: 11/16/2022] Open
Abstract
Plasma cell dyscrasias are estimated to newly affect almost 40,000 people in 2022. They fall on a spectrum of diseases ranging from relatively benign to malignant, the malignant end of the spectrum being multiple myeloma (MM). The International Myeloma Working Group (IMWG) has traditionally outlined the diagnostic criteria and therapeutic management of MM. In the last two decades, novel imaging techniques have been employed for MM to provide more information that can guide not only diagnosis and staging, but also treatment efficacy. These imaging techniques, due to their low invasiveness and high reliability, have gained significant clinical attention and have already changed the clinical practice. The development of functional MRI sequences such as diffusion weighted imaging (DWI) or intravoxel incoherent motion (IVIM) has made the functional assessment of lesions feasible. Moreover, the growing availability of positron emission tomography (PET)–magnetic resonance imaging (MRI) scanners is leading to the potential combination of sensitive anatomical and functional information in a single step. This paper provides an organized framework for evaluating the benefits and challenges of novel and more functional imaging techniques used for the management of patients with plasma cell dyscrasias, notably MM.
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Wang Q, Zhang L, Li S, Sun Z, Wu X, Zhao A, Benkert T, Zhou D, Xue H, Jin Z, Li J. Histogram Analysis Based on Apparent Diffusion Coefficient Maps of Bone Marrow in Multiple Myeloma: An Independent Predictor for High-risk Patients Classified by the Revised International Staging System. Acad Radiol 2022; 29:e98-e107. [PMID: 34452820 DOI: 10.1016/j.acra.2021.07.010] [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: 12/14/2020] [Revised: 06/29/2021] [Accepted: 07/09/2021] [Indexed: 11/15/2022]
Abstract
RATIONALE AND OBJECTIVES The revised International Staging System (R-ISS) is the current risk stratifier for patients with newly diagnosed multiple myeloma (NDMM). We used histogram analysis based on apparent diffusion coefficient (ADC) maps of bone marrow to predict high-risk NDMM patients staged as R-ISS stage III. MATERIAL AND METHODS Sixty-one NDMM patients were recruited prospectively and underwent whole-body diffusion-weighted MRI. Mean ADC and four ADC-based histogram parameters of representative background bone marrow were quantified with TexRAD software, including ADC entropy, ADC standard deviation (SD), ADC skewness and ADC kurtosis. Diagnostic performance to discriminate R-ISS III from I/II disease was evaluated by receiver-operating characteristics curve (ROC). Univariate and multivariate analysis using stepwise logistic regression model was performed to identify predictors for R-ISS III. RESULTS ADC entropy of background marrow showed the highest areas under the ROC (0.784, sensitivity = 93.3%, specificity = 63.0%) for the detection of R-ISS stage III disease. Multivariate analysis showed that increased ADC entropy (>3.612) of background marrow can independently predict R-ISS stage III disease in the overall patients (Model 1 corrected for diffuse infiltration [DI] pattern: odds ratio [OR], 10.647; p = 0.008; Model 2 corrected for mean ADC: OR, 10.485; p = 0.010) and in the subgroup with DI pattern (OR, 7.043; p = 0.037). CONCLUSION ADC entropy of background marrow may serve as a sensitive imaging biomarker facilitating the detection of high-risk NDMM patients staged as R-ISS stage III. Increased ADC entropy of background marrow can independently predict R-ISS stage III in the overall patients and in the subgroup with DI pattern.
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Affiliation(s)
- Qin Wang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lu Zhang
- Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shuo Li
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhaoyong Sun
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xia Wu
- Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ailin Zhao
- Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Thomas Benkert
- Development of Application, Siemens Healthcare GmbH, Erlangen, Germany
| | - Daobin Zhou
- Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Huadan Xue
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Zhengyu Jin
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jian Li
- Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Koutoulidis V, Terpos E, Papanikolaou N, Fontara S, Seimenis I, Gavriatopoulou M, Ntanasis-Stathopoulos I, Bourgioti C, Santinha J, Moreira JM, Kastritis E, Dimopoulos MA, Moulopoulos LA. Comparison of MRI Features of Fat Fraction and ADC for Early Treatment Response Assessment in Participants with Multiple Myeloma. Radiology 2022; 304:137-144. [PMID: 35380497 DOI: 10.1148/radiol.211388] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Background An imaging-based predictor of response could provide prognostic information early during treatment course in patients with multiple myeloma (MM). Purpose To investigate if very early changes in bone marrow relative fat fraction (rFF) and apparent diffusion coefficient (ADC) histogram metrics, occurring after one cycle of induction therapy in participants with newly diagnosed MM, could help predict overall best response status. Materials and Methods This prospective study included participants with MM who were enrolled between August 2014 and December 2017. Histogram metrics were extracted from ADC and rFF maps from MRI examinations performed before treatment and after the first treatment cycle. Participants were categorized into the very good partial response (VGPR) or better group and the less than VGPR group per the International Myeloma Working Group response criteria. ADC and rFF map metrics for predicting treatment response were compared using the Wilcoxon rank test, and the false discovery rate (FDR) was used to correct for multiple comparisons. Results A total of 23 participants (mean age, 65 years ± 11 [SD]; 13 men) were evaluated. There was no evidence of a difference in ADC metrics between the two responder groups after correcting for multiple comparisons. The rFF histogram changes between pretreatment MRI and MRI after the first treatment cycle (ΔrFF) that provided significant differences between the VGPR or better and less than VGPR groups were as follows: ΔrFF_10th Percentile (median, 0.5 [95% CI: 0, 1] vs -2.5 [95% CI: -5.1, 0.1], respectively), ΔrFF_90th Percentile (median, 2 [95% CI: 1, 6.8] vs -0.5 [95% CI: -1, 0]), ΔrFF_Mean (median, 3.4 [95% CI: 0.3, 7.6] vs -1.1 [95% CI: -1.8, -0.7]), and ΔrFF_Root Mean Squared (median, 3.2 [95% CI: 0.3, 6.1] vs -0.7 [95% CI: -1.3, -0.4]) (FDR-adjusted P = .03 for all), and the latter two also presented mean group increases in the VGPR or better group that were above the upper 95% CI limit for repeatability. Conclusion Very early changes in bone marrow relative fat fraction histogram metrics, calculated from MRI examination at baseline and after only one cycle of induction therapy, may help to predict very good partial response or better in participants with newly diagnosed multiple myeloma. © RSNA, 2022 Online supplemental material is available for this article.
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Affiliation(s)
- Vassilis Koutoulidis
- From the 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 76 Vas. Sophias Ave, 11528 Athens, Greece (V.K., S.F., C.B., L.A.M.); Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Alexandra Hospital, Athens, Greece (E.T., M.G., I.N.S., E.K., M.A.D.); Computational Clinical Imaging Group, Center for the Unknown, Champalimaud Foundation, Lisbon, Portugal (N.P., J.S., J.M.M.); and Department of Medical Physics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece (I.S.)
| | - Evangelos Terpos
- From the 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 76 Vas. Sophias Ave, 11528 Athens, Greece (V.K., S.F., C.B., L.A.M.); Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Alexandra Hospital, Athens, Greece (E.T., M.G., I.N.S., E.K., M.A.D.); Computational Clinical Imaging Group, Center for the Unknown, Champalimaud Foundation, Lisbon, Portugal (N.P., J.S., J.M.M.); and Department of Medical Physics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece (I.S.)
| | - Nikolaos Papanikolaou
- From the 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 76 Vas. Sophias Ave, 11528 Athens, Greece (V.K., S.F., C.B., L.A.M.); Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Alexandra Hospital, Athens, Greece (E.T., M.G., I.N.S., E.K., M.A.D.); Computational Clinical Imaging Group, Center for the Unknown, Champalimaud Foundation, Lisbon, Portugal (N.P., J.S., J.M.M.); and Department of Medical Physics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece (I.S.)
| | - Sophia Fontara
- From the 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 76 Vas. Sophias Ave, 11528 Athens, Greece (V.K., S.F., C.B., L.A.M.); Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Alexandra Hospital, Athens, Greece (E.T., M.G., I.N.S., E.K., M.A.D.); Computational Clinical Imaging Group, Center for the Unknown, Champalimaud Foundation, Lisbon, Portugal (N.P., J.S., J.M.M.); and Department of Medical Physics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece (I.S.)
| | - Ioannis Seimenis
- From the 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 76 Vas. Sophias Ave, 11528 Athens, Greece (V.K., S.F., C.B., L.A.M.); Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Alexandra Hospital, Athens, Greece (E.T., M.G., I.N.S., E.K., M.A.D.); Computational Clinical Imaging Group, Center for the Unknown, Champalimaud Foundation, Lisbon, Portugal (N.P., J.S., J.M.M.); and Department of Medical Physics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece (I.S.)
| | - Maria Gavriatopoulou
- From the 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 76 Vas. Sophias Ave, 11528 Athens, Greece (V.K., S.F., C.B., L.A.M.); Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Alexandra Hospital, Athens, Greece (E.T., M.G., I.N.S., E.K., M.A.D.); Computational Clinical Imaging Group, Center for the Unknown, Champalimaud Foundation, Lisbon, Portugal (N.P., J.S., J.M.M.); and Department of Medical Physics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece (I.S.)
| | - Ioannis Ntanasis-Stathopoulos
- From the 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 76 Vas. Sophias Ave, 11528 Athens, Greece (V.K., S.F., C.B., L.A.M.); Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Alexandra Hospital, Athens, Greece (E.T., M.G., I.N.S., E.K., M.A.D.); Computational Clinical Imaging Group, Center for the Unknown, Champalimaud Foundation, Lisbon, Portugal (N.P., J.S., J.M.M.); and Department of Medical Physics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece (I.S.)
| | - Charis Bourgioti
- From the 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 76 Vas. Sophias Ave, 11528 Athens, Greece (V.K., S.F., C.B., L.A.M.); Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Alexandra Hospital, Athens, Greece (E.T., M.G., I.N.S., E.K., M.A.D.); Computational Clinical Imaging Group, Center for the Unknown, Champalimaud Foundation, Lisbon, Portugal (N.P., J.S., J.M.M.); and Department of Medical Physics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece (I.S.)
| | - João Santinha
- From the 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 76 Vas. Sophias Ave, 11528 Athens, Greece (V.K., S.F., C.B., L.A.M.); Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Alexandra Hospital, Athens, Greece (E.T., M.G., I.N.S., E.K., M.A.D.); Computational Clinical Imaging Group, Center for the Unknown, Champalimaud Foundation, Lisbon, Portugal (N.P., J.S., J.M.M.); and Department of Medical Physics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece (I.S.)
| | - José Maria Moreira
- From the 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 76 Vas. Sophias Ave, 11528 Athens, Greece (V.K., S.F., C.B., L.A.M.); Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Alexandra Hospital, Athens, Greece (E.T., M.G., I.N.S., E.K., M.A.D.); Computational Clinical Imaging Group, Center for the Unknown, Champalimaud Foundation, Lisbon, Portugal (N.P., J.S., J.M.M.); and Department of Medical Physics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece (I.S.)
| | - Efstathios Kastritis
- From the 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 76 Vas. Sophias Ave, 11528 Athens, Greece (V.K., S.F., C.B., L.A.M.); Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Alexandra Hospital, Athens, Greece (E.T., M.G., I.N.S., E.K., M.A.D.); Computational Clinical Imaging Group, Center for the Unknown, Champalimaud Foundation, Lisbon, Portugal (N.P., J.S., J.M.M.); and Department of Medical Physics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece (I.S.)
| | - Meletios A Dimopoulos
- From the 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 76 Vas. Sophias Ave, 11528 Athens, Greece (V.K., S.F., C.B., L.A.M.); Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Alexandra Hospital, Athens, Greece (E.T., M.G., I.N.S., E.K., M.A.D.); Computational Clinical Imaging Group, Center for the Unknown, Champalimaud Foundation, Lisbon, Portugal (N.P., J.S., J.M.M.); and Department of Medical Physics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece (I.S.)
| | - Lia A Moulopoulos
- From the 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 76 Vas. Sophias Ave, 11528 Athens, Greece (V.K., S.F., C.B., L.A.M.); Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Alexandra Hospital, Athens, Greece (E.T., M.G., I.N.S., E.K., M.A.D.); Computational Clinical Imaging Group, Center for the Unknown, Champalimaud Foundation, Lisbon, Portugal (N.P., J.S., J.M.M.); and Department of Medical Physics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece (I.S.)
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Mesguich C, Hulin C, Latrabe V, Lascaux A, Bordenave L, Hindié E. 18 F-FDG PET/CT and MRI in the Management of Multiple Myeloma: A Comparative Review. FRONTIERS IN NUCLEAR MEDICINE (LAUSANNE, SWITZERLAND) 2022; 1:808627. [PMID: 39355637 PMCID: PMC11440970 DOI: 10.3389/fnume.2021.808627] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 12/27/2021] [Indexed: 10/03/2024]
Abstract
During the last two decades, the imaging landscape of multiple myeloma (MM) has evolved with whole-body imaging techniques such as fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) and MRI replacing X-ray skeletal survey. Both imaging modalities have high diagnostic performance at the initial diagnosis of MM and are key players in the identification of patients needing treatment. Diffusion-weighted MRI has a high sensitivity for bone involvement, while 18F-FDG PET/CT baseline parameters carry a strong prognostic value. The advent of more efficient therapeutics, such as immunomodulatory drugs and proteasome inhibitors, has called for the use of sensitive imaging techniques for monitoring response to treatment. Diffusion-weighted MRI could improve the specificity of MRI for tumor response evaluation, but questions remain regarding its role as a prognostic factor. Performed at key time points of treatment in newly diagnosed MM patients, 18F-FDG PET/CT showed a strong association with relapse risk and survival. The deployment of minimal residual disease detection at the cellular or the molecular level may raise questions on the role of these imaging techniques, which will be addressed. This review summarizes and outlines the specificities and respective roles of MRI and 18F-FDG PET/CT in the management of MM.
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Affiliation(s)
- Charles Mesguich
- Department of Nuclear Medicine, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France
- University of Bordeaux, IMB, UMR CNRS 5251, INRIA Project Team Monc, Talence, France
| | - Cyrille Hulin
- Department of Haematology, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France
| | - Valérie Latrabe
- Department of Radiology, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France
| | - Axelle Lascaux
- Department of Haematology, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France
| | - Laurence Bordenave
- Department of Nuclear Medicine, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France
| | - Elif Hindié
- Department of Nuclear Medicine, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France
- University of Bordeaux, INCIA UMR-CNRS 5287, Talence, France
- Institut Universitaire de France (IUF), Paris, France
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Mena E, Turkbey EB, Lindenberg L. Modern radiographic imaging in multiple myeloma, what is the minimum requirement? Semin Oncol 2022; 49:86-93. [PMID: 35190200 PMCID: PMC9149049 DOI: 10.1053/j.seminoncol.2022.01.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 01/09/2022] [Indexed: 02/03/2023]
Abstract
Imaging innovations offer useful techniques applicable to many oncology specialties. Treatment advances in the field of multiple myeloma (MM) have increased the need for accurate diagnosis, particularly in the bone marrow, which is an essential component in myeloma-defining criteria. Modern imaging identifies osteolytic lesions, distinguishes solitary plasmacytoma from MM, and evaluates the presence of extramedullary disease. Furthermore, imaging is increasingly valuable in post-treatment response assessment. Detection of minimal residual disease after therapy carries prognostic implications and influences subsequent treatment planning. Whole-body low-dose Computed Tomography is now recommended over the conventional skeletal survey, and more sophisticated functional imaging methods, such as 18F-Fluorodeoxyglucose Positron Emission Tomography , and diffusion-weighted Magnetic Resonance Imaging are proving effective in the assessment and monitoring of MM disease. This review focuses on understanding indications and advantages of these imaging modalities for diagnosing and managing myeloma.
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Affiliation(s)
- Esther Mena
- Molecular Imaging Branch. National Cancer Institute, NIH, Bethesda, MD, USA
| | - Evrim B. Turkbey
- Department of Radiology and Imaging Sciences, National Institutes of Health, Bethesda, MD, USA
| | - Liza Lindenberg
- Molecular Imaging Branch. National Cancer Institute, NIH, Bethesda, MD, USA
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Application of diffusion-weighted whole-body MRI for response monitoring in multiple myeloma after chemotherapy: a systematic review and meta-analysis. Eur Radiol 2022; 32:2135-2148. [PMID: 35028748 DOI: 10.1007/s00330-021-08311-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 07/27/2021] [Accepted: 08/30/2021] [Indexed: 12/17/2022]
Abstract
OBJECTIVE Myeloma Response Assessment and Diagnosis System recently published provides a framework for the standardised interpretation of DW-WBMRI in response assessment of multiple myeloma (MM) based on expert opinion. However, there is a lack of meta-analysis providing higher-level evidence to support the recommendations. In addition, some disagreement exists in the literature regarding the effect of timing and lesion subtypes on apparent diffusion coefficient (ADC) value changes post-treatment. METHOD Medline, Cochrane and Embase were searched from inception to 20th July 2021, using terms reflecting multiple myeloma and DW-WBMRI. Using PRISMA reporting guidelines, data were extracted by two investigators. Quality was assessed by the Quality Assessment of Diagnostic Accuracy Studies-2 method. RESULTS Of the 74 papers screened, 10 studies were included comprising 259 patients (127 males and 102 females) and 1744 reported lesions. Responders showed a significant absolute ADC change of 0.21×10-3 mm/s2 (95% CI, 0.01-0.41) with little evidence of heterogeneity (Cochran Q, p = 0.12, I2 = 45%) or publication bias (p = 0.737). Non-responders did not show a significant absolute difference in ADC (0.06 ×10-3 mm/s2, 95% CI, -0.07 to 0.19). A percentage ADC increase of 34.78% (95% CI, 10.75-58.81) was observed in responders. Meta-regression showed an inverse trend between ADC increases and time since chemotherapy initiation which did not reach statistical significance (R2 = 20.46, p = 0.282). CONCLUSIONS This meta-analysis supports the use of the DW-WBMRI as an imaging biomarker for response assessment. More evidence is needed to further characterise ADC changes by lesion subtypes over time. KEY POINTS • In multiple myeloma patients who received chemotherapy, responders have a significant absolute increase in ADC values that is not seen in non-responders. • A 35% increase in ADC from baseline values is found to classify response post-induction chemotherapy which corroborates with expert opinion from the Myeloma Response Assessment and Diagnosis System. • More evidence is needed to further characterise ADC changes by lesion subtypes over time after induction of therapy.
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Prediction of Early Treatment Response in Multiple Myeloma Using MY-RADS Total Burden Score, ADC, and Fat Fraction From Whole-Body MRI: Impact of Anemia on Predictive Performance. AJR Am J Roentgenol 2021; 218:310-319. [PMID: 34523949 DOI: 10.2214/ajr.21.26534] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Background: The recently released Myeloma Response Assessment and Diagnosis System (MY-RADS) for multiple myeloma (MM) evaluation by whole-body MRI (WB-MRI) describes the total burden score. However, assessment is confounded by red bone marrow hyperplasia in anemia. Objective: To assess utility of the MY-RADS total burden score, ADC, and fat fraction (FF) from WB-MRI in predicting early treatment response in patients with newly diagnosed MM and to compare these measures' utility between patients with and without anemia. Methods: This retrospective study included 56 patients (mean age 57.4±9.6 years; 40 men, 16 women) with newly diagnosed MM who underwent baseline WB-MRI including DWI and mDixon sequences. Two radiologists recorded total burden score using MY-RADS and measured ADC and FF of diffuse and focal disease sites. Mean values across sites were derived. Interobserver agreement was evaluated; readers' mean assessments were used for further analyses. Presence of deep response after four cycles of induction chemotherapy was recorded. Patients were classified as anemic if having hemoglobin less than 100 g/L. Utility of WB-MRI parameters in predicting deep response was assessed. Results: A total of 24/56 patients showed deep response; a total of 25/56 patients had anemia. Interobserver agreement, expressed using intraclass correlation coefficients, ranged from 0.95 to 0.99. Among patients without anemia, those with deep response compared with those without deep response exhibited lower total burden score (9.0 vs 18.0), lower ADC (0.79x10-3mm2/s vs 1.08x10-3mm2/s), and higher FF (0.21 vs 0.10) (all p<.001). The combination of these three parameters (optimal cutoffs: <15 for total burden score, <0.84×10-3mm2/s for ADC, >0.16 for FF) achieved sensitivity of 93.8%, specificity of 93.3%, and accuracy of 93.5% for predicting deep response. In patients with anemia, none of the three parameters were significantly different between those with and without deep response (all p>.05), and the combination of parameters achieved sensitivity of 56.3%, specificity of 100.0%, and accuracy of 72.0%. Conclusion: Low total burden score, low ADC, and high FF from WB-MRI may predict deep response in MM, though only among those patients without anemia. Clinical Impact: WB-MRI findings may help guide determination of prognosis and initial treatment selection in MM.
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Yamada A, Araki Y, Tanaka Y, Otsuki S, Yamada A, Moriyama M, Katagiri S, Suguro T, Asano M, Yoshizawa S, Akahane D, Furuya N, Fujimoto H, Okabe S, Gotoh M, Suzuki K, Saito K, Gotoh A. Relevance of diffusion-weighted imaging with background body signal suppression for staging, prognosis, morphology, treatment response, and apparent diffusion coefficient in plasma-cell neoplasms: A single-center, retrospective study. PLoS One 2021; 16:e0253025. [PMID: 34242226 PMCID: PMC8270139 DOI: 10.1371/journal.pone.0253025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 05/26/2021] [Indexed: 12/14/2022] Open
Abstract
Accurate staging and evaluation of therapeutic effects are important in managing plasma-cell neoplasms. Diffusion-weighted imaging with body signal suppression magnetic resonance imaging (DWIBS-MRI) allows for acquisition of whole-body volumetric data without radiation exposure. This study aimed to investigate the usefulness of DWIBS-MRI in plasma-cell neoplasms. We retrospectively analyzed 29 and 8 Japanese patients with multiple myeloma and monoclonal gammopathy of undetermined significance, respectively, who underwent DWIBS-MRI. We conducted a histogram analysis of apparent diffusion coefficient values. The correlations between each histogram parameter and staging, cell maturation, prognosis, and treatment response were evaluated. We found that the apparent diffusion coefficient values in patients with monoclonal gammopathy of undetermined significance were lower than those in patients with multiple myeloma. Pretreatment apparent diffusion coefficient values of immature myeloma were lower than those of mature myeloma. Moreover, these values decreased in proportion to stage progression in Durie-Salmon classification system but showed no significant correlation with other staging systems or prognosis. Patients were stratified as responder, stable, and non-responder based on the International Myeloma Working Group criteria. The magnitude of changes in apparent diffusion coefficients differed significantly between responders and non-responders (0.154 ± 0.386 ×10-3 mm2/s vs. -0.307 ± 0.424 ×10-3 mm2/s, p = 0.003). Although its usefulness has yet to be established, DWIBS-MRI combined with apparent diffusion coefficient measurement allowed for excellent response evaluation in patients with multiple myeloma. Furthermore, apparent diffusion coefficient analysis using DWIBS-MRI may be useful in predicting cell maturation and total tumor volume.
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Affiliation(s)
- Akiko Yamada
- Department of Hematology, Tokyo Medical University, Tokyo, Japan
| | - Yoichi Araki
- Department of Radiology, Tokyo Medical University, Tokyo, Japan
| | - Yuko Tanaka
- Department of Hematology, Tokyo Medical University, Tokyo, Japan
| | - Shunsuke Otsuki
- Department of Hematology, Tokyo Medical University, Tokyo, Japan
| | - Arisa Yamada
- Department of Hematology, Tokyo Medical University, Tokyo, Japan
| | - Mitsuru Moriyama
- Department of Hematology, Tokyo Medical University, Tokyo, Japan
| | | | - Tamiko Suguro
- Department of Hematology, Tokyo Medical University, Tokyo, Japan
| | - Michiyo Asano
- Department of Hematology, Tokyo Medical University, Tokyo, Japan
| | | | - Daigo Akahane
- Department of Hematology, Tokyo Medical University, Tokyo, Japan
| | - Nahoko Furuya
- Department of Hematology, Tokyo Medical University, Tokyo, Japan
| | - Hiroaki Fujimoto
- Department of Hematology, Tokyo Medical University, Tokyo, Japan
| | - Seiichi Okabe
- Department of Hematology, Tokyo Medical University, Tokyo, Japan
| | - Moritaka Gotoh
- Department of Hematology, Tokyo Medical University, Tokyo, Japan
| | - Kunihito Suzuki
- Department of Radiology, Tokyo Medical University, Tokyo, Japan
| | - Kazuhiro Saito
- Department of Radiology, Tokyo Medical University, Tokyo, Japan
| | - Akihiko Gotoh
- Department of Hematology, Tokyo Medical University, Tokyo, Japan
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17
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Zhang B, Bian B, Zhao Z, Lin F, Zhu Z, Lou M. Correlations between apparent diffusion coefficient values of WB-DWI and clinical parameters in multiple myeloma. BMC Med Imaging 2021; 21:98. [PMID: 34103001 PMCID: PMC8186136 DOI: 10.1186/s12880-021-00631-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 06/01/2021] [Indexed: 12/19/2022] Open
Abstract
Background Whole-body diffusion-weighted imaging (WB-DWI) is a method for evaluating bone marrow infiltration in multiple myeloma (MM). This study seeks to elucidate the correlation between the apparent diffusion coefficient (ADC) value and some selected clinical parameters.
Methods A total of 101 Chinese patients with MM who had undergone WB-DWI from May 2017 to May 2019 were enrolled in this study. The ADC values of the MM lesions and the clinical parameters were quantified at the first (baseline) visit and after four-course induction chemotherapy. Multiple linear regression and logistic analyses were carried out to find the implicit inherent relationships within the patients’ data. Results The paired Wilcoxon test showed that the ADC values at the baseline visit (ADC0) were significantly lower than the values after four-course induction chemotherapy (ADC4 c) (p < 0.001), including different therapeutic responses. The Revised International Staging System (RISS) stage, type of MM, and β2-microglobulin (β2-MG) were predictors of clinically significant increases or decreases in the ADC values (p < 0.05). Multiple linear regression showed that the ADC0 was negatively associated with β2-MG (p < 0.001) and immunoglobulin heavy chain gene rearrangement (p = 0.012), while the RISS Stage III (p = 0.001), type IgG λ (p = 0.005), and albumin were negatively associated with ADC4 c (p = 0.010). The impacts of the therapeutic response were associated with ADC0 and immunoglobulin heavy chain gene rearrangement (p < 0.001). Conclusion The ADC values of WB-DWI may be associated with clinical parameters of MM including the fluorescence in situ hybridization result, and may be useful in the prognosis of patients with MM. Trial Registration: ChiCTR2000029587
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Affiliation(s)
- Bei Zhang
- Shenzhen Clinical Medical School, Guangzhou University of Chinese Medicine, Shenzhen, China.,Department of Radiology, First Hospital of Jilin University, Changchun, China
| | - Bingyang Bian
- Department of Radiology, First Hospital of Jilin University, Changchun, China
| | - Zhiwei Zhao
- Department of Hand and Foot Surgery, First Hospital of Jilin University, Changchun, China
| | - Fang Lin
- Department of Radiology, First Hospital of Jilin University, Changchun, China
| | - Zining Zhu
- Department of Radiology, First Hospital of Jilin University, Changchun, China
| | - Mingwu Lou
- Shenzhen Clinical Medical School, Guangzhou University of Chinese Medicine, Shenzhen, China. .,Department of Radiology, Longgang Central Hospital of Shenzhen, No. 6082, Longgang Road, Longgang District, Shenzhen, 518116, Guangdong Province, China.
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18
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Mesguich C, Latrabe V, Hulin C, Lascaux A, Bordenave L, Hindié E, Marit G. Prospective Comparison of 18-FDG PET/CT and Whole-Body MRI with Diffusion-Weighted Imaging in the Evaluation of Treatment Response of Multiple Myeloma Patients Eligible for Autologous Stem Cell Transplant. Cancers (Basel) 2021; 13:cancers13081938. [PMID: 33923781 PMCID: PMC8074107 DOI: 10.3390/cancers13081938] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 04/07/2021] [Accepted: 04/13/2021] [Indexed: 11/16/2022] Open
Abstract
To compare the prognostic values of 18-FDG PET/CT (FDG-PET) and Whole-Body MRI with Diffusion-Weighted Imaging (WB-DW-MRI) in the evaluation of treatment response of Multiple Myeloma (MM) patients eligible for ASCT. Thirty patients with newly diagnosed MM prospectively underwent FDG-PET and WB-DW-MRI at baseline, after induction chemotherapy and after ASCT. Response on WB-DW-MRI was evaluated with the MY-RADS criteria. FDG-PET was considered positive if residual uptake was superior to liver uptake. Imaging results were not used for treatment modification. The impact of imaging results on PFS was analyzed. After a median follow-up of 32 months, 10 patients relapsed. With WB-DW-MRI, post-induction examination was positive in 3/25 and post-ASCT examination was positive in 3/27 patients. However, neither study showed prognostic impact on PFS. FDG-PET was positive in 5/22 post-induction and 3/26 patients post-ASCT, respectively. Positivity of FDG-PET, post-induction or post-ASCT, was associated with a shorter PFS (post-induction: median PFS 19 months vs. not reached, log-rank p = 0.0089; post-ASCT: median PFS 18 months vs. not reached, log-rank p = 0.0005). Preliminary results from this small, single-center, prospective study show that, whether performed post-induction or post-ASCT, FDG-PET has a higher prognostic value than WB-DW-MRI for treatment response evaluation of newly diagnosed MM.
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Affiliation(s)
- Charles Mesguich
- Nuclear Medicine Department, CHU Bordeaux, F-33000 Bordeaux, France; (L.B.); (E.H.)
- INSERM U1035, University of Bordeaux, F-33000 Bordeaux, France;
- Correspondence: ; Tel.: +33-5-57656335
| | - Valérie Latrabe
- Radiology Department, CHU Bordeaux, F-33000 Bordeaux, France;
| | - Cyrille Hulin
- Haematology Department, CHU Bordeaux, F-33000 Bordeaux, France; (C.H.); (A.L.)
| | - Axelle Lascaux
- Haematology Department, CHU Bordeaux, F-33000 Bordeaux, France; (C.H.); (A.L.)
| | - Laurence Bordenave
- Nuclear Medicine Department, CHU Bordeaux, F-33000 Bordeaux, France; (L.B.); (E.H.)
| | - Elif Hindié
- Nuclear Medicine Department, CHU Bordeaux, F-33000 Bordeaux, France; (L.B.); (E.H.)
| | - Gerald Marit
- INSERM U1035, University of Bordeaux, F-33000 Bordeaux, France;
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19
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Comparison of [ 18F]FDG PET/CT and MRI for Treatment Response Assessment in Multiple Myeloma: A Meta-Analysis. Diagnostics (Basel) 2021; 11:diagnostics11040706. [PMID: 33920809 PMCID: PMC8071116 DOI: 10.3390/diagnostics11040706] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 04/10/2021] [Accepted: 04/13/2021] [Indexed: 11/17/2022] Open
Abstract
The present study was designed to assess the additional value of 2-deoxy-2[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) to magnetic resonance imaging (MRI) in the treatment response assessment of multiple myeloma (MM). We performed a meta-analysis of all available studies to compare the detectability of treatment response of [18F]FDG PET/CT and MRI in treated MM. We defined detecting a good therapeutic effect as positive, and residual disease as negative. We determined the sensitivities and specificities across studies, calculated the positive and negative likelihood ratios (LR), and made summary receiver operating characteristic curves (SROC) using hierarchical regression models. The pooled analysis included six studies that comprised 278 patients. The respective performance characteristics (95% confidence interval (CI)) of [18F]FDG PET/CT and MRI were as follows: sensitivity of 80% (56% to 94%) and 25% (19% to 31%); specificity of 58% (44% to 71%) and 83% (71% to 91%); diagnostic odds ratio (DOR) of 6.0 (3.0-12.0) and 1.7 (0.7-2.7); positive LR of 1.8 (1.3-2.4) and 1.4 (0.7-2.7); and negative LR of 0.33 (0.21-0.53) and 0.81 (0.62-1.1). In the respective SROC curves, the area under the curve was 0.77 (SE, 0.038) and 0.59 (SE, 0.079) and the Q* index was 0.71 and 0.57. Compared with MRI, [18F]FDG PET/CT had higher sensitivity and better DOR and SROC curves. Compared with MRI, [18F]FDG PET/CT had greater ability to detect the treatment assessment of MM.
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20
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Paternain A, García-Velloso MJ, Rosales JJ, Ezponda A, Soriano I, Elorz M, Rodríguez-Otero P, Aquerreta JD. The utility of ADC value in diffusion-weighted whole-body MRI in the follow-up of patients with multiple myeloma. Correlation study with 18F-FDG PET-CT. Eur J Radiol 2020; 133:109403. [PMID: 33202373 DOI: 10.1016/j.ejrad.2020.109403] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 10/29/2020] [Accepted: 11/03/2020] [Indexed: 12/17/2022]
Abstract
OBJECTIVES To analyze the feasibility of DWI-MRI and ADC to evaluate treatment response in patients with multiple myeloma (MM). To correlate the variations of ADC and SUVmax in 18F-FDG PET-CT. METHODS 27 patients with MM that had a whole-body MRI and 18F-FDG PET-CT performed at baseline and after treatment were retrospectively recruited between February 2018 and May 2020. Three target bone lesions were selected for each patient and their ADC, SUVmax and Deauville score were measured in every study. Correlation between ADC and SUVmax of the lesions was evaluated, as well as changes in mean ADC, SUVmax, and Deauville score between studies. Patients were classified as responder or non-responder according to the IMWG, MRI (MY-RADS) and PET-CT (IMPeTUs) response criteria. Agreement between the MRI and PET-CT criteria with the IMWG criteria was evaluated. RESULTS The correlation between the ADC and SUVmax of all the target lesions was strong, negative and significant (r=-0.603; p < 0.001). After treatment, mean ADC in lesions from responders was significantly higher than in non-responders (1585.51 × 10-6 mm2/s vs 698.17 × 10-6 mm2/s; p < 0.001). SUVmax of the same lesions was significantly lower in responders than in non-responders (2.05 vs 5.33; p < 0.001). There was a very strong or strong agreement of the IMWG response criteria with both MRI (κ = 0.852; p < 0.001) and PET (κ = 0.767; p < 0.001) criteria. CONCLUSION DWI-MRI and ADC may be used to assess treatment response in MM patients, showing a good correlation with 18F-FDG PET-CT and the IMWG response criteria.
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Affiliation(s)
- Alberto Paternain
- Clínica Universidad de Navarra, Avenida Pío XII, 36., Pamplona, Spain.
| | | | - Juan José Rosales
- Clínica Universidad de Navarra, Avenida Pío XII, 36., Pamplona, Spain
| | - Ana Ezponda
- Clínica Universidad de Navarra, Avenida Pío XII, 36., Pamplona, Spain
| | - Ignacio Soriano
- Clínica Universidad de Navarra, Avenida Pío XII, 36., Pamplona, Spain
| | - Mariana Elorz
- Clínica Universidad de Navarra, Avenida Pío XII, 36., Pamplona, Spain
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