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Ghasemi A, Ahlawat S, Fayad LM. Magnetic Resonance Imaging Biomarkers of Bone and Soft Tissue Tumors. Semin Musculoskelet Radiol 2024; 28:39-48. [PMID: 38330969 DOI: 10.1055/s-0043-1776433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Abstract
Magnetic resonance imaging (MRI) is essential in the management of musculoskeletal (MSK) tumors. This review delves into the diverse MRI modalities, focusing on anatomical, functional, and metabolic sequences that provide essential biomarkers for tumor detection, characterization, disease extent determination, and assessment of treatment response. MRI's multimodal capabilities offer a range of biomarkers that enhance MSK tumor evaluation, aiding in better patient management.
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Affiliation(s)
- Ali Ghasemi
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Shivani Ahlawat
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Laura Marie Fayad
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins Medical Institutions, Baltimore, Maryland
- Department of Orthopaedic Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland
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Yan SY, Yang YW, Jiang XY, Hu S, Su YY, Yao H, Hu CH. Fat quantification: Imaging methods and clinical applications in cancer. Eur J Radiol 2023; 164:110851. [PMID: 37148843 DOI: 10.1016/j.ejrad.2023.110851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 04/19/2023] [Accepted: 04/24/2023] [Indexed: 05/08/2023]
Abstract
Recently, the study of the relationship between lipid metabolism and cancer has evolved. The characteristics of intratumoral and peritumoral fat are distinct and changeable during cancer development. Subcutaneous and visceral adipose tissue are also associated with cancer prognosis. In non-invasive imaging, fat quantification parameters such as controlled attenuation parameter, fat volume fraction, and proton density fat fraction from different imaging methods complement conventional images by providing concrete fat information. Therefore, measuring the changes of fat content for further understanding of cancer characteristics has been applied in both research and clinical settings. In this review, the authors summarize imaging advances in fat quantification and highlight their clinical applications in cancer precaution, auxiliary diagnosis and classification, therapy response monitoring, and prognosis.
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Affiliation(s)
- Suo Yu Yan
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China
| | - Yi Wen Yang
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China
| | - Xin Yu Jiang
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China
| | - Su Hu
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China
| | - Yun Yan Su
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China.
| | - Hui Yao
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China; Department of General Surgery, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China.
| | - Chun Hong Hu
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China.
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Wennmann M, Neher P, Stanczyk N, Kahl KC, Kächele J, Weru V, Hielscher T, Grözinger M, Chmelik J, Zhang KS, Bauer F, Nonnenmacher T, Debic M, Sauer S, Rotkopf LT, Jauch A, Schlamp K, Mai EK, Weinhold N, Afat S, Horger M, Goldschmidt H, Schlemmer HP, Weber TF, Delorme S, Kurz FT, Maier-Hein K. Deep Learning for Automatic Bone Marrow Apparent Diffusion Coefficient Measurements From Whole-Body Magnetic Resonance Imaging in Patients With Multiple Myeloma: A Retrospective Multicenter Study. Invest Radiol 2023; 58:273-282. [PMID: 36256790 DOI: 10.1097/rli.0000000000000932] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/15/2023]
Abstract
OBJECTIVES Diffusion-weighted magnetic resonance imaging (MRI) is increasingly important in patients with multiple myeloma (MM). The objective of this study was to train and test an algorithm for automatic pelvic bone marrow analysis from whole-body apparent diffusion coefficient (ADC) maps in patients with MM, which automatically segments pelvic bones and subsequently extracts objective, representative ADC measurements from each bone. MATERIALS AND METHODS In this retrospective multicentric study, 180 MRIs from 54 patients were annotated (semi)manually and used to train an nnU-Net for automatic, individual segmentation of the right hip bone, the left hip bone, and the sacral bone. The quality of the automatic segmentation was evaluated on 15 manually segmented whole-body MRIs from 3 centers using the dice score. In 3 independent test sets from 3 centers, which comprised a total of 312 whole-body MRIs, agreement between automatically extracted mean ADC values from the nnU-Net segmentation and manual ADC measurements from 2 independent radiologists was evaluated. Bland-Altman plots were constructed, and absolute bias, relative bias to mean, limits of agreement, and coefficients of variation were calculated. In 56 patients with newly diagnosed MM who had undergone bone marrow biopsy, ADC measurements were correlated with biopsy results using Spearman correlation. RESULTS The ADC-nnU-Net achieved automatic segmentations with mean dice scores of 0.92, 0.93, and 0.85 for the right pelvis, the left pelvis, and the sacral bone, whereas the interrater experiment gave mean dice scores of 0.86, 0.86, and 0.77, respectively. The agreement between radiologists' manual ADC measurements and automatic ADC measurements was as follows: the bias between the first reader and the automatic approach was 49 × 10 -6 mm 2 /s, 7 × 10 -6 mm 2 /s, and -58 × 10 -6 mm 2 /s, and the bias between the second reader and the automatic approach was 12 × 10 -6 mm 2 /s, 2 × 10 -6 mm 2 /s, and -66 × 10 -6 mm 2 /s for the right pelvis, the left pelvis, and the sacral bone, respectively. The bias between reader 1 and reader 2 was 40 × 10 -6 mm 2 /s, 8 × 10 -6 mm 2 /s, and 7 × 10 -6 mm 2 /s, and the mean absolute difference between manual readers was 84 × 10 -6 mm 2 /s, 65 × 10 -6 mm 2 /s, and 75 × 10 -6 mm 2 /s. Automatically extracted ADC values significantly correlated with bone marrow plasma cell infiltration ( R = 0.36, P = 0.007). CONCLUSIONS In this study, a nnU-Net was trained that can automatically segment pelvic bone marrow from whole-body ADC maps in multicentric data sets with a quality comparable to manual segmentations. This approach allows automatic, objective bone marrow ADC measurements, which agree well with manual ADC measurements and can help to overcome interrater variability or nonrepresentative measurements. Automatically extracted ADC values significantly correlate with bone marrow plasma cell infiltration and might be of value for automatic staging, risk stratification, or therapy response assessment.
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Affiliation(s)
| | - Peter Neher
- Medical Image Computing, German Cancer Research Center (DKFZ)
| | | | - Kim-Celine Kahl
- Medical Image Computing, German Cancer Research Center (DKFZ)
| | - Jessica Kächele
- Medical Image Computing, German Cancer Research Center (DKFZ)
| | - Vivienn Weru
- Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Thomas Hielscher
- Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | | | | | | | | | | | - Sandra Sauer
- Department of Internal Medicine V, Section Multiple Myeloma
| | | | | | | | - Elias Karl Mai
- Department of Internal Medicine V, Section Multiple Myeloma
| | - Niels Weinhold
- Department of Internal Medicine V, Section Multiple Myeloma
| | - Saif Afat
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen
| | - Marius Horger
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen
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Diffusion-weighted imaging (DWI) in diagnosis, staging, and treatment response assessment of multiple myeloma: a systematic review and meta-analysis. Skeletal Radiol 2023; 52:565-583. [PMID: 35881152 DOI: 10.1007/s00256-022-04119-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 07/06/2022] [Accepted: 07/07/2022] [Indexed: 02/02/2023]
Abstract
OBJECTIVE To evaluate the role of diffusion-weighted imaging (DWI) in the initial diagnosis, staging, and assessment of treatment response in patients with multiple myeloma (MM). MATERIALS AND METHODS A systematic literature review was conducted in PubMed, the Cochrane Library, EMBASE, Scopus, and Web of Science databases. The primary endpoints were defined as the diagnostic performance of DWI for disease detection, staging of MM, and assessing response to treatment in these patients. RESULTS Of 5881 initially reviewed publications, 33 were included in the final qualitative and quantitative meta-analysis. The diagnostic performance of DWI in the detection of patients with MM revealed pooled sensitivity and specificity of 86% (95% CI: 84-89) and 63% (95% CI: 56-70), respectively, with a diagnostic odds ratio (OR) of 14.98 (95% CI: 4.24-52.91). The pooled risk difference of 0.19 (95% CI: - 0.04-0.42) was reported in favor of upstaging with DWI compared to conventional MRI (P value = 0.1). Treatment response evaluation and ADCmean value changes across different studies showed sensitivity and specificity of approximately 78% (95% CI: 72-83) and 73% (95% CI: 61-83), respectively, with a diagnostic OR of 7.21 in distinguishing responders from non-responders. CONCLUSIONS DWI is not only a promising tool for the diagnosis of MM, but it is also useful in the initial staging and re-staging of the disease and treatment response assessment. This can aid clinicians with earlier initiation or change in treatment strategy, which could have prognostic significance for patients.
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Santoni A, Simoncelli M, Franceschini M, Ciofini S, Fredducci S, Caroni F, Sammartano V, Bocchia M, Gozzetti A. Functional Imaging in the Evaluation of Treatment Response in Multiple Myeloma: The Role of PET-CT and MRI. J Pers Med 2022; 12:jpm12111885. [PMID: 36579605 PMCID: PMC9696713 DOI: 10.3390/jpm12111885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 11/01/2022] [Accepted: 11/08/2022] [Indexed: 11/12/2022] Open
Abstract
Bone disease is among the defining characteristics of symptomatic Multiple Myeloma (MM). Imaging techniques such as fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET/CT) and magnetic resonance imaging (MRI) can identify plasma cell proliferation and quantify disease activity. This function renders these imaging tools as suitable not only for diagnosis, but also for the assessment of bone disease after treatment of MM patients. The aim of this article is to review FDG PET/CT and MRI and their applications, with a focus on their role in treatment response evaluation. MRI emerges as the technique with the highest sensitivity in lesions' detection and PET/CT as the technique with a major impact on prognosis. Their comparison yields different results concerning the best tool to evaluate treatment response. The inhomogeneity of the data suggests the need to address limitations related to these tools with the employment of new techniques and the potential for a complementary use of both PET/CT and MRI to refine the sensitivity and achieve the standards for minimal residual disease (MRD) evaluation.
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Terao T, Matsue K. Progress of modern imaging modalities in multiple myeloma. Int J Hematol 2022; 115:778-789. [DOI: 10.1007/s12185-022-03360-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 04/14/2022] [Accepted: 04/14/2022] [Indexed: 12/26/2022]
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Wu Z, Bian T, Dong C, Duan S, Fei H, Hao D, Xu W. Spinal MRI-Based Radiomics Analysis to Predict Treatment Response in Multiple Myeloma. J Comput Assist Tomogr 2022; 46:447-454. [PMID: 35405690 DOI: 10.1097/rct.0000000000001298] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVE The aim of this study was to explore the clinical utility of spinal magnetic resonance imaging-based radiomics to predict treatment response (TR) in patients with multiple myeloma (MM). METHODS A total of 123 MM patients (85 in the training cohort and 38 in the test cohort) with complete response (CR) (n = 40) or non-CR (n = 83) were retrospectively enrolled in the study. Key feature selection and data dimension reduction were performed using the least absolute shrinkage and selection operator regression. A nomogram was built by combining radiomic signatures and independent clinical risk factors. The prediction performance of the nomogram was assessed using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis. Treatment response was assessed by determining the serum and urinary levels of M-proteins, serum-free light chain ratio, and the percentage of bone marrow plasma cells. RESULTS Thirteen features were selected to build a radiomic signature. The International Staging System (ISS) stage was selected as an independent clinical factor. The radiomic signature and nomogram showed better calibration and higher discriminatory capacity (AUC of 0.929 and 0.917 for the radiomics and nomogram in the training cohort, respectively, and 0.862 and 0.874 for the radiomics and nomogram in the test cohort, respectively) than the clinical model (AUC of 0.661 and 0.674 in the training and test cohort, respectively). Decision curve analysis confirmed the clinical utility of the radiomics model. CONCLUSIONS Nomograms incorporating a magnetic resonance imaging-based radiomic signature and ISS stage help predict the response to chemotherapy for MM and can be useful in clinical decision-making.
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Affiliation(s)
| | - Tiantian Bian
- Breast Disease Center, the Affiliated Hospital of Qingdao University, Qingdao, Shandong
| | | | | | - Hairong Fei
- Department of Hematology, the Affiliated Hospital of Qingdao University, Qingdao, Shandong, 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: 14] [Impact Index Per Article: 7.0] [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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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: 1.5] [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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Lecouvet FE, Vekemans MC, Van Den Berghe T, Verstraete K, Kirchgesner T, Acid S, Malghem J, Wuts J, Hillengass J, Vandecaveye V, Jamar F, Gheysens O, Vande Berg BC. Imaging of treatment response and minimal residual disease in multiple myeloma: state of the art WB-MRI and PET/CT. Skeletal Radiol 2022; 51:59-80. [PMID: 34363522 PMCID: PMC8626399 DOI: 10.1007/s00256-021-03841-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 05/28/2021] [Accepted: 06/06/2021] [Indexed: 02/02/2023]
Abstract
Bone imaging has been intimately associated with the diagnosis and staging of multiple myeloma (MM) for more than 5 decades, as the presence of bone lesions indicates advanced disease and dictates treatment initiation. The methods used have been evolving, and the historical radiographic skeletal survey has been replaced by whole body CT, whole body MRI (WB-MRI) and [18F]FDG-PET/CT for the detection of bone marrow lesions and less frequent extramedullary plasmacytomas.Beyond diagnosis, imaging methods are expected to provide the clinician with evaluation of the response to treatment. Imaging techniques are consistently challenged as treatments become more and more efficient, inducing profound response, with more subtle residual disease. WB-MRI and FDG-PET/CT are the methods of choice to address these challenges, being able to assess disease progression or response and to detect "minimal" residual disease, providing key prognostic information and guiding necessary change of treatment.This paper provides an up-to-date overview of the WB-MRI and PET/CT techniques, their observations in responsive and progressive disease and their role and limitations in capturing minimal residual disease. It reviews trials assessing these techniques for response evaluation, points out the limited comparisons between both methods and highlights their complementarity with most recent molecular methods (next-generation flow cytometry, next-generation sequencing) to detect minimal residual disease. It underlines the important role of PET/MRI technology as a research tool to compare the effectiveness and complementarity of both methods to address the key clinical questions.
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Affiliation(s)
- Frederic E. Lecouvet
- Radiology Department, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, UCLouvain, Hippocrate Avenue 10, 1200 Brussels, Belgium
| | - Marie-Christiane Vekemans
- Haematology Unit, Cliniques Universitaires Saint-Luc, Institut de Recherche Expérimentale et Clinique (IREC), 1200 Brussels, Belgium
| | - Thomas Van Den Berghe
- Radiology Department, Universiteit Ghent, Sint-Pietersnieuwstraat 33, 9000 Gent, Belgium
| | - Koenraad Verstraete
- Radiology Department, Universiteit Ghent, Sint-Pietersnieuwstraat 33, 9000 Gent, Belgium
| | - Thomas Kirchgesner
- Radiology Department, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, UCLouvain, Hippocrate Avenue 10, 1200 Brussels, Belgium
| | - Souad Acid
- Radiology Department, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, UCLouvain, Hippocrate Avenue 10, 1200 Brussels, Belgium
| | - Jacques Malghem
- Radiology Department, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, UCLouvain, Hippocrate Avenue 10, 1200 Brussels, Belgium
| | - Joris Wuts
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, Avenue du Laerbeek 101, 1090 Jette, Belgium
| | - Jens Hillengass
- Departement of Medicine, Myeloma Unit, Park Comprehensive Cancer Center, Buffalo, NY USA
| | - Vincent Vandecaveye
- Radiology Department, Katholieke Univesiteit Leuven, Oude Markt, 13, 3000 Leuven, Belgium
| | - François Jamar
- Nuclear Medicine Department, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium
| | - Olivier Gheysens
- Nuclear Medicine Department, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium
| | - Bruno C. Vande Berg
- Radiology Department, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, UCLouvain, Hippocrate Avenue 10, 1200 Brussels, Belgium
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11
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Association of loss of spleen visualization on whole-body diffusion-weighted imaging with prognosis and tumor burden in patients with multiple myeloma. Sci Rep 2021; 11:23978. [PMID: 34907317 PMCID: PMC8671425 DOI: 10.1038/s41598-021-03496-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 12/03/2021] [Indexed: 12/05/2022] Open
Abstract
This study investigated the clinical significance of loss of spleen visualization (LSV) on whole-body diffusion-weighted imaging (WB-DWI) in patients with multiple myeloma (MM). The WB-DWI of 96 patients with newly diagnosed MM (NDMM) and 15 patients with smoldering MM (sMM) were retrospectively reviewed. LSV was observed in 56 patients with NDMM (58.3%) and 1 patient with sMM (6.7%). Patients with NDMM with LSV had a higher median infiltration of bone marrow plasma cells (80.0% vs. 50.0%, p < 0.001) and median total diffusion volume (median; 540.2 vs. 137.0 mL, p = 0.003) than patients without LSV. Patients with LSV had a lower spleen-to-spinal cord ratio (0.36 vs. 0.96, p < 0.001) and worse 2-year overall survival (OS) (84.6% vs. 100%, p = 0.032). Patients who did not recover spleen visualization during treatment had a worse prognosis, even when they obtained very good partial response (median progression-free survival: 13.2 months). Spleen histopathological findings revealed higher cellularity and diffuse myeloma cell infiltration in a patient with LSV and splenic amyloidosis without extramedullary hematopoiesis in a patient without LSV. Therefore, LSV indicates worse prognosis for patients with MM, even when the patient responds to treatment. Further studies are warranted to clarify the immunological role of spleen in MM.
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12
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Fervers P, Celik E, Bratke G, Maintz D, Baues C, Ruffing S, Pollman-Schweckhorst P, Kottlors J, Lennartz S, Große Hokamp N. Radiotherapy Response Assessment of Multiple Myeloma: A Dual-Energy CT Approach With Virtual Non-Calcium Images. Front Oncol 2021; 11:734819. [PMID: 34646776 PMCID: PMC8504158 DOI: 10.3389/fonc.2021.734819] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 09/01/2021] [Indexed: 12/19/2022] Open
Abstract
Background Life expectancy of patients with multiple myeloma (MM) has increased over the past decades, underlining the importance of local tumor control and avoidance of dose-dependent side effects of palliative radiotherapy (RT). Virtual noncalcium (VNCa) imaging from dual-energy computed tomography (DECT) has been suggested to estimate cellularity and metabolic activity of lytic bone lesions (LBLs) in MM. Objective To explore the feasibility of RT response monitoring with DECT-derived VNCa attenuation measurements in MM. Methods Thirty-three patients with 85 LBLs that had been irradiated and 85 paired non-irradiated LBLs from the same patients were included in this retrospective study. Irradiated and non-irradiated LBLs were measured by circular regions of interest (ROIs) on conventional and VNCa images in a total of 216 follow-up measurements (48 before and 168 after RT). Follow-ups were rated as therapy response, stable disease, or local progression according to the MD Anderson criteria. Receiver operating characteristic (ROC) analysis was performed to discriminate irradiated vs. non-irradiated and locally progressive vs. stable/responsive LBLs using absolute attenuation post-irradiation and percentage attenuation change for patients with pre-irradiation DECT, if available. Results Attenuation of LBLs decreased after RT depending on the time that had passed after irradiation [absolute thresholds for identification of irradiated LBLs 30.5–70.0 HU [best area under the curve [AUC] 0.75 (0.59–0.91)] and -77.0 to -22.5 HU [best AUC 0.85 (0.65–1.00)]/-50% and -117% to -167% proportional change of attenuation on conventional and VNCa images, respectively]. VNCa CT was significantly superior for identification of RT effects in LBLs with higher calcium content [best VNCa AUC 0.96 (0.91–1.00), best conventional CT AUC 0.64 (0.45–0.83)]. Thresholds for early identification of local irradiation failure were >20.5 HU on conventional CT [AUC 0.78 (0.68–0.88)] and >-27 HU on VNCa CT [AUC 0.83 (0.70–0.96)]. Conclusion Therapy response of LBLs after RT can be monitored by VNCa imaging based on regular myeloma scans, which yields potential for optimizing the lesion-specific radiation dose for local tumor control. Decreasing attenuation indicates RT response, while above threshold attenuation of LBLs precedes local irradiation failure.
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Affiliation(s)
- Philipp Fervers
- Department of Radiology, University Hospital of Cologne, Cologne, Germany
| | - Erkan Celik
- Department of Radiology, University Hospital of Cologne, Cologne, Germany
| | - Grischa Bratke
- Department of Radiology, University Hospital of Cologne, Cologne, Germany
| | - David Maintz
- Department of Radiology, University Hospital of Cologne, Cologne, Germany
| | - Christian Baues
- Department of Radiotherapy and Cyberknife Center, University Hospital of Cologne, Cologne, Germany
| | - Simon Ruffing
- Department of Radiotherapy and Cyberknife Center, University Hospital of Cologne, Cologne, Germany
| | | | - Jonathan Kottlors
- Department of Radiology, University Hospital of Cologne, Cologne, Germany
| | - Simon Lennartz
- Department of Radiology, University Hospital of Cologne, Cologne, Germany
| | - Nils Große Hokamp
- Department of Radiology, University Hospital of Cologne, Cologne, Germany
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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
- * E-mail:
| | - 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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14
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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: 1.0] [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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15
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Updates and Ongoing Challenges in Imaging of Multiple Myeloma: AJR Expert Panel Narrative Review. AJR Am J Roentgenol 2021; 217:775-785. [PMID: 33978464 DOI: 10.2214/ajr.21.25878] [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] [Indexed: 12/22/2022]
Abstract
Advances in the understanding and treatment of multiple myeloma have led to the need for more sensitive and accurate imaging of intramedullary and extramedullary disease. This role of imaging is underscored by recently revised imaging recommendations of the International Myeloma Working Group (IMWG). This narrative review discusses these recommendations from the IMWG for different disease stages, focusing on advanced whole-body modalities, and addresses related challenges and controversies. In the recommendations, whole-body low-dose CT is central in initial patient assessment, replacing the conventional skeletal survey. Although the recommendations favor MRI for diagnosis because of its superior sensitivity and utility in identifying myeloma-defining events, FDG PET/CT is recommended as the modality of choice for assessing treatment response. Consensus opinions are offered regarding the role of imaging in multiple myeloma for characterization of disease distribution, determination of prognosis, and response evaluation.
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16
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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: 2.0] [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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17
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Schmeel FC, Enkirch SJ, Luetkens JA, Faron A, Lehnen N, Sprinkart AM, Schmeel LC, Radbruch A, Attenberger U, Kukuk GM, Mürtz P. Diagnostic Accuracy of Quantitative Imaging Biomarkers in the Differentiation of Benign and Malignant Vertebral Lesions : Combination of Diffusion-Weighted and Proton Density Fat Fraction Spine MRI. Clin Neuroradiol 2021; 31:1059-1070. [PMID: 33787957 PMCID: PMC8648653 DOI: 10.1007/s00062-021-01009-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Accepted: 02/26/2021] [Indexed: 11/30/2022]
Abstract
Purpose To compare and combine the diagnostic performance of the apparent diffusion coefficient (ADC) derived from diffusion-weighted imaging (DWI) and proton density fat fraction (PDFF) derived from chemical-shift encoding (CSE)-based water-fat magnetic resonance imaging (MRI) for distinguishing benign and malignant vertebral bone marrow lesions (VBML). Methods A total of 55 consecutive patients with 53 benign (traumatic, inflammatory and primary) and 36 malignant (metastatic and hematologic) previously untreated VBMLs were prospectively enrolled in this IRB-approved study and underwent sagittal DWI (single-shot spin-echo echo-planar with multi-slice short TI inversion recovery fat suppression) and CSE-based MRI (gradient-echo 6‑point modified Dixon) in addition to routine clinical spine MRI at 1.5 T or 3.0 T. Diagnostic reference standard was established according to histopathology or imaging follow-up. The ADC = ADC (0, 800) and PDFF = fat / (water + fat) were calculated voxel-wise and examined for differences between benign and malignant lesions. Results The ADC and PDFF values of malignant lesions were significantly lower compared to benign lesions (mean ADC 861 × 10−6 mm2/s vs. 1323 × 10−6 mm2/s, p < 0.001; mean PDFF 3.1% vs. 28.2%, p < 0.001). The areas under the curve (AUC) and diagnostic accuracies were 0.847 (p < 0.001) and 85.4% (cut-off at 1084.4 × 10−6 mm2/s) for ADC and 0.940 (p < 0.001) and 89.9% for PDFF (cut-off at 7.8%), respectively. The combined use of ADC and PDFF improved the diagnostic accuracy to 96.6% (malignancy if ADC ≤ 1118.2 × 10−6 mm2/s and PDFF ≤ 20.0%, otherwise benign). Conclusion Quantitative evaluation of both ADC and PDFF was useful in differentiating benign VBMLs from malignancy. The combination of ADC and PDFF improved the diagnostic performance and yielded high diagnostic accuracy for the differentiation of benign and malignant VBMLs.
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Affiliation(s)
- Frederic Carsten Schmeel
- Department of Neuroradiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Venusberg-Campus 1, 53127, Bonn, Germany. .,Research Group Clinical Neuroimaging, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany.
| | - Simon Jonas Enkirch
- Department of Neuroradiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Julian Alexander Luetkens
- Department of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Anton Faron
- Department of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Nils Lehnen
- Department of Neuroradiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.,Research Group Clinical Neuroimaging, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Alois Martin Sprinkart
- Department of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Leonard Christopher Schmeel
- Department of Radiotherapy and Radiation Oncology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Alexander Radbruch
- Department of Neuroradiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.,Research Group Clinical Neuroimaging, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Ulrike Attenberger
- Department of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Guido Matthias Kukuk
- Department of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany.,Department of Radiology, Cantonal Hospital Graubuenden, Chur, Switzerland
| | - Petra Mürtz
- Department of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
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18
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Terao T, Machida Y, Narita K, Kuzume A, Tabata R, Tsushima T, Miura D, Takeuchi M, Tateishi U, Matsue K. Total diffusion volume in MRI vs. total lesion glycolysis in PET/CT for tumor volume evaluation of multiple myeloma. Eur Radiol 2021; 31:6136-6144. [PMID: 33496828 DOI: 10.1007/s00330-021-07687-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 12/18/2020] [Accepted: 01/13/2021] [Indexed: 12/30/2022]
Abstract
OBJECTIVE This study compared the tumor burden and prognostic impact of total diffusion volume (tDV) and total lesion glycolysis (TLG) in the same patients with newly diagnosed multiple myeloma (NDMM) simultaneously. We also examined the relationship between these imaging tumor volumes (TVs) and plasma cell (PC) TV in bone marrow (BM) specimens. METHODS We retrospectively reviewed the data of 63 patients with newly diagnosed multiple myeloma (NDMM) from April 2016 to March 2018. tDV was calculated from whole-body diffusion-weighted imaging and TLG was calculated from the average standard uptake value and the metabolic tumor volume, respectively. Cellularity of BM hematopoietic tissue and the percentage of BM PCs were used as a reference of PC volume in the BM. RESULTS The Spearman correlation coefficient between tDV and TLG was moderate (ɤs = 0.588, p < 0.001) when PET false-negative patients were excluded. There were positive correlations between the BM plasma cell volume (BMPCV) and the imaging TVs (ɤs = 0.505, vs. tDV; and 0.464, vs. TLG). Patients with high tDV and high TLG, as determined by the receiver operating characteristic curve, had worse survival; moreover, patients with both high tDV and high TLG showed the worst prognosis (median progression-free and overall survival: 13.2 and 28.9 months, respectively). CONCLUSIONS Although tDV and TLG each reflected the total TV, in several cases, tDV and TLG were discrepant due to the biological features of each MM. It is important to use both modalities for complementary assessment of total tumor burden and biological characteristics in MM. KEY POINTS • Total diffusion volume (tDV) and total lesion glycolysis (TLG) reflect the total tumor volume and have prognostic value in patients with multiple myeloma (MM). • tDV and TLG could assess MM from different biological perspectives and should be considered for each patient individually.
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Affiliation(s)
- Toshiki Terao
- Division of Haematology/Oncology, Department of Internal Medicine, Kameda Medical Centre, 929 Higashi-chou, Kamogawa, 296-8602, Japan.
| | - Youichi Machida
- Department of Radiology, Kameda Medical Centre, Kamogawa, Japan
| | - Kentaro Narita
- Division of Haematology/Oncology, Department of Internal Medicine, Kameda Medical Centre, 929 Higashi-chou, Kamogawa, 296-8602, Japan
| | - Ayumi Kuzume
- Division of Haematology/Oncology, Department of Internal Medicine, Kameda Medical Centre, 929 Higashi-chou, Kamogawa, 296-8602, Japan
| | - Rikako Tabata
- Division of Haematology/Oncology, Department of Internal Medicine, Kameda Medical Centre, 929 Higashi-chou, Kamogawa, 296-8602, Japan
| | - Takafumi Tsushima
- Division of Haematology/Oncology, Department of Internal Medicine, Kameda Medical Centre, 929 Higashi-chou, Kamogawa, 296-8602, Japan
| | - Daisuke Miura
- Division of Haematology/Oncology, Department of Internal Medicine, Kameda Medical Centre, 929 Higashi-chou, Kamogawa, 296-8602, Japan
| | - Masami Takeuchi
- Division of Haematology/Oncology, Department of Internal Medicine, Kameda Medical Centre, 929 Higashi-chou, Kamogawa, 296-8602, Japan
| | - Ukihide Tateishi
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, Tokyo, Japan
| | - Kosei Matsue
- Division of Haematology/Oncology, Department of Internal Medicine, Kameda Medical Centre, 929 Higashi-chou, Kamogawa, 296-8602, Japan
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Van Nieuwenhove S, Van Damme J, Padhani AR, Vandecaveye V, Tombal B, Wuts J, Pasoglou V, Lecouvet FE. Whole-body magnetic resonance imaging for prostate cancer assessment: Current status and future directions. J Magn Reson Imaging 2020; 55:653-680. [PMID: 33382151 DOI: 10.1002/jmri.27485] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 12/08/2020] [Accepted: 12/08/2020] [Indexed: 12/20/2022] Open
Abstract
Over the past decade, updated definitions for the different stages of prostate cancer and risk for distant disease, along with the advent of new therapies, have remarkably changed the management of patients. The two expectations from imaging are accurate staging and appropriate assessment of disease response to therapies. Modern, next-generation imaging (NGI) modalities, including whole-body magnetic resonance imaging (WB-MRI) and nuclear medicine (most often prostate-specific membrane antigen [PSMA] positron emission tomography [PET]/computed tomography [CT]) bring added value to these imaging tasks. WB-MRI has proven its superiority over bone scintigraphy (BS) and CT for the detection of distant metastasis, also providing reliable evaluations of disease response to treatment. Comparison of the effectiveness of WB-MRI and molecular nuclear imaging techniques with regard to indications and the definition of their respective/complementary roles in clinical practice is ongoing. This paper illustrates the evolution of WB-MRI imaging protocols, defines the current state-of-the art, and highlights the latest developments and future challenges. The paper presents and discusses WB-MRI indications in the care pathway of men with prostate cancer in specific key situations: response assessment of metastatic disease, "all in one" cancer staging, and oligometastatic disease.
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Affiliation(s)
- Sandy Van Nieuwenhove
- Department of Radiology and Medical Imaging, Cliniques Universitaires Saint-Luc, Institut de Recherche Expérimentale et Clinique, Université Catholique de Louvain, Brussels, Belgium
| | - Julien Van Damme
- Department of Urology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Anwar R Padhani
- Mount Vernon Cancer Centre, Mount Vernon Hospital, London, UK
| | - Vincent Vandecaveye
- Department of Radiology and Pathology, University Hospitals Leuven, Leuven, Belgium
| | - Bertrand Tombal
- Department of Urology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Joris Wuts
- Department of Radiology and Medical Imaging, Cliniques Universitaires Saint-Luc, Institut de Recherche Expérimentale et Clinique, Université Catholique de Louvain, Brussels, Belgium.,Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, Brussels, Belgium
| | - Vassiliki Pasoglou
- Department of Radiology and Medical Imaging, Cliniques Universitaires Saint-Luc, Institut de Recherche Expérimentale et Clinique, Université Catholique de Louvain, Brussels, Belgium
| | - Frederic E Lecouvet
- Department of Radiology and Medical Imaging, Cliniques Universitaires Saint-Luc, Institut de Recherche Expérimentale et Clinique, Université Catholique de Louvain, Brussels, Belgium
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