Apparent Diffusion Coefficient Maps Integrated in Whole-Body MRI Examination for the Evaluation of Tumor Response to Chemotherapy in Patients with Multiple Myeloma

Bonaffini, Pietro Andrea; Ippolito, Davide; Casiraghi, Alessandra; Besostri, Valeria; Franzesi, Cammillo Talei; Sironi, Sandro

doi:10.1016/j.acra.2015.05.011

Cited by 30 publications

(28 citation statements)

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“…However, they all reported consistent increases in mean ADC after therapy 40 and a significant degree of ADC increase in responders. 38,39,41 Interestingly, similar to the previously mentioned bone metastasis study, high increases of ADC in MM were found at 1 month after treatment began and the value decreased at 20 weeks after treatment. 39,41 One study showed an inverse relationship between ADC and fat fraction through two-point Dixon measurement, and suggested that the initial increase of ADC might reflect necrosis and edema, whereas the consequent decrease might reflect the return of normal marrow fat.…”

Section: Adc For Therapeutic Assessmentsupporting

confidence: 85%

“…Variable low ADCs have been reported in osteosarcoma (OS), Ewing sarcoma, plasmacytoma, multiple myeloma (MM), lymphoma, and bone metastases . Among them, small round cell tumors like Ewing sarcoma, plasmacytoma, MM, and lymphoma tend to have somewhat consistently lower values around 0.9 × 10 −3 mm 2 /s, with some overlapping with the range of normal red marrow . In OS, variable ADC can be measured according to histological features (Fig.…”

Section: Apparent Diffusion Coefficient (Adc)mentioning

confidence: 99%

“…ADC has also been explored for therapeutic assessment of MM and lymphoma . For MM, the amount of time after therapy began (3 weeks to 7 months) and the definition of responder varied in each study.…”

Section: Apparent Diffusion Coefficient (Adc)mentioning

confidence: 99%

“…36 Among them, small round cell tumors like Ewing sarcoma, plasmacytoma, MM, and lymphoma tend to have somewhat consistently lower values around 0.9 × 10 −3 mm 2 /s, with some overlapping with the range of normal red marrow. 29,[34][35][36][37][38][39][40][41][42] In OS, variable ADC can be measured according to histological features 43 (Fig. 5).…”

Section: Adc For Benign and Malignant Osseous Tumorsmentioning

confidence: 99%

“…ADC has also been explored for therapeutic assessment of MM and lymphoma. [38][39][40][41][42] For MM, the amount of time after therapy began (3 weeks to 7 months) and the definition of responder varied in each study. However, they all reported consistent increases in mean ADC after therapy 40 and a significant degree of ADC increase in responders.…”

Section: Adc For Therapeutic Assessmentmentioning

confidence: 99%

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MRI biomarkers in osseous tumors

Fukuda

Wengler

Carvalho

et al. 2019

Magnetic Resonance Imaging

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Although radiography continues to play a critical role in osseous tumor assessment, there have been remarkable advances in cross‐sectional imaging. MRI has taken a lead in this assessment due to high tissue contrast and spatial resolution, which are well suited for bone lesion assessment. More recently, although somewhat lagging other organ systems, quantitative parameters have shown promising potential as biomarkers for osseous tumors. Among these sequences are chemical shift imaging (CSI), apparent diffusion coefficient (ADC), and intravoxel incoherent motion (IVIM) from diffusion‐weighted imaging (DWI), quantitative dynamic contrast enhanced (DCE)‐MRI, and magnetic resonance spectroscopy (MRS). In this article, we review the background and recent roles of these quantitative MRI biomarkers for osseous tumors. Level of Evidence: 3 Technical Efficacy Stage: 3 J. MAGN. RESON. IMAGING 2019. J. Magn. Reson. Imaging 2019;50:702–718.

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Section: Adc For Therapeutic Assessmentsupporting

confidence: 85%

Section: Apparent Diffusion Coefficient (Adc)mentioning

confidence: 99%

Section: Apparent Diffusion Coefficient (Adc)mentioning

confidence: 99%

Section: Adc For Benign and Malignant Osseous Tumorsmentioning

confidence: 99%

Section: Adc For Therapeutic Assessmentmentioning

confidence: 99%

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MRI biomarkers in osseous tumors

Fukuda

Wengler

Carvalho

et al. 2019

Magnetic Resonance Imaging

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Treatment Response Assessment in Multiple Myeloma: Histogram Analysis of Total Tumor Apparent Diffusion Coefficient based on Whole‐body Diffusion‐weighted MR Imaging

Gao,

Wang,

Zhang

et al. 2023

Magnetic Resonance Imaging

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BackgroundThe 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.PurposeTo 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 TypeRetrospective.PopulationThirty‐six patients with NDMM.Field Strength/Sequence3.0T/single‐shot DWI echo planar imaging (EPI) sequence with an integrated slice‐by‐slice shimming (iShim) technique.AssessmentBaseline (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 TestsMann–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.ResultsThirty 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 ConclusionttADC histogram may facilitate response assessment in patients with NDMM.Level of Evidence3Technical EfficacyStage 4

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