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

Yamada, Akiko; Araki, Yoichi; Tanaka, Yūko; Otsuki, Shunsuke; Yamada, Ayaka; Moriyama, Mitsuru; Katagiri, Seiichiro; Suguro, Tamiko; Asano, Michiyo; Yoshizawa, Seiichiro; Akahane, Daigo; Furuya, Nahoko; Fujimoto, Hiroaki; Okabe, Seiichi; Gotoh, Moritaka; Suzuki, Kunihito; Saito, Kazuhiro; Gotoh, Akihiko

doi:10.1371/journal.pone.0253025

Cited by 2 publications

(2 citation statements)

References 37 publications

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“…After induction chemotherapy, the ADC of intra-medullary lesions in MM patients increased significantly except for PD, which was preliminarily confirmed. Yamada et al [ 22 ] found that ADC value of MM treatment responders differed more significantly than that of non-responders (0.154 ± 0.386 × 10 −3 mm 2 /s vs –0.307 ± 0.424 × 10 −3 mm 2 /s, P = .003). In addition, it has been proved that ADC value was negatively correlated with survival time (r = –0.641, P < .001).…”

Section: Discussionmentioning

confidence: 99%

Role of whole-body diffusion-weighted imaging in evaluation of multiple myeloma

Wang

Zhang

et al. 2021

Medicine

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The evaluation of bone disease in multiple myeloma (MM) is an important topic in imaging. This study retrospectively investigated whole-body diffusion-weighted imaging (WB-DWI) in the evaluation of bone marrow infiltration and treatment response in MM. A total of 126 patients with MM who underwent WB-DWI between January 2016 and December 2020 were enrolled. All the patients received 4-course induction chemotherapy. WB-DWI was performed before and after chemotherapy to measure the apparent diffusion coefficient (ADC) values. According to gender and Revised International Staging System (RISS) staging groups, the relationship between ADC value and bone marrow plasma cell infiltration ratio before treatment were explored using Spearman and Pearson correlation coefficients. Comparison of ADC values before and after treatment according to different chemotherapy regimens and treatment response was performed by 2-independent samples non-parametric tests and t test. There was a negative correlation between the ADC value and the degree of bone marrow infiltration and this was statistically significant (r = –0.843, P < .001). In different gender and RISS groups, ADC value before treatment was negatively correlated with the proportion of plasma cell infiltration (male, r = –0.849; female, r = –0.836; Stage I, r = –0.659; Stage II, r = –0.870; Stage III, r = –0.745; all P < .001). The ADC values of all subjects increased to varying degrees after 4-course induction chemotherapy, including different chemotherapy regimens and treatment responses (all P < .05 except for progressive disease group). The ADC value was negatively correlated with the degree of bone marrow infiltration in different gender and RISS stages. The ADC value increased after treatment, but it was not consistent with progressive disease group. The increase of ADC value may indicate the disease burden and outcome of MM induced chemotherapy.

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Section: Discussionmentioning

confidence: 99%

Role of whole-body diffusion-weighted imaging in evaluation of multiple myeloma

Wang

Zhang

et al. 2021

Medicine

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“…Diffusion-weighted imaging (DWI) as part of whole-body magnetic resonance imaging (wb-MRI) is of great clinical value in imaging of MM patients 3,4 and is increasingly recommended for both initial workup and follow-up imaging. [5][6][7][8] Diffusion-weighted imaging allows assessment of the semiquantitative apparent diffusion coefficient (ADC), which has been shown to correlate with histology 9,10 and to differ significantly between the different stages of monoclonal plasma cell disorders, [9][10][11] between different classes of therapy response, 9,[12][13][14][15][16][17][18][19][20][21] and to be of predictive value for progression-free survival and overall survival. 22,23 The texture of the bone marrow is very heterogenous, and there is a large volume of bone marrow in which a region of interest (ROI) can be placed when the ADC is manually measured by radiologists.…”

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Deep Learning for Automatic Bone Marrow Apparent Diffusion Coefficient Measurements From Whole-Body Magnetic Resonance Imaging in Patients With Multiple Myeloma

Wennmann

Neher

Stanczyk³

et al. 2022

Invest Radiol

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ObjectivesDiffusion-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 MethodsIn 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.ResultsThe 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 mm2/s, 7 × 10−6 mm2/s, and −58 × 10−6 mm2/s, and the bias between the second reader and the automatic approach was 12 × 10−6 mm2/s, 2 × 10−6 mm2/s, and −66 × 10−6 mm2/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 mm2/s, 8 × 10−6 mm2/s, and 7 × 10−6 mm2/s, and the mean absolute difference between manual readers was 84 × 10−6 mm2/s, 65 × 10−6 mm2/s, and 75 × 10−6 mm2/s. Automatically extracted ADC values significantly correlated with bone marrow plasma cell infiltration (R = 0.36, P = 0.007).ConclusionsIn 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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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

Cited by 2 publications

References 37 publications

Role of whole-body diffusion-weighted imaging in evaluation of multiple myeloma

Role of whole-body diffusion-weighted imaging in evaluation of multiple myeloma

Deep Learning for Automatic Bone Marrow Apparent Diffusion Coefficient Measurements From Whole-Body Magnetic Resonance Imaging in Patients With Multiple Myeloma

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