Artificial intelligence-based, volumetric assessment of the bone marrow metabolic activity in [18F]FDG PET/CT predicts survival in multiple myeloma.

PURPOSE: Multiple myeloma (MM) is a highly heterogeneous disease with wide variations in patient outcome. [18F]FDG PET/CT can provide prognostic information in MM, but it is hampered by issues regarding standardization of scan interpretation. Our group has recently demonstrated the feasibility of automated, volumetric assessment of bone marrow (BM) metabolic activity on PET/CT using a novel artificial intelligence (AI)-based tool. Accordingly, the aim of the current study is to investigate the prognostic role of whole-body calculations of BM metabolism in patients with newly diagnosed MM using this AI tool. MATERIALS AND METHODS: Forty-four, previously untreated MM patients underwent whole-body [18F]FDG PET/CT. Automated PET/CT image segmentation and volumetric quantification of BM metabolism were based on an initial CT-based segmentation of the skeleton, its transfer to the standardized uptake value (SUV) PET images, subsequent application of different SUV thresholds, and refinement of the resulting regions using postprocessing. In the present analysis, ten different uptake thresholds (AI approaches), based on reference organs or absolute SUV values, were applied for definition of pathological tracer uptake and subsequent calculation of the whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Correlation analysis was performed between the automated PET values and histopathological results of the BM as well as patients' progression-free survival (PFS) and overall survival (OS). Receiver operating characteristic (ROC) curve analysis was used to investigate the discrimination performance of MTV and TLG for prediction of 2-year PFS. The prognostic performance of the new Italian Myeloma criteria for PET Use (IMPeTUs) was also investigated. RESULTS: Median follow-up [95% CI] of the patient cohort was 110 months [105-123 months]. AI-based BM segmentation and calculation of MTV and TLG were feasible in all patients. A significant, positive, moderate correlation was observed between the automated quantitative whole-body PET/CT parameters, MTV and TLG, and BM plasma cell infiltration for all ten [18F]FDG uptake thresholds. With regard to PFS, univariable analysis for both MTV and TLG predicted patient outcome reasonably well for all AI approaches. Adjusting for cytogenetic abnormalities and BM plasma cell infiltration rate, multivariable analysis also showed prognostic significance for high MTV, which defined pathological [18F]FDG uptake in the BM via the liver. In terms of OS, univariable and multivariable analysis showed that whole-body MTV, again mainly using liver uptake as reference, was significantly associated with shorter survival. In line with these findings, ROC curve analysis showed that MTV and TLG, assessed using liver-based cut-offs, could predict 2-year PFS rates. The application of IMPeTUs showed that the number of focal hypermetabolic BM lesions and extramedullary disease had an adverse effect on PFS. CONCLUSIONS: The AI-based, whole-body calculations of BM metabolism via the parameters MTV and TLG not only correlate with the degree of BM plasma cell infiltration, but also predict patient survival in MM. In particular, the parameter MTV, using the liver uptake as reference for BM segmentation, provides solid prognostic information for disease progression. In addition to highlighting the prognostic significance of automated, global volumetric estimation of metabolic tumor burden, these data open up new perspectives towards solving the complex problem of interpreting PET scans in MM with a simple, fast, and robust method that is not affected by operator-dependent interventions.

Quantitative assessment of bone marrow infiltration and characterization of tumor burden using dual-layer spectral CT in patients with multiple myeloma.

BACKGROUND: The aim of the study was to evaluate whether virtual calcium subtraction (VNCa) image extracted from dual-layer spectral CT could estimate bone marrow (BM) infiltration with MRI as the reference standard and characterize tumor burden in patients with multiple myeloma (MM). PATIENTS AND METHODS: Forty-seven patients with newly diagnosed MM were retrospectively enrolled. They had undergone whole-body low-dose dual-layer spectral CT (DLCT) and whole-body MRI within one week. VNCa images with calcium-suppressed (CaSupp) indices ranging from 25 to 95 at an interval of 10 and apparent diffusion coefficient (ADC) maps were quantitatively analyzed on vertebral bodies L1-L5 at the central slice of images. The optimal combination was selected by correlation analysis between CT numbers and ADC values. Then, it was used to characterize tumor burden by correlation analysis and receiver operating characteristic (ROC) curves analysis, including plasma cell infiltration rate (PCIR), high serum-free light chains (SFLC) ratio and the high-risk cytogenetic (HRC) status. RESULTS: The most significant quantitative correlation between CT numbers of VNCa images and ADC values could be found at CaSupp index 85 for averaged L1-L5 (r = 0.612, p < 0.001). It allowed quantitative evaluation of PCIR (r = 0.835, p < 0.001). It could also anticipate high SFLC ratio and the HRC status with area under the curve (AUC) of 0.876 and 0.760, respectively. CONCLUSIONS: The VNCa measurements of averaged L1-L5 showed the highest correlation with ADC at CaSupp index 85. It could therefore be used as additional imaging biomarker for non-invasive assessment of tumor burden if ADC is not feasible.

[68Ga]Pentixafor PET/CT for staging and prognostic assessment of newly diagnosed multiple myeloma: comparison to [18F]FDG PET/CT.

PURPOSE: To evaluate the prognostic performance of [68Ga]Pentixafor PET/CT at baseline for staging of patients with newly diagnosed multiple myeloma (MM) and to compare it with [18F]FDG PET/CT and the Revised-International Staging System (R-ISS). METHODS: Patients who underwent [68Ga]Pentixafor and [18F]FDG PET/CT imaging were retrospectively included. Patient staging was performed according to the Durie-Salmon PLUS staging system based on [68Ga]Pentixafor PET/CT and [18F]FDG PET/CT images, and the R-ISS. Progression-free survival (PFS) at patient follow-up was estimated using the Kaplan-Meier estimator and compared using the log-rank test. Area under the receiver operating characteristic curve (AUC) was calculated to assess predictive performance. RESULTS: Fifty-five MM patients were evaluated. Compared with [18F]FDG PET, [68Ga]Pentixafor PET detected 25 patients as the same stage, while 26 patients were upstaged and 4 patients were downstaged (P = 0.001). After considering the low-dose CT data, there was no statistically significant difference in the number of patients classified in each stage using [68Ga]Pentixafor PET/CT and [18F]FDG PET/CT (P = 0.091). [68Ga]Pentixafor PET/CT-based staging discriminated PFS outcomes in patients with different disease stages (stage I vs. stage II, stage I vs. stage III, and stage II vs. stage III; all P < 0.05), whereas for [18F]FDG PET/CT, there was only a difference in median PFS between stage I and III (P = 0.021). When staged by R-ISS, the median PFS for stage III was significantly lower than that for stage I and II (P = 0.008 and 0.035, respectively). When predicting 2-year PFS based on staging, the AUC of [68Ga]Pentixafor PET/CT was significantly higher than that of [68Ga]Pentixafor PET (0.923 vs. 0.821, P = 0.002), [18F]FDG PET (0.923 vs. 0.752 P = 0.002), and R-ISS (0.923 vs. 0.776, P = 0.005). CONCLUSIONS: [68Ga]Pentixafor PET/CT-based staging possesses substantial potential to predict disease progression in newly diagnosed MM patients.

The role of conventional and novel PET radiotracers in assessment of myeloma bone disease.

Over 80 % of patients with multiple myeloma (MM) experience osteolytic bone lesions, primarily due to an imbalanced interaction between osteoclasts and osteoblasts. This imbalance can lead to several adverse outcomes such as pain, fractures, limited mobility, and neurological impairments. Myeloma bone disease (MBD) raises the expense of management in addition to being a major source of disability and morbidity in myeloma patients. Whole-body x-ray radiography was the gold standard imaging modality for detecting lytic lesions. Osteolytic lesions are difficult to identify at an earlier stage on X-ray since the lesions do not manifest themselves on conventional radiographs until at least 30 % to 50 % of the bone mass has been destroyed. Hence, early diagnosis of osteolytic lesions necessitates the utilization of more complex and advanced imaging modalities, such as PET. One of the PET radiotracers that has been frequently investigated in MM is 18F-FDG, which has demonstrated a high level of sensitivity and specificity in detecting myeloma lesions. However, 18F-FDG PET/CT has several restrictions, and therefore the novel PET tracers that can overcome the limitations of 18F-FDG PET/CT should be further examined in assessment of MBD. The objective of this review article is to thoroughly examine the significance of both conventional and novel PET radiotracers in the assessment of MBD. The intention is to present the information in a manner that would be easily understood by healthcare professionals from diverse backgrounds, while minimizing the use of complex nuclear medicine terminology.

Apparent diffusion coefficient measurements of bone marrow infiltration patterns in multiple myeloma for the assessment of tumor burden - a feasibility study.

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 (ß2-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.

New Developments in Myeloma Treatment and Response Assessment.

Recent innovative strategies have dramatically redefined the therapeutic landscape for treating multiple myeloma patients. In particular, the development and application of immunotherapy and high-dose therapy have demonstrated high response rates and have prolonged remission duration. Over the past decade, new morphologic or hybrid imaging techniques have gradually replaced conventional skeletal surveys. PET/CT using 18F-FDG is a powerful imaging tool for the workup at diagnosis and for therapeutic evaluation allowing medullary and extramedullary assessment. The independent negative prognostic value for progression-free and overall survival derived from baseline PET-derived parameters such as the presence of extramedullary disease or paramedullary disease, as well as the number of focal bone lesions and SUVmax, has been reported in several large prospective studies. During therapeutic evaluation, 18F-FDG PET/CT is considered the reference imaging technique because it can be performed much earlier than MRI, which lacks specificity. Persistence of significant abnormal 18F-FDG uptake after therapy is an independent negative prognostic factor, and 18F-FDG PET/CT and medullary flow cytometry are complementary tools for detecting minimal residual disease before maintenance therapy. The definition of a PET metabolic complete response has recently been standardized and the interpretation criteria harmonized. The development of advanced PET analysis and radiomics using machine learning, as well as hybrid imaging with PET/MRI, offers new perspectives for multiple myeloma imaging. Most recently, innovative radiopharmaceuticals such as C-X-C chemokine receptor type 4-targeted small molecules and anti-CD38 radiolabeled antibodies have shown promising results for tumor phenotype imaging and as potential theranostics.

Application of an artificial intelligence-based tool in [18F]FDG PET/CT for the assessment of bone marrow involvement in multiple myeloma.

PURPOSE: [18F]FDG PET/CT is an imaging modality of high performance in multiple myeloma (MM). Nevertheless, the inter-observer reproducibility in PET/CT scan interpretation may be hampered by the different patterns of bone marrow (BM) infiltration in the disease. Although many approaches have been recently developed to address the issue of standardization, none can yet be considered a standard method in the interpretation of PET/CT. We herein aim to validate a novel three-dimensional deep learning-based tool on PET/CT images for automated assessment of the intensity of BM metabolism in MM patients. MATERIALS AND METHODS: Whole-body [18F]FDG PET/CT scans of 35 consecutive, previously untreated MM patients were studied. All patients were investigated in the context of an open-label, multicenter, randomized, active-controlled, phase 3 trial (GMMG-HD7). Qualitative (visual) analysis classified the PET/CT scans into three groups based on the presence and number of focal [18F]FDG-avid lesions as well as the degree of diffuse [18F]FDG uptake in the BM. The proposed automated method for BM metabolism assessment is based on an initial CT-based segmentation of the skeleton, its transfer to the SUV PET images, the subsequent application of different SUV thresholds, and refinement of the resulting regions using postprocessing. In the present analysis, six different SUV thresholds (Approaches 1-6) were applied for the definition of pathological tracer uptake in the skeleton [Approach 1: liver SUVmedian × 1.1 (axial skeleton), gluteal muscles SUVmedian × 4 (extremities). Approach 2: liver SUVmedian × 1.5 (axial skeleton), gluteal muscles SUVmedian × 4 (extremities). Approach 3: liver SUVmedian × 2 (axial skeleton), gluteal muscles SUVmedian × 4 (extremities). Approach 4: ≥ 2.5. Approach 5: ≥ 2.5 (axial skeleton), ≥ 2.0 (extremities). Approach 6: SUVmax liver]. Using the resulting masks, subsequent calculations of the whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in each patient were performed. A correlation analysis was performed between the automated PET values and the results of the visual PET/CT analysis as well as the histopathological, cytogenetical, and clinical data of the patients. RESULTS: BM segmentation and calculation of MTV and TLG after the application of the deep learning tool were feasible in all patients. A significant positive correlation (p < 0.05) was observed between the results of the visual analysis of the PET/CT scans for the three patient groups and the MTV and TLG values after the employment of all six [18F]FDG uptake thresholds. In addition, there were significant differences between the three patient groups with regard to their MTV and TLG values for all applied thresholds of pathological tracer uptake. Furthermore, we could demonstrate a significant, moderate, positive correlation of BM plasma cell infiltration and plasma levels of ß2-microglobulin with the automated quantitative PET/CT parameters MTV and TLG after utilization of Approaches 1, 2, 4, and 5. CONCLUSIONS: The automated, volumetric, whole-body PET/CT assessment of the BM metabolic activity in MM is feasible with the herein applied method and correlates with clinically relevant parameters in the disease. This methodology offers a potentially reliable tool in the direction of optimization and standardization of PET/CT interpretation in MM. Based on the present promising findings, the deep learning-based approach will be further evaluated in future prospective studies with larger patient cohorts.

Radiomics analysis of bone marrow biopsy locations in [18F]FDG PET/CT images for measurable residual disease assessment in multiple myeloma.

The combination of visual assessment of whole body [18F]FDG PET images and evaluation of bone marrow samples by Multiparameter Flow Cytometry (MFC) or Next-Generation Sequencing (NGS) is currently the most common clinical practice for the detection of Measurable Residual Disease (MRD) in Multiple Myeloma (MM) patients. In this study, radiomic features extracted from the bone marrow biopsy locations are analyzed and compared to those extracted from the whole bone marrow in order to study the representativeness of these biopsy locations in the image-based MRD assessment. Whole body [18F]FDG PET of 39 patients with newly diagnosed MM were included in the database, and visually evaluated by experts in nuclear medicine. A methodology for the segmentation of biopsy sites from PET images, including sternum and posterior iliac crest, and their subsequent quantification is proposed. First, starting from the bone marrow segmentation, a segmentation of the biopsy sites is performed. Then, segmentations are quantified extracting SUV metrics and radiomic features from the [18F]FDG PET images and are evaluated by Mann-Whitney U-tests as valuable features differentiating PET+/PET- and MFC+ /MFC- groups. Moreover, correlation between whole bone marrow and biopsy sites is studied by Spearman ρ rank. Classification performance of the radiomics features is evaluated applying seven machine learning algorithms. Statistical analyses reveal that some images features are significant in PET+/PET- differentiation, such as SUVmax, Gray Level Non-Uniformity or Entropy, especially with a balanced database where 16 of the features show a p value < 0.001. Correlation analyses between whole bone marrow and biopsy sites results in significant and acceptable coefficients, with 11 of the variables reaching a correlation coefficient greater than 0.7, with a maximum of 0.853. Machine learning algorithms demonstrate high performances in PET+/PET- classification reaching a maximum AUC of 0.974, but not for MFC+/MFC- classification. The results demonstrate the representativeness of sample sites as well as the effectiveness of extracted features (SUV metrics and radiomic features) from the [18F]FDG PET images in MRD assessment in MM patients.

Diffusion-weighted imaging (DWI) in diagnosis, staging, and treatment response assessment of multiple myeloma: a systematic review and meta-analysis.

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.

11C-Methionine PET/CT in Assessment of Multiple Myeloma Patients: Comparison to 18F-FDG PET/CT and Prognostic Value.

Multiple myeloma (MM) is the second most common haematological malignancy and remains incurable despite therapeutic advances. 18F-FDG (FDG) PET/CT is a relevant tool MM for staging and it is the reference imaging technique for treatment evaluation. However, it has limitations, and investigation of other PET tracers is required. Preliminary results with L-methyl-[11C]- methionine (MET), suggest higher sensitivity than 18F-FDG. This study aimed to compare the diagnostic accuracy and prognostic value of 1FDG and MET in MM patients. We prospectively compared FDG and MET PET/CT for assessment of bone disease and extramedullary disease (EMD) in a series of 52 consecutive patients (8 smoldering MM, 18 newly diagnosed MM and 26 relapsed MM patients). Bone marrow (BM) uptake patterns and the detection of focal lesions (FLs) and EMD were compared. Furthermore, FDG PET parameters with known MM prognostic value were explored for both tracers, as well as total lesion MET uptake (TLMU). Median patient age was 61 years (range, 37-83 years), 54% were male, 13% of them were in stage ISS (International Staging System) III, and 31% had high-risk cytogenetics. FDG PET/CT did not detect active disease in 6 patients, while they were shown to be positive by MET PET/CT. Additionally, MET PET/CT identified a higher number of FLs than FDG in more than half of the patients (63%). For prognostication we focussed on the relapsed cohort, due to the low number of progressions in the two other cohorts. Upon using FDG PET/CT in relapsed patients, the presence of more than 3 FLs (HR 4.61, p = 0.056), more than 10 FLs (HR 5.65, p = 0.013), total metabolic tumor volume (TMTV) p50 (HR 4.91, p = 0.049) or TMTV p75 (HR 5.32, p = 0.016) were associated with adverse prognosis. In MET PET/CT analysis, TMTV p50 (HR 4.71, p = 0.056), TMTV p75 (HR 6.27, p = 0.007), TLMU p50 (HR 8.8, p = 0.04) and TLMU p75 (HR 6.3, p = 0.007) adversely affected PFS. This study confirmed the diagnostic and prognostic value of FDG in MM. In addition, it highlights that MET has higher sensitivity than FDG PET/CT for detection of myeloma lesions, including FLs. Moreover, we show, for the first time, the prognostic value of TMTV and TLMU MET PET/CT in the imaging evaluation of MM patients.

Bone marrow segmentation and radiomics analysis of [18F]FDG PET/CT images for measurable residual disease assessment in multiple myeloma.

BACKGROUND AND OBJECTIVES: The last few years have been crucial in defining the most appropriate way to quantitatively assess [18F]FDG PET images in Multiple Myeloma (MM) patients to detect persistent tumor burden. The visual evaluation of images complements the assessment of Measurable Residual Disease (MRD) in bone marrow samples by multiparameter flow cytometry (MFC) or next-generation sequencing (NGS). The aim of this study was to quantify MRD by analyzing quantitative and texture [18F]FDG PET features. METHODS: Whole body [18F]FDG PET of 39 patients with newly diagnosed MM were included in the database, and visually evaluated by experts in nuclear medicine. A segmentation methodology of the skeleton from CT images and an additional manual segmentation tool were proposed, implemented in a software solution including a graphical user interface. Both the compact bone and the spinal canal were removed from the segmentation to obtain only the bone marrow mask. SUV metrics, GLCM, GLRLM, and NGTDM parameters were extracted from the PET images and evaluated by Mann-Whitney U-tests and Spearman ρ rank correlation as valuable features differentiating PET+/PET- and MFC+/MFC- groups. Seven machine learning algorithms were applied for evaluating the classification performance of the extracted features. RESULTS: Quantitative analysis for PET+/PET- differentiating demonstrated to be significant for most of the variables assessed with Mann-Whitney U-test such as Variance, Energy, and Entropy (p-value = 0.001). Moreover, the quantitative analysis with a balanced database evaluated by Mann-Whitney U-test revealed in even better results with 19 features with p-values < 0.001. On the other hand, radiomics analysis for MFC+/MFC- differentiating demonstrated the necessity of combining MFC evaluation with [18F]FDG PET assessment in the MRD diagnosis. Machine learning algorithms using the image features for the PET+/PET- classification demonstrated high performance metrics but decreasing for the MFC+/MFC- classification. CONCLUSIONS: A proof-of-concept for the extraction and evaluation of bone marrow radiomics features of [18F]FDG PET images was proposed and implemented. The validation showed the possible use of these features for the image-based assessment of MRD.

Comparison of MRI Features of Fat Fraction and ADC for Early Treatment Response Assessment in Participants with Multiple Myeloma.

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.

Dual-Energy CT-Based Bone Marrow Imaging in Multiple Myeloma: Assessment of Focal Lesions in Relation to Disease Status and MRI Findings.

RATIONALE AND OBJECTIVES: To assess focal multiple myeloma bone lesions via dual-energy CT-based virtual noncalcium (VNCa) bone marrow imaging in relation to the overall hematological disease status and MRI findings. MATERIALS AND METHODS: We retrospectively evaluated 103 focal osteolytic lesions of the axial skeleton in VNCa bone marrow images of 32 patients. Region of interest-based attenuation measurements were correlated with T1w signal intensity and apparent diffusion coefficient (ADC). Results were compared between patients in active and inactive disease. Receiver operating characteristic analysis was performed to determine a cut-off value of VNCa attenuation for differentiation between the two groups. Standard of reference was the overall disease status according to International Myeloma Working Group response criteria. RESULTS: Mean attenuation difference between lesions and background bone marrow was significantly lower in inactive disease (16 HU, SD 30) compared to active disease (35 HU, SD 29). VNCa attenuation measurement allowed for differentiation between active and inactive disease with a sensitivity of 92% and a specificity of 58% at a cut-off value of -21 HU. VNCa attenuation was negatively correlated to T1w signal intensity (Spearman's ρ -0.617, p < 0.001) and positively correlated to ADC (Spearman's ρ 0.521, p < 0.001). CONCLUSION: Quantitative assessment of attenuation of focal osteolytic lesions in VNCa bone marrow images allows differentiation between overall active and inactive disease with higher attenuation signifying an increasing likelihood of active disease. This is supported by a significant positive correlation between the attenuation and the ADC, as well as a corresponding inverse correlation to T1w signal intensity.

Radiation exposure and establishment of diagnostic reference levels of whole-body low-dose CT for the assessment of multiple myeloma with second- and third-generation dual-source CT.

BACKGROUND: In the assessment of diseases causing skeletal lesions such as multiple myeloma (MM), whole-body low-dose computed tomography (WBLDCT) is a sensitive diagnostic imaging modality, which has the potential to replace the conventional radiographic survey. PURPOSE: To optimize radiation protection and examine radiation exposure, and effective and organ doses of WBLDCT using different modern dual-source CT (DSCT) devices, and to establish local diagnostic reference levels (DRL). MATERIAL AND METHODS: In this retrospective study, 281 WBLDCT scans of 232 patients performed between January 2017 and April 2020 either on a second- (A) or third-generation (B) DSCT device could be included. Radiation exposure indices and organ and effective doses were calculated using a commercially available automated dose-tracking software based on Monte-Carlo simulation techniques. RESULTS: The radiation exposure indices and effective doses were distributed as follows (median, interquartile range): (A) second-generation DSCT: volume-weighted CT dose index (CTDIvol) 1.78 mGy (1.47-2.17 mGy); dose length product (DLP) 282.8 mGy·cm (224.6-319.4 mGy·cm), effective dose (ED) 1.87 mSv (1.61-2.17 mSv) and (B) third-generation DSCT: CTDIvol 0.56 mGy (0.47-0.67 mGy), DLP 92.0 mGy·cm (73.7-107.6 mGy·cm), ED 0.61 mSv (0.52-0.69 mSv). Radiation exposure indices and effective and organ doses were significantly lower with third-generation DSCT (P < 0.001). Local DRLs could be set for CTDIvol at 0.75 mGy and DLP at 120 mGy·cm. CONCLUSION: Third-generation DSCT requires significantly lower radiation dose for WBLDCT than second-generation DSCT and has an effective dose below reported doses for radiographic skeletal surveys. To ensure radiation protection, DRLs regarding WBLDCT are required, where our locally determined values may help as benchmarks.

Myeloma Response Assessment and Diagnosis System (MY-RADS): strategies for practice implementation.

Structured reporting systems have been developed for many organ systems and disease processes beginning with BI-RADS in 1993. Numerous reports indicate that referring health care providers prefer structured reports. Reducing variability of reports from one radiologist to another helps referring physician and patient confidence. Changing radiologists practice habits from completely free text to structured reports can be met with some resistance, but most radiologists quickly find that structured reports make their job easier. Whole-body MR studies are recommended as first-line imaging, by the International Myeloma Working Group (IMWG), for all patients with suspected diagnosis of asymptomatic myeloma and/or initial diagnosis of solitary plasmacytoma. Whole-body MR imaging (WBMRI) has been shown to have equal or greater sensitivity and specificity compared to PET/CT for detection of bone marrow involvement. Changing to WBMRI from other imaging modalities can be difficult for referring providers. Patient acceptance is high. MY-RADS is for myeloma patients who have WBMRI studies done. The intent of the system is to promote uniformity in MR imaging acquisition, diagnostic criteria, and response assessment and to diminish differences in the subsequent interpretation and reporting. A secondary benefit is a report template that provides a guide for interpretation for radiologists who may not have previously dictated these difficult studies. The characterization of bone marrow abnormalities in myeloma patients usually is fairly straightforward. To date, there is no standardized scoring or risk stratification of abnormalities nor is there an imaging atlas of abnormalities.

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.

BACKGROUND. The recently released Myeloma Response Assessment and Diagnosis System (MY-RADS) for multiple myeloma (MM) evaluation using whole-body MRI (WB-MRI) describes the total burden score. However, assessment is confounded by red bone marrow hyperplasia in anemia. OBJECTIVE. The purpose of this study is to assess the 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 the utility of these measures between patients with and without anemia. METHODS. This retrospective study included 56 patients (40 men, 16 women; mean age, 57.4 ± 9.6 [SD] years) with newly diagnosed MM who underwent baseline WB-MRI including DWI and modified Dixon sequences. Two radiologists recorded total burden score using MY-RADS and measured the ADC and FF of diffuse and focal disease sites. Mean values across sites were derived. Interobserver agreement was evaluated, and the mean assessments of the readers were used for further analyses. Presence of deep response after four cycles of induction chemotherapy was recorded. Patients were classified as having anemia if their hemoglobin level was less than 100 g/L. The utility of WBMRI parameters in predicting deep response was assessed. RESULTS. A total of 24 of 56 patients showed deep response, and 25 of 56 patients had anemia. Interobserver agreement, which was 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 had a lower total burden score (9.0 vs 18.0), a lower ADC (0.79 × 10-3 mm2/s vs 1.08 × 10-3 mm2/s), and a 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 × 10-3 mm2/s for ADC, and > 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 patients 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 patients with MM, although only among those without anemia. CLINICAL IMPACT. WB-MRI findings may help guide determination of prognosis and initial treatment selection in MM.

Feasibility of artificial intelligence-supported assessment of bone marrow infiltration using dual-energy computed tomography in patients with evidence of monoclonal protein - a retrospective observational study.

OBJECTIVES: To demonstrate the feasibility of an automated, non-invasive approach to estimate bone marrow (BM) infiltration of multiple myeloma (MM) by dual-energy computed tomography (DECT) after virtual non-calcium (VNCa) post-processing. METHODS: Individuals with MM and monoclonal gammopathy of unknown significance (MGUS) with concurrent DECT and BM biopsy between May 2018 and July 2020 were included in this retrospective observational study. Two pathologists and three radiologists reported BM infiltration and presence of osteolytic bone lesions, respectively. Bone mineral density (BMD) was quantified CT-based by a CE-certified software. Automated spine segmentation was implemented by a pre-trained convolutional neural network. The non-fatty portion of BM was defined as voxels > 0 HU in VNCa. For statistical assessment, multivariate regression and receiver operating characteristic (ROC) were conducted. RESULTS: Thirty-five patients (mean age 65 ± 12 years; 18 female) were evaluated. The non-fatty portion of BM significantly predicted BM infiltration after adjusting for the covariable BMD (p = 0.007, r = 0.46). A non-fatty portion of BM > 0.93% could anticipate osteolytic lesions and the clinical diagnosis of MM with an area under the ROC curve of 0.70 [0.49-0.90] and 0.71 [0.54-0.89], respectively. Our approach identified MM-patients without osteolytic lesions on conventional CT with a sensitivity and specificity of 0.63 and 0.71, respectively. CONCLUSIONS: Automated, AI-supported attenuation assessment of the spine in DECT VNCa is feasible to predict BM infiltration in MM. Further, the proposed method might allow for pre-selecting patients with higher pre-test probability of osteolytic bone lesions and support the clinical diagnosis of MM without pathognomonic lesions on conventional CT. KEY POINTS: • The retrospective study provides an automated approach for quantification of the non-fatty portion of bone marrow, based on AI-supported spine segmentation and virtual non-calcium dual-energy CT data. • An increasing non-fatty portion of bone marrow is associated with a higher infiltration determined by invasive biopsy after adjusting for bone mineral density as a control variable (p = 0.007, r = 0.46). • The non-fatty portion of bone marrow might support the clinical diagnosis of multiple myeloma when conventional CT images are negative (sensitivity 0.63, specificity 0.71).

Association of loss of spleen visualization on whole-body diffusion-weighted imaging with prognosis and tumor burden in patients with multiple myeloma.

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.