Monoclonal gammopathy of clinical signifi cance with osteosclerotic lesions - a case report and a literature review.

INTRODUCTION: Multiple myeloma is a common plasma cell neoplasia usually accompanied by the formation of osteolytic foci, whereas osteosclerotic myeloma is a very rare form of plasma cell dyscrasia. When osteosclerotic myeloma is detected, osteosclerotic foci are usually part of the POEMS syndrome. Osteosclerotic myeloma without other manifestations of the POEMS syndrome is an unusual finding. CASE DESCRIPTION: In a 46-year-old woman, osteosclerotic changes of the temporoparietal region caused soft tissue induration over this lesion, which initiated further investigation. Imaging studies subsequently showed multiple osteosclerotic foci in the skull. Examination of blood proteins revealed 8 g/L of IgG-lambda monoclonal immunoglobulin, subclass IgG1. In search of the cause of the osteosclerotic changes, FDG-PET/CT was performed, which revealed no FDG accumulation, i.e., no other tumor (breast or stomach cancer). Low-dose CT showed irregular bone structure, but not significant osteolytic or osteosclerotic foci. To map the extent of osteosclerotic changes, NaF-PET/CT imagination followed, which revealed multiple spots with high fluoride accumulation. A parietal bone biopsy showed osteosclerosis with minor clonal plasma cell infiltration. Trepanobioptic bone marrow sampling revealed an infiltration of bone marrow with atypical plasma cells in 8%. Flow-cytometric examination of bone marrow showed 0,37% of plasma cells, however predominantly (91%) clonal with lambda expression. MRI of the brain identified asymptomatic meningeal thickening. There was no evidence of POEMS syndrome in the patient; thus, we concluded the diagnosis as monoclonal gammopathy of clinical significance with osteosclerosis which was previously termed osteosclerotic multiple myeloma. CONCLUSION: Monoclonal gammopathy of clinical significance (MGCS) with osteosclerotic skeletal changes, documented on CT and multiple foci with intensive osteoneogenesis, documented on NaF-PET/CT without evidence of POEMS syndrome, is an extremely rare form of plasma cell dyscrasia. This publication documents the unique clinical manifestations of IgG-lambda type plasma cell proliferation without signs of POEMS syndrome and the role of NaF-PET/CT imaging. Classification of this disease as MGSC with osteosclerotic manifestations is more consistent with the indolent nature of the disease with a significantly better prognosis, compared with multiple myeloma.

18 F-FDG Uptake in Pancreatic AL Amyloidosis Associated With Multiple Myeloma.

ABSTRACT: A 60-year-old woman underwent whole-body contrast-enhanced CT because multiple myeloma was suspected. The contrast-enhanced CT showed pancreatic enlargement without main pancreatic duct dilatation and increased peripancreatic fat tissue. 18 F-FDG PET/CT demonstrated diffuse uptake in the enlargement of the pancreas, left and right ventricles, and vertebral column. Biopsy and bone marrow aspiration cytology revealed amyloid light-chain amyloidosis associated with multiple myeloma. Chemotherapy was performed; 18 F-FDG uptake in the pancreas then disappeared, and the pancreatic enlargement decreased. When diffuse 18 F-FDG uptake in pancreatic enlargement is observed in multiple myeloma patients, amyloid light-chain amyloidosis should be considered.

Isolated Abducens Nerve Palsy: A Rare Manifestation of Recurrent Extramedullary Myeloma.

Multiple myeloma is a plasma cell neoplasm, which may present as a solitary plasmacytoma and, uncommonly, as an extramedullary plasmacytoma. Intracranial plasmacytomas may manifest in central nervous system involvement as cranial nerve palsies. Cranial nerve six palsy is the most common in cases of malignancy. However, isolated abducens palsy presenting as multiple myeloma recurrence is very uncommon. Here, we detail two cases in which intracranial plasmacytoma lesions were present within the region of the Dorello canal, resulting in acute isolated unilateral diplopia from disease recurrence in the absence of systemic marrow involvement.

Value of third-generation of VNCa dual-energy CT for differentiating diffuse marrow infiltration of multiple myeloma from red bone marrow.

This study aims to investigate the ability of bone marrow imaging using third-generation dual-energy computed tomography (CT) virtual noncalcium (VNCa) to differentiate between multiple myeloma (MM) with diffuse bone marrow infiltration and red bone marrow (RBM). Bone marrow aspiration or follow-up results were used as reference. We retrospectively reviewed 188 regions of interests (ROIs) from 21 patients with confirmed MM and diffuse bone marrow infiltrations who underwent VNCa bone marrow imaging between May 2019 and September 2022. At the same time, we obtained 98 ROIs from 11 subjects with RBM for comparative study, and 189 ROIs from 20 subjects with normal yellow bone marrow for the control group. The ROIs were delineated by 2 radiologists independently, the interobservers reproducibility was evaluated by interclass correlation coefficients. The correlation with MRI grade results was analyzed by Spearman correlation coefficient. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal threshold for differentiating between these groups and to assess diagnostic performance. There were statistically significant differences in VNCa CT values of bone marrow among the MM, RBM, and control groups (all P < .001), with values decreasing sequentially. A strong positive rank correlation was observed between normal bone marrow, subgroup MM with moderately and severe bone marrow infiltration divided by MRI and their corresponding CT values (ρ = 0.897, 95%CI: 0.822 to 0.942, P < .001). When the CT value of VNCa bone marrow was 7.15 HU, the area under the curve (AUC) value for differentiating RBM and MM was 0.723, with a sensitivity of 50.5% and a specificity of 89.8%. When distinguishing severe bone marrow infiltration of MM from RBM, the AUC value was 0.80 with a sensitivity 70.9% and a specificity 78.9%. The AUC values for MM, RBM, and the combined group compared to the control group were all >0.99, with all diagnostic sensitivity and specificity exceeding 95%. VNCa bone marrow imaging using third-generation dual-energy CT accurately differentiates MM lesions from normal bone marrow or RBM. It demonstrates superior diagnostic performance in distinguishing RBM from MM with diffuse bone marrow infiltration.

Two-color diffuse in vivo flow cytometer.

Significance: Hematogenous metastasis is mediated by circulating tumor cells (CTCs) and CTC clusters (CTCCs). We recently developed "diffuse in vivo flow cytometry" (DiFC) to detect fluorescent protein (FP) expressing CTCs in small animals. Extending DiFC to allow detection of two FPs simultaneously would allow concurrent study of different CTC sub-populations or heterogeneous CTCCs in the same animal. Aim: The goal of this work was to develop and validate a two-color DiFC system capable of non-invasively detecting circulating cells expressing two distinct FPs. Approach: A DiFC instrument was designed and built to detect cells expressing either green FP (GFP) or tdTomato. We tested the instrument in tissue-mimicking flow phantoms in vitro and in multiple myeloma bearing mice in vivo. Results: In phantoms, we could accurately differentiate GFP+ and tdTomato+ CTCs and CTCCs. In tumor-bearing mice, CTC numbers expressing both FPs increased during disease. Most CTCCs (86.5%) expressed single FPs with the remainder both FPs. These data were supported by whole-body hyperspectral fluorescence cryo-imaging of the mice. Conclusions: We showed that two-color DiFC can detect two populations of CTCs and CTCCs concurrently. This instrument could allow study of tumor development and response to therapies for different sub-populations in the same animal.

Expanding Myeloma Training and Care in Western Kenya Through the ECHO Model: The Pilot Phase.

PURPOSE: Multiple myeloma (MM) in rural western Kenya is characterized by under and late diagnosis with poor long-term outcomes. Inadequate skilled rural health care teams are partly to blame. The Extension for Community Healthcare Outcomes (ECHO) model attempts to bridge this skills gap by linking rural primary/secondary health care teams (spokes) to myeloma experts in a tertiary care center (hub) in a longitudinal training program. METHODS: A hub team comprising myeloma experts and administrators from Moi Teaching and Referral Hospital/Academic Model Providing Access to Healthcare was assembled and spoke sites were recruited from rural health care facilities across western Kenya. A curriculum was developed by incorporating input from spokes on their perceived skills gaps in myeloma. Participants joined sessions remotely through virtual meeting technology. ECHO sessions consisted of a spoke-led case presentation with guided discussion followed by an expert-led lecture. An end-of-program survey was used to evaluate participant satisfaction, knowledge, and practice patterns. RESULTS: A total of eight sessions were conducted between April and November 2021 with a median of 40 attendees per session drawn from diverse health care disciplines. Twenty-four spoke sites were identified from 15 counties across western Kenya. The majority of attendees reported satisfaction with the ECHO program (25 of 29) and improvement in their myeloma knowledge (24 of 29). There were 74 new myeloma diagnoses made at the hub site in 2021, representing a 35% increase from the previous 3-year average despite the COVID-19 pandemic that suppressed health care access globally. RECOMMENDATIONS: The pilot ECHO model was successfully implemented in myeloma training for rural-based health care teams. Key attributes included collaborative curriculum development, interactive case-based bidirectional learning, and multidisciplinary engagement.

Diagnostic value of LGE and T1 mapping in multiple myeloma patients'heart.

BACKGROUND: Unidentified heart failure occurs in patients with multiple myeloma when their heart was involved. CMR with late gadolinium enhancement (LGE) and T1 mapping can identify myocardial amyloid infiltrations. PURPOSE: To explore the role of CMR with late gadolinium enhancement (LGE) and T1 mapping for detection of multiple myeloma patients'heart. MATERIAL AND METHODS: A total of 16 MM patients with above underwent CMR (3.0-T) with T1 mapping (pre-contrast and post-contrast) and LGE imaging. In addition, 26 patients with non-obstructive hypertrophic cardiomyopathy and 26 healthy volunteers were compared to age- and sex-matched healthy controls without a history of cardiac disease, diabetes mellitus, or normal in CMR. All statistical analyses were performed using the statistical software GraphPad Prism. The measurement data were represented by median (X) and single sample T test was adopted. Enumeration data were represented by examples and Chi-tested was adopted. All tests were two-sided, and P values < 0.05 were considered statistically significant. RESULTS: In MM group, LVEF was lower than healthy controls and higher than that of non-obstructive hypertrophic cardiomyopathy group, but without statistically significant difference (%: 49.1 ± 17.5 vs. 55.6 ± 10.3, 40.4 ± 15.6, all P > 0.05). Pre-contrast T1 values of MM group were obviously higher than those of healthy controls and non-obstructive hypertrophic cardiomyopathy group (ms:1462.0 ± 71.3vs. 1269.3 ± 42.3, 1324.0 ± 45.1, all P < 0.05). 16 cases (100%) in MM group all had LGE. CONCLUSION: LGE joint T1 mapping wider clinical use techniques and follow-up the patients'disease severity.

Chemokine Receptor 4-Targeted PET/CT With 68 Ga-Pentixather Detects More Lesions Than 68 Ga-Pentixafor PET/CT in Multiple Myeloma.

ABSTRACT: An 83-year-old woman with newly diagnosed multiple myeloma (MM) was enrolled in our 68 Ga-pentixather and 68 Ga-pentixafor PET/CT trial for evaluation of tumor burden. 68 Ga-pentixather PET/CT detected more focal bone lesions, and the uptake levels of focal bone lesions on 68 Ga-pentixather PET/CT were higher than those on 68 Ga-pentixafor PET/CT. This suggests that 68 Ga-pentixather PET/CT may be an alternative imaging modality and more sensitive in detecting MM lesions than 68 Ga-pentixafor PET/CT.

Simulation of cancer progression in bone by a virtual thermal flux with a case study on lumbar vertebrae with multiple myeloma.

BACKGROUND: Two main problems examining the mechanism of cancer progression in the tissues using the computational models are lack of enough knowledge on the effective factors for such events in vivo environments and lack of specific parameters in the available computational models to simulate such complicated reactions. METHODS: In this study, it was tried to simulate the progression of cancerous lesions in the bone tissues by an independent parameter from the anatomical and physiological characteristics of the tissues, so to degrade the orthotropic mechanical properties of the bone tissues, a virtual temperature was determined to be used by a well-known framework for simulation of damages in the composite materials. First, the reliability of the FE model to simulate hyperelastic response in the intervertebral discs (IVDs) and progressive failure in the bony components were verified by simulation of some In-Vitro tests, available in the literature. Then, the progression of the osteolytic damage was simulated in a clinical case with multiple myeloma in the lumbar vertebrae. RESULTS: The FE model could simulate stress-shielding and diffusion of lesion in the posterior elements of the damaged vertebra which led to spinal stenosis. The load carrying shares associated with the anterior half and the posterior half of the examined vertebral body and the posterior elements were estimated equal to 41 %, 47 % and 12 %, respectively for the intact condition, that changed to 14 %, 16 % and 70 %, when lesion occupied one third of the vertebral body. CONCLUSION: Correlation of the FE results with the deformation shapes, observed in the MRIs for the clinical case study, indicated appropriateness of the procedure, proposed for simulation of the progressive osteolytic damage in the vertebral segments. The future studies may follow simulation of tumor growth for various metastatic tissues using the method, established here.

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.

3D CNN-based Deep Learning Model-based Explanatory Prognostication in Patients with Multiple Myeloma using Whole-body MRI.

Although magnetic resonance imaging (MRI) data of patients with multiple myeloma (MM) are used to predict prognosis, few reports have applied artificial intelligence (AI) techniques for this purpose. We aimed to analyze whole-body diffusion-weighted MRI data using three-dimensional (3D) convolutional neural networks (CNNs) and Gradient-weighted Class Activation Mapping (Grad-CAM), an explainable AI, to predict prognosis and explore the factors involved in prediction. We retrospectively analyzed the MRI data of a total of 142 patients with MM obtained from two medical centers. We defined the occurrence of progressive disease after MRI evaluation within 12 months as a poor prognosis and constructed a 3D CNN-based deep learning model to predict prognosis. Images from 111 cases were used as the training and internal validation data; images from 31 cases were used as the external validation data. Internal validation of the AI model with stratified 5-fold cross-validation resulted in a significant difference in progression-free survival (PFS) between good and poor prognostic cases (2-year PFS, 91.2% versus [vs.] 61.1%, P = 0.0002). The AI model clearly stratified good and poor prognostic cases in the external validation cohort (2-year PFS, 92.9% vs. 55.6%, P = 0.004), with an area under the receiver operating characteristic curve of 0.804. According to Grad-CAM, the MRI signals of the spleen and bones of the vertebrae and pelvis contributed to prognosis prediction. This study is the first to show that image analysis of whole-body MRI using a 3D CNN without any other clinical data is effective in predicting the prognosis of patients with MM.

Construction and validation of an 18F-FDG-PET/CT-based prognostic model to predict progression-free survival in newly diagnosed multiple myeloma patients.

OBJECTIVE: To investigate the relationship between 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) related parameters and the prognosis of multiple myeloma and to establish and validate a prediction model regarding the progression-free survival (PFS) of multiple myeloma. METHODS: A retrospective analysis of 126 newly diagnosed multiple myeloma patients who attended Nanjing Drum Tower Hospital from 2014-2021. All patients underwent PET/CT before treatment and were divided into a training cohort (n = 75) and a validation cohort (n = 51). Multivariate Cox proportional hazard regression analysis incorporated PET/CT-related parameters and clinical indicators. A nomogram was established to individually predict PFS in MM patients. The model was evaluated by calculating the C-index and calibration curve. RESULTS: Here, 4.2 was used as the cut-off value of SUVmax to divide patients into high and low groups. PFS significantly differed between patients in the high-SUVmax group and low-SUVmax group, and SUVmax was an independent predictor of PFS in newly diagnosed multiple myeloma (NDMM) patients. Univariate and multivariate cox regression analysis suggested that lactate dehydrogenase (LDH), bone marrow plasma cell (BMPC), and SUVmax affected PFS. These factors were incorporated to construct a nomogram model for predicting PFS at 1 and 2 years in NDMM patients. The C-index and calibration curves of the nomogram exhibited good accuracy and consistency, and the DCA curves suggested that the model had good clinical utility. CONCLUSION: The PET/CT parameter SUVmax is closely related to the prognosis of myeloma patients. The nomogram constructed in this study based on PET/CT-related parameters and clinical indicators individually predicts the PFS rate of NDMM patients and enables further risk stratification of NDMM patients.

The quantitative parameters based on marrow metabolism derived from synthetic MRI: A pilot study of prognostic value in participants with newly diagnosed multiple myeloma.

BACKGROUND: The value of SyMRI-derived parameters from lumbar marrow for predicting early treatment response and optimizing the risk stratification of the Revised International Staging System (R-ISS) in participants with multiple myeloma (MM) is unknown. METHODS: We prospectively enrolled participants with newly diagnosed MM before treatment. The SyMRI of lumbar marrow was used to calculate T1, T2, and PD values and the clinical features were collected. All participants were divided into good response (≥VGPR) and poor response (

Development of a whole spinal MRI-based tumor burden scoring method in participants with multiple myeloma: a pilot study of prognostic significance.

The aim of the study was to develop a new whole spinal MRI-based tumor burden scoring method in participants with newly diagnosed multiple myeloma (MM) and to explore its prognostic significance. We prospectively recruited participants with newly diagnosed MM; performed whole spinal MRI (sagittal FSE T1WI, sagittal IDEAL T2WI, and axial FLAIR T2WI) on them; and collected their clinical data, early treatment response, progression-free survival (PFS), and overall survival (OS). We developed a new tumor burden scoring method according to the extent of bone marrow infiltration in five MRI patterns. All participants were divided into good response and poor response groups after four treatment cycles. Univariate, multivariate analyses, and ROC were used to determine the performance of independent predictors. Thresholds for PFS and OS were calculated using X-tile, and their prognostic significance were assessed by Kaplan-Meier. The Kruskal-Wallis H test was used to compare the differences of tumor burden score between the revised International Staging System (R-ISS) stages. The new tumor burden scoring method was used in 62 participants (median score, 12; range, 0-18). The tumor burden score (OR 1.266, p = 0.002) was an independent predictor of poor response and the AUC was 0.838. Higher tumor burden scores were associated with shorter PFS (p = 0.002) and OS (p = 0.011). The tumor burden score was higher in R-ISS-III than in R-ISS-I and R-ISS-II (p = 0.016 and p = 0.006, respectively). The tumor burden score was an excellent predictor of prognosis and may serve as a supplemental marker for R-ISS.

CD38-Specific Gallium-68 Labeled Peptide Radiotracer Enables Pharmacodynamic Monitoring in Multiple Myeloma with PET.

The limited availability of molecularly targeted low-molecular-weight imaging agents for monitoring multiple myeloma (MM)-targeted therapies has been a significant challenge in the field. In response, a first-in-class peptide-based radiotracer, [68Ga]Ga-AJ206, is developed that can be seamlessly integrated into the standard clinical workflow and is specifically designed to noninvasively quantify CD38 levels and pharmacodynamics by positron emission tomography (PET). A bicyclic peptide, AJ206, is synthesized and exhibits high affinity to CD38 (KD: 19.1 ± 0.99 × 10-9 m) by surface plasmon resonance. Further, [68Ga]Ga-AJ206-PET shows high contrast within 60 min and suitable absorbed dose estimates for clinical use. Additionally, [68Ga]Ga-AJ206 detects CD38 expression in cell line-derived xenografts, patient-derived xenografts (PDXs), and disseminated disease models in a manner consistent with flow cytometry and immunohistochemistry findings. Moreover, [68Ga]Ga-AJ206-PET successfully quantifies CD38 pharmacodynamics in PDXs, revealing increased CD38 expression in the tumor following all-trans retinoic acid (ATRA) therapy. In conclusion, [68Ga]Ga-AJ206 exhibits the salient features required for clinical translation, providing CD38-specific high-contrast images in multiple models of MM. [68Ga]Ga-AJ206-PET could be useful for quantifying total CD38 levels and pharmacodynamics during therapy to evaluate approved and new therapies in MM and other diseases with CD38 involvement.

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.

Positron Emission Tomography/Computed Tomography Transformation of Oncology: Multiple Myeloma.

This article provides a comprehensive review of the role of 2-deoxy-2-[18F]fluoro-d-glucose (18F FDG) positron emission tomography/computed tomography (PET/CT) in multiple myeloma (MM) and related plasma cell disorders. MM is a hematologic malignancy characterized by the neoplastic proliferation of plasma cells. 18F FDG PET/CT integrates metabolic and anatomic information, allowing for accurate localization of metabolically active disease. The article discusses the use of 18F FDG PET/CT in initial diagnosis, staging, prognostication, and assessing treatment response. Additionally, it provides valuable insights into the novel imaging targets including chemokine receptor C-X-C motif 4 and CD38.

MRI-based bone marrow radiomics for predicting cytogenetic abnormalities in multiple myeloma.

AIM: To develop a radiomics signature applied to magnetic resonance imaging (MRI)-images to predict cytogenetic abnormalities in multiple myeloma (MM). MATERIALS AND METHODS: Patients with newly diagnosed MM were enrolled retrospectively from March 2019 to September 2022. They were categorised into the high-risk cytogenetics (HRC) group and standard-risk cytogenetics (SRC) group. The patients were allocated randomly at a ratio of 7:3 into training and validation cohorts. Volumes of interest (VOI) was drawn manually on fat suppression T2-weighted imaging (FS-T2WI) and copied to the same location of the T1-weighted imaging (T1WI) sequence. Radiomics features were extracted from two sequences and selected by reproducibility and redundant analysis. The least absolute shrinkage selection operation (LASSO) algorithm was applied to build the radiomics signatures. The performance of the radiomics signatures to distinguish HRC with SRC was evaluated by ROC curves. The area under the curve (AUC), specificity, and sensitivity were also calculated. RESULTS: A total of 105 MM patients were enrolled in this study. The four and 11 most significant and relevant features were selected separately from T1WI and FS-T2WI sequences to build the radiomics signatures based on the training cohort. Compared to the T1WI sequence, the radiomics signature based on the FS-T2WI sequence achieved better performance with AUCs of 0.896 and 0.729 in the training and validation cohorts respectively. A sensitivity of 0.833, specificity of 0.667, and Youden index of 0.500 were achieved for the FS-T2WI radiomics signature in the validation cohort. CONCLUSIONS: The radiomics signature based on MRI provides a non-invasive and convenient tool to predict cytogenetic abnormalities in MM patients.

[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.