DCE-MRI to distinguish all monoclonal plasma cell disease stages and correlation with diffusion-weighted MRI/PET-based biomarkers in a hybrid simultaneous whole body-2-[18F]FDG-PET/MRI imaging approach.

BACKGROUND: Dynamic contrast-enhanced-MRI (DCE-MRI) is able to study bone marrow angiogenesis in patients with multiple myeloma (MM) and asymptomatic precursor diseases but its role in the management of MM has not yet been established. The aims of this prospective study was to compare DCE-MRI-based parameters between all monoclonal plasma cell disease stages in order to find out discriminatory parameters and to seek correlations with other diffusion-weighted MRI and positron emission tomography (PET)-based biomarkers in a hybrid simultaneous whole-body-2-[18F]fluorodeoxyglucose (FDG)-PET/MRI (WB-2-[18F]FDG-PET/MRI) imaging approach. METHODS: Patients with newly diagnosed Monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM) or symptomatic MM according to international myeloma working group and underwent WB-2-[18F]FDG-PET/MRI imaging including bone marrow DCE sequences at the Nantes University Hospital were prospectively enrolled in this study before receiving treatment. RESULTS: One hundred and sixty-seven patients (N = 167, mean age: 64 years ± 11 [Standard deviation], 66 males) were considered for the analysis. DCE-MRI-based Peak Enhancement Intensity (PEI), Time to PEI (TPEI) and their maximum intensity time ratio (MITR: PEI/TPEI) values were significantly different between the different monoclonal plasma cell disease stages, PEI values increasing and TPEI values decreasing progressively along the spectrum of plasma cell disorders, from MGUS stage to symptomatic multiple myeloma. PEI values were significantly higher in patients with diffuse bone marrow involvement (either in PET or in MRI images) than in those without diffuse bone marrow involvement, unlike TPEI values. PEI and TPEI values were not significantly different between patients with or without focal bone lesions. CONCLUSION: Different DCE-MRI-based parameters (PEI, TPEI, MITR) could significantly differentiate all monoclonal plasma cell disease stages and complemented conventional MRI and PET-based biomarkers.

Healthy tissue metabolism assessed by [18F]FDG PET/CT as a marker of prognosis and adverse events in advanced Hodgkin lymphoma patients.

The aim of the study was to assess healthy tissue metabolism (HTM) using 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) during chemotherapy in Hodgkin lymphoma (HL) and the association of HTM with baseline metabolic tumour volume (MTV), haematological parameters, adverse events (AEs), early response and progression-free survival (PFS). We retrospectively identified 200 patients with advanced HL from the RATHL trial with [18F]FDG-PET/CT before (PET0) and following 2 cycles of chemotherapy (PET2). [18F]FDG-uptake was measured in bone marrow (BM), spleen, liver and mediastinal blood pool (MBP). Deauville score (DS) 1-3 was used to classify responders and DS 4-5, non-responders. [18F]FDG-uptake decreased significantly in BM and spleen and increased in liver and MBP at PET2 (all p < 0.0001), but was not associated with MTV. Higher BM uptake at PET0 was associated with lower baseline haemoglobin and higher absolute neutrophil counts, platelets, and white blood cells. High BM, spleen, and liver uptake at PET0 was associated with neutropenia after cycles 1-2. BM uptake at PET0 was associated with treatment failure at PET2 and non-responders with higher BM uptake at PET2 had significantly inferior PFS (p = 0.023; hazard ratio = 2.31). Based on these results, we concluded that the change in HTM during chemotherapy was most likely a direct impact of chemotherapy rather than a change in MTV. BM uptake has prognostic value in HL.

Deep learning promoted target volumes delineation of total marrow and total lymphoid irradiation for accelerated radiotherapy: A multi-institutional study.

BACKGROUND AND PURPOSE: One of the current roadblocks to the widespread use of Total Marrow Irradiation (TMI) and Total Marrow and Lymphoid Irradiation (TMLI) is the challenging difficulties in tumor target contouring workflow. This study aims to develop a hybrid neural network model that promotes accurate, automatic, and rapid segmentation of multi-class clinical target volumes. MATERIALS AND METHODS: Patients who underwent TMI and TMLI from January 2018 to May 2022 were included. Two independent oncologists manually contoured eight target volumes for patients on CT images. A novel Dual-Encoder Alignment Network (DEA-Net) was developed and trained using 46 patients from one internal institution and independently evaluated on a total of 39 internal and external patients. Performance was evaluated on accuracy metrics and delineation time. RESULTS: The DEA-Net achieved a mean dice similarity coefficient of 90.1 % ± 1.8 % for internal testing dataset (23 patients) and 91.1 % ± 2.5 % for external testing dataset (16 patients). The 95 % Hausdorff distance and average symmetric surface distance were 2.04 ± 0.62 mm and 0.57 ± 0.11 mm for internal testing dataset, and 2.17 ± 0.68 mm, and 0.57 ± 0.20 mm for external testing dataset, respectively, outperforming most of existing state-of-the-art methods. In addition, the automatic segmentation workflow reduced delineation time by 98 % compared to the conventional manual contouring process (mean 173 ± 29 s vs. 12168 ± 1690 s; P < 0.001). Ablation study validate the effectiveness of hybrid structures. CONCLUSION: The proposed deep learning framework achieved comparable or superior target volume delineation accuracy, significantly accelerating the radiotherapy planning process.

Deep learning-based automated detection and segmentation of bone and traumatic bone marrow lesions from MRI following an acute ACL tear.

INTRODUCTION: Traumatic bone marrow lesions (BML) are frequently identified on knee MRI scans in patients following an acute full-thickness, complete ACL tear. BMLs coincide with regions of elevated localized bone loss, and studies suggest these may act as a precursor to the development of post-traumatic osteoarthritis. This study addresses the labour-intensive manual assessment of BMLs by using a 3D U-Net for automated identification and segmentation from MRI scans. METHODS: A multi-task learning approach was used to segment both bone and BML from T2 fat-suppressed (FS) fast spin echo (FSE) MRI sequences for BML assessment. Training and testing utilized datasets from individuals with complete ACL tears, employing a five-fold cross-validation approach and pre-processing involved image intensity normalization and data augmentation. A post-processing algorithm was developed to improve segmentation and remove outliers. Training and testing datasets were acquired from different studies with similar imaging protocol to assess the model's performance robustness across different populations and acquisition conditions. RESULTS: The 3D U-Net model exhibited effectiveness in semantic segmentation, while post-processing enhanced segmentation accuracy and precision through morphological operations. The trained model with post-processing achieved a Dice similarity coefficient (DSC) of 0.75 ± 0.08 (mean ± std) and a precision of 0.87 ± 0.07 for BML segmentation on testing data. Additionally, the trained model with post-processing achieved a DSC of 0.93 ± 0.02 and a precision of 0.92 ± 0.02 for bone segmentation on testing data. This demonstrates the approach's high accuracy for capturing true positives and effectively minimizing false positives in the identification and segmentation of bone structures. CONCLUSION: Automated segmentation methods are a valuable tool for clinicians and researchers, streamlining the assessment of BMLs and allowing for longitudinal assessments. This study presents a model with promising clinical efficacy and provides a quantitative approach for bone-related pathology research and diagnostics.

Deep learning-based quantification of osteonecrosis using magnetic resonance images in Gaucher disease.

Gaucher disease is one of the most common lysosomal storage disorders. Osteonecrosis is a principal clinical manifestation of Gaucher disease and often leads to joint collapse and fractures. T1-weighted (T1w) modality in MRI is widely used to monitor bone involvement in Gaucher disease and to diagnose osteonecrosis. However, objective and quantitative methods for characterizing osteonecrosis are still limited. In this work, we present a deep learning-based quantification approach for the segmentation of osteonecrosis and the extraction of characteristic parameters. We first constructed two independent U-net models to segment the osteonecrosis and bone marrow unaffected by osteonecrosis (UBM) in spine and femur respectively, based on T1w images from patients in the UK national Gaucherite study database. We manually delineated parcellation maps including osteonecrosis and UBM from 364 T1w images (176 for spine, 188 for femur) as the training datasets, and the trained models were subsequently applied to all the 917 T1w images in the database. To quantify the segmentation, we calculated morphological parameters including the volume of osteonecrosis, the volume of UBM, and the fraction of total marrow occupied by osteonecrosis. Then, we examined the correlation between calculated features and the bone marrow burden score for marrow infiltration of the corresponding image, and no strong correlation was found. In addition, we analyzed the influence of splenectomy and the interval between the age at first symptom and the age of onset of treatment on the quantitative measurements of osteonecrosis. The results are consistent with previous studies, showing that prior splenectomy is closely associated with the fractional volume of osteonecrosis, and there is a positive relationship between the duration of untreated disease and the quantifications of osteonecrosis. We propose this technique as an efficient and reliable tool for assessing the extent of osteonecrosis in MR images of patients and improving prediction of clinically important adverse events.

Feasibility of identifying proliferative active bone marrow with fat fraction MRI and multi-energy CT.

Objective.Active bone marrow (ABM) can serve as both an organ at risk and a target in external beam radiotherapy.18F-fluorothymidine (FLT) PET is the current gold standard for identifying proliferative ABM but it is not approved for human use, and PET scanners are not always available to radiotherapy clinics. Identifying ABM through other, more accessible imaging modalities will allow more patients to receive treatment specific to their ABM distribution. Multi-energy CT (MECT) and fat-fraction MRI (FFMRI) show promise in their ability to characterize bone marrow adiposity, but these methods require validation for identifying proliferative ABM.Approach.Six swine subjects were imaged using FFMRI, fast-kVp switching (FKS) MECT and sequential-scanning (SS) MECT to identify ABM volumes relative to FLT PET-derived ABM volumes. ABM was contoured on FLT PET images as the region within the bone marrow with a SUV above the mean. Bone marrow was then contoured on the FFMRI and MECT images, and thresholds were applied within these contours to determine which threshold produced the best agreement with the FLT PET determined ABM contour. Agreement between contours was measured using the Dice similarity coefficient (DSC).Main results.FFMRI produced the best estimate of the PET ABM contour. Compared to FLT PET ABM volumes, the FFMRI, SS MECT and FKS MECT ABM contours produced average peak DSC of 0.722 ± 0.080, 0.619 ± 0.070, and 0.464 ± 0.080, respectively. The ABM volume was overestimated by 40.51%, 97.63%, and 140.13% by FFMRI, SS MECT and FKS MECT, respectively.Significance.This study explored the ability of FFMRI and MECT to identify the proliferative relative to ABM defined by FLT PET. Of the methods investigated, FFMRI emerged as the most accurate approximation to FLT PET-derived active marrow contour, demonstrating superior performance by both DSC and volume comparison metrics. Both FFMRI and SS MECT show promise for providing patient-specific ABM treatments.

Bone marrow lesion and 5-year incident joint surgery in patients with knee osteoarthritis: a retrospective cohort study.

BACKGROUND: It is beneficial for society to discover the risk factors associated with surgery and to carry out some early interventions for patients with these risk factors. Few studies specifically explored the relationship between bone marrow lesions (BMLs) and long-term incident joint surgery. OBJECTIVE: To investigate the association between BML severity observed in knee osteoarthritis (OA) patients' first MRI examination and incident knee surgery within 5 years. Additionally, to assess the predictive value of BMLs for the incident knee surgery. DESIGN: Retrospective cohort study. METHODS: We identified patients diagnosed with knee OA and treated at our institution between January 2015 and January 2018, and retrieved their baseline clinical data and first MRI examination films from the information system. Next, we proceeded to determine the Max BML grades, BML burden grades and Presence BML grades for the medial, lateral, patellofemoral, and total compartments, respectively. Multi-variable logistic regression models examined the association of the BML grades with 5-year incident knee surgery. Positive and negative predictive values (PPVs and NPVs) were determined for BML grades referring to 5-year incident knee surgery. RESULTS: Totally, 1011 participants (knees) were found eligible to form the study population. Within the 5 years, surgery was performed on 74 knees. Max BML grade 2 and grade 3 of medial, patellofemoral and total compartments were strongly and significantly associated with incident surgery. None of the BML grades from lateral compartment was associated with incident surgery. The PPV was low and NPV was high for BMLs. CONCLUSIONS: BMLs found in the first MRI examination were associated with 5-year incident joint surgery, except for those allocated in lateral compartments. The high NPVs imply that patients without BMLs have a low risk of requiring surgery within 5 years.

Associations of marrow fat fraction with MR imaging based trabecular bone microarchitecture in first-time diagnosed type 1 diabetes mellitus.

Purpose: To determine whether there are alterations in marrow fat content in individuals first-time diagnosed with type 1 diabetes mellitus (T1DM) and to explore the associations between marrow fat fraction and MRI-based findings in trabecular bone microarchitecture. Method: A case-control study was conducted, involving adults with first-time diagnosed T1DM (n=35) and age- and sex-matched healthy adults (n=46). Dual-energy X-ray absorptiometry and 3 Tesla-MRI of the proximal tibia were performed to assess trabecular microarchitecture and vertebral marrow fat fraction. Multiple linear regression analysis was used to test the associations of marrow fat fraction with trabecular microarchitecture and bone density while adjusting for potential confounding factors. Results: In individuals first-time diagnosed with T1DM, the marrow fat fraction was significantly higher (p < 0.001) compared to healthy controls. T1DM patients also exhibited higher trabecular separation [median (IQR): 2.19 (1.70, 2.68) vs 1.81 (1.62, 2.10), p < 0.001], lower trabecular volume [0.45 (0.30, 0.56) vs 0.53 (0.38, 0.60), p = 0.013], and lower trabecular number [0.37 (0.26, 0.44) vs 0.41 (0.32, 0.47), p = 0.020] compared to controls. However, bone density was similar between the two groups (p = 0.815). In individuals with T1DM, there was an inverse association between marrow fat fraction and trabecular volume (r = -0.69, p < 0.001) as well as trabecular number (r = -0.55, p < 0.001), and a positive association with trabecular separation (r = 0.75, p < 0.001). Marrow fat fraction was independently associated with total trabecular volume (standardized ß = -0.21), trabecular number (ß = -0.12), and trabecular separation (ß = 0.57) of the proximal tibia after adjusting for various factors including age, gender, body mass index, physical activity, smoking status, alcohol consumption, blood glucose, plasma glycated hemoglobin, lipid profile, and bone turnover biomarkers. Conclusions: Individuals first-time diagnosed with T1DM experience expansion of marrow adiposity, and elevated marrow fat content is associated with MRI-based trabecular microstructure.

Relationship between Femoral Proximal Bone Quality Assessment by MRI IDEAL-IQ Sequence and Body Mass Index in Elderly Men.

BACKGROUND: Bone assessment using the MRI DEAL-IQ sequence may have the potential to serve as a substitute for evaluating bone strength by quantifying the bone marrow hematopoietic region (R2*) and marrow adiposity (proton density fat fraction: PDFF). Higher body mass index (BMI) is associated with increased bone mineral density (BMD) in the proximal femur; however, the relationship between BMI and R2* or PDFF remains unclear. Herein, we investigated the correlation between BMI and MRI IDEAL-IQ based R2* or PDFF of the proximal femur. METHODS: A retrospective single-cohort study was conducted on 217 patients diagnosed with non-metastatic prostate cancer between September 2019 and December 2022 who underwent MRI. The correlation between BMI and R2* or PDFF of the proximal femur was analyzed using Spearman's rank correlation test. RESULTS: Among 217 patients (median age, 74 years; median BMI, 23.8 kg/m2), there was a significant positive correlation between BMI and R2* at the right and left proximal femur (r = 0.2686, p < 0.0001; r = 0.2755, p < 0.0001, respectively). Furthermore, BMI and PDFF showed a significant negative correlation (r = -0.239, p = 0.0004; r = -0.2212, p = 0.001, respectively). CONCLUSION: In elderly men, the increased loading on the proximal femur due to elevated BMI was observed to promote a decrease in bone marrow adiposity in the proximal femur, causing a tendency for a transition from fatty marrow to red marrow with hematopoietic activity. These results indicate that the MRI IDEAL-IQ sequence may be valuable for assessing bone quality deterioration in the proximal femur.

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.

W-DRAG: A joint framework of WGAN with data random augmentation optimized for generative networks for bone marrow edema detection in dual energy CT.

Dual-energy computed tomography (CT) is an excellent substitute for identifying bone marrow edema in magnetic resonance imaging. However, it is rarely used in practice owing to its low contrast. To overcome this problem, we constructed a framework based on deep learning techniques to screen for diseases using axial bone images and to identify the local positions of bone lesions. To address the limited availability of labeled samples, we developed a new generative adversarial network (GAN) that extends expressions beyond conventional augmentation (CA) methods based on geometric transformations. We theoretically and experimentally determined that combining the concepts of data augmentation optimized for GAN training (DAG) and Wasserstein GAN yields a considerably stable generation of synthetic images and effectively aligns their distribution with that of real images, thereby achieving a high degree of similarity. The classification model was trained using real and synthetic samples. Consequently, the GAN technique used in the diagnostic test had an improved F1 score of approximately 7.8% compared with CA. The final F1 score was 80.24%, and the recall and precision were 84.3% and 88.7%, respectively. The results obtained using the augmented samples outperformed those obtained using pure real samples without augmentation. In addition, we adopted explainable AI techniques that leverage a class activation map (CAM) and principal component analysis to facilitate visual analysis of the network's results. The framework was designed to suggest an attention map and scattering plot to visually explain the disease predictions of the network.

Dose-Volume Parameters of Spared Magnetic Resonance Imaging-Defined Active Bone Marrow Predict Hematologic Toxicity in Pelvic Malignancies Patients Undergoing Radiotherapy: A Cohort Study.

Background: The objective of this investigation is to evaluate the superiority of dose-volume parameters relying on magnetic resonance imaging (MRI)-defined active bone marrow (ABM) over those based on total bone marrow (TBM) contoured via CT in the prediction of hematologic toxicity (HT) occurrence among patients with pelvic malignancies undergoing radiotherapy. Methods: The clinical data of 116 patients with pelvic malignancies treated with pelvic radiotherapy were analyzed retrospectively. The ABM areas on T1-weighted MRI were contoured. The statistical significance between TBM and ABM dose-volume measures was assessed through the utilization of either Student's t-test or Wilcoxon signed rank test. Logistic and linear regression models were employed to analyze the correlation between dose-volume parameters (V5-V50) and HT occurrence in pelvic ABM and TBM. Receiver operating characteristic (ROC) curves were used to compare predictors of HT2+. Results: There were significant differences in dosimetric parameters between ABM and TBM. Logistic regression analysis showed that ABM V5, ABM V10, ABM V15, ABM V20, and TBM V5 were significantly associated with the occurrence of HT2+ in pelvic malignancies. Linear regression analysis showed that ABM V5, ABM V10, and ABM V15 were significantly associated with white blood cell (WBC), absolute neutrophil count (ANC), hemoglobin (Hb), and lymphocyte (Lym) nadir. ABM V5, ABM V10, ABM V15, and ABM V30 were predictive of HT2+. Conclusions: More accurate prediction of HT in patients receiving pelvic radiotherapy may be achieved by relying on dose-volume parameters of MRI-based ABM. Further prospective studies are needed to confirm this.

Age and BMI have different effects on subcutaneous, visceral, liver, bone marrow, and muscle adiposity, as measured by CT and MRI.

OBJECTIVE: We analyzed quantitative computed tomography (CT) and chemical shift-encoded magnetic resonance imaging (MRI) data from a Chinese cohort to investigate the effects of BMI and aging on different adipose tissue (AT) depots. METHODS: In 400 healthy, community-dwelling individuals aged 22 to 83 years, we used MRI to quantify proton density fat fraction (PDFF) of the lumbar spine (L2-L4) bone marrow AT (BMAT), the psoas major and erector spinae (ES) muscles, and the liver. Abdominal total AT, visceral AT (VAT), and subcutaneous AT (SAT) areas were measured at the L2-L3 level using quantitative CT. Partial correlation analysis was used to evaluate the relationship of each AT variable with age and BMI. Multiple linear regression analysis was performed in which each AT variable was evaluated in turn as a function of age and the other five independent AT measurements. RESULTS: Of the 168 men, 29% had normal BMI (<24.0 kg/m2), 47% had overweight (24.0-27.9 kg/m2), and 24% had obesity (≥ 28.0 kg/m2). In the 232 women, the percentages were 46%, 32%, and 22%, respectively. Strong or very strong correlations with BMI were found for total AT, VAT, and SAT in both sexes. BMAT and ES PDFF was strongly correlated with age in women and moderately correlated in men. In both sexes, BMAT PDFF correlated only with age and not with any of the other AT depots. Psoas PDFF correlated only with ES PDFF and not with age or the other AT depots. Liver PDFF correlated with BMI and VAT and weakly with SAT in men. VAT and SAT correlated with age and each other in both sexes. CONCLUSIONS: Age and BMI are both associated with adiposity, but their effects differ depending on the type of AT.

Diagnosis of bone marrow involvement in angioimmunoblastic T-cell lymphoma should be based on both [18F]FDG-PET/CT and bone marrow biopsy findings.

OBJECTIVE: During the initial staging of certain lymphoma subtypes, 18 F-fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG-PET/CT) has become an alternative to bone marrow biopsy (BMB) for detecting bone marrow (BM) involvement. However, whether [18F]FDG-PET/CT can accurately detect BM involvement in angioimmunoblastic T-cell lymphoma (AITL) remains unknown. Our study aimed to assess the diagnostic and prognostic capability of [18F]FDG-PET/CT for detecting BM involvement in AITL. Methods: This retrospective study included 84 individuals newly diagnosed with AITL who underwent baseline BMB and [18F]FDG-PET/CT. "BM involvement" was defined as one or both of the following: 1) angioimmunoblastic T-cells detected in the BM; or 2) initially heightened focal uptake having disappeared on follow-up [18F]FDG-PET/CT. The ability of [18F]FDG-PET/CT to detect BM cancerous lesions was respectively analyzed by BM involvement confirmed by BMB or the aforementioned definition as the reference standard. The patients' clinical characteristics and survival and prognostic outcomes were respectively analyzed. RESULTS: Of the 84 participants, five (6.0%) displayed positive BMB and PET/BM results, 17 (20.2%) had BMB-positive but PET/BM-negative results, eight (9.5%) showed BMB-negative but PET/BM-positive outcomes, and 54 (64.3%) displayed negative BMB and PET/BM outcomes. Using pre-defined BM involvement as the reference standard, [18F]FDG-PET/CT exhibited a specificity of 100%, sensitivity of 40%, negative predictive value (NPV) of 75%, and positive predictive value (PPV) of 100%. In contrast, using BMB-detected BM involvement as reference, [18F]FDG-PET/CT exhibited a sensitivity, specificity, PPV, and NPV of 38.5%, 76.1%, 22.7%, and 87.1%, respectively. Among patients with PET/BM-positive and BMB-negative outcomes, 62.5% (5/8) underwent upstaging from III to IV. In 58.8% (10/17) of patients who were initially diagnosed with stage II/III disease based on the [18F]FDG-PET/CT results, repeat BMB resulted in upstaging to IV. PET/BM-negative patients had a higher 3-year progression-free survival rate (38.3% vs. 22.8%, p = 0.018) and 3-year overall survival rate (64.4% vs. 34.6%, p = 0.011) than PET/BM-positive patients. CONCLUSION: In AITL patients, PET/BM-positive results may obviate the necessity for repeat BMB to ascertain confirm BM involvement. PET/BM-negative results do not definitively exclude BM involvement. The combined use of [18F]FDG-PET/CT and BMB can increase the diagnostic accuracy of BM involvement for AITL patients.

Chemical shift-encoded MRI with compressed sensing combined with parallel imaging for proton density fat fraction measurement of the lumbar vertebral bone marrow.

We aimed to investigate the accuracy of proton density fat fraction (PDFF) measurement of the lumbar vertebral bone marrow using chemical shift-encoded magnetic resonance imaging (CSE-MRI) with compressed sensing combined with parallel imaging (CSPI). This study recruited a commercially available phantom, and 43 patients. Fully sampled data without CSPI and under-sampled data with CSPI acceleration factors of 2.4, 3.6, and 4.8 were acquired using a 1.5T imaging system. The relationships between PDFF measurements obtained with the no-CSPI acquisition and those obtained with each CSPI acquisition were assessed using Pearson correlation coefficient (r), linear regression analyses, and Bland-Altman analysis. The intra- and inter-observer variabilities of the PDFF measurements were evaluated using the intraclass correlation coefficient. PDFF measurements obtained with all acquisitions showed a significant correlation and strong agreement with the reference PDFF measurement of the phantom. PDFF measurements obtained using CSE-MRI with and without CSPI were positively correlated (all acquisitions: r = 0.99; P < .001). The mean bias was -0.31% to -0.17% with 95% limits of agreement within ±2.02%. The intra- and inter-observer agreements were excellent (intraclass correlation coefficient: 0.988 and 0.981, respectively). A strong agreement and positive correlation were observed between the PDFF measurements obtained using CSE-MRI with and without CSPI. PDFF measurement of the lumbar vertebral bone marrow using CSE-MRI with CSPI can be acquired with a maximum reduction of approximately 75% in the acquisition time compared with a fully sampled acquisition.

[The Value of Baseline PET/CT Imaging of Bone Marrow 18F-FDG Uptake Pattern in Predicting Prognosis of DLBCL].

OBJECTIVE: To investigate the prognostic value of bone marrow uptake pattern in 18F-deoxyglucose (18F-FDG) PET/CT imaging before diffuse large B-cell lymphoma (DLBCL) treatment. METHODS: The clinical data of 156 patients with DLBCL were retrospectively analyzed. All patients underwent bone marrow biopsy, bone marrow smear, flow cytometry and 18F-FDG PET/CT scan before treatment. Taking normal liver 18F-FDG uptake as the standard, the bone marrow uptake patterns of patients were divided into three types: focal increased bone marrow uptake (fPET+), diffusely increased bone marrow uptake (dPET+), and normal bone marrow uptake (nPET). Survival analysis was performed using the Kaplan-Meier method, log-rank test was used for comparison of differences between groups, and multivariate Cox regression analysis was used to identify risk factors associated with prognosis. RESULTS: Among the 156 patients, 17 cases were fPET+, 28 cases were dPET+, and 111 cases were nPET. Clinical diagnosis of bone marrow infiltration (BMI) was positive in 21 cases and negative in 135 cases. There were 62 cases of recurrence and progression, and 18 cases of death. Univariate analysis showed that Ann Arbor stage III/IV, B symptoms, NCCN-IPI score, lactate dehydrogenase (LDH), BMI+ and fPET+ were associated with progression-free survival (PFS) (all P < 0.05), while Ann Arbor stage III/IV, NCCN-IPI score, LDH, BMI+ and fPET+ were associated with overall survival (OS) (all P < 0.05). Multivariate analysis showed that Ann Arbor stage III/IV, LDH and fPET+ were independent predictors of PFS (all P < 0.05). There were no independent predictors of OS in multivariate analysis. CONCLUSION: The bone marrow uptake pattern of 18F-FDG imaging in DLBCL patients before treatment has a predictive value for DLBCL, while fPET+ is an independent risk factor for PFS.

Recurrent Marginal Zone Lymphoma with Bone Marrow Involvement Detected by ¹8F-FDG PET/CT and Biopsy: A Diagnostic Challenge.

BACKGROUND Marginal zone lymphoma is a low-grade, B-cell, non-Hodgkin lymphoma. Bone marrow involvement (BMI) of leukemia or lymphoma can usually be displayed in fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (¹8F-FDG PET/CT) with high standardized uptake values (SUV), while diffuse homogeneous ¹8F-FDG bone marrow uptake (BMU) in PET/CT primarily reflects hyperplastic bone marrow status. This report is of a 74-year-old man presenting with anemia and a diagnosis of recurrent marginal zone lymphoma with bone marrow involvement identified with 18F-FDG PET/CT imaging and biopsy. CASE REPORT A 64-year-old man with severe anemia and body weight loss of 7 kg in 1 month was diagnosed with marginal zone lymphoma, stage III, in July 2011. He went into complete remission in April 2012 after 6 cycles of chemotherapy, with Hb restored. Anemia and diffuse homogeneous ¹8F-FDG BMU in PET/CT were then noted during a routine check-up in October 2021, and recurrent disease was established through positive biopsy of subcutaneous nodules and bone marrow. Subsequent complete remission after 6 cycles of combination therapy was validated with pathologically negative BMI, the resolution of the slightly enhanced ¹8F-FDG BMU in PET/CT, and restored hemoglobin. CONCLUSIONS This report has highlighted the importance of follow-up for patients with lymphoma and supports the diagnostic role of ¹8F-FDG PET/CT imaging and the pathological verification in identifying malignant involvement in bone marrow.

Prediction of the activity of early ankylosing spondylitis using radiomics texture analysis on short tau inversion recovery (STIR).

OBJECTIVES: The study aimed to explore the value of texture analysis of radiomics based on the short tau inversion recovery (STIR) sequence to evaluate the activity of bone marrow oedema of sacroiliac joints in early AS. METHODS: 43 patients with early AS whose data were randomly divided into the training cohort (n=116) and verification cohort (n=56) according to the ratio of 7:3. The optimal feature subsets were obtained by Mann-Whitney U-test, the minimum-Redundancy Maximum-Relevancy (mRMR), and then least absolute shrinkage and selection operator (LASSO) using these texture feature parameters, which were used to construct the final prediction model and obtained the Radscore. The ROC curve was performed to evaluate the performance of the model. The Spearman correlation test was used to analyse the correlation of various indicators. RESULTS: In the training cohort, to differentiate early AS sacroiliac joint bone marrow oedema between the active and stable groups, the AUCs of the Radscore, SPARCC and ADC were 0.81, 0.91, 0.78, respectively. In the validation cohort, the AUCs were 0.87, 0.89, 0.85. In the two cohorts, there were no significant differences in AUCs between values of the Radscore and SPARCC, ADC (p>0.05). There was a significant difference in AUC between SPARCC and ADC in the training cohort (p<0.05), with no statistical significance in the validation cohort (p>0.05). The correlations were all low between the Radscore values and the values of ESR, CRP, tI, ASDAS-ESR and ASDAS-CRP (p<0.05). CONCLUSIONS: Radiomics analysis based on STIR texture analysis has a good prediction for the evaluation of bone marrow oedema activity of sacroiliac joints in AS. It can be a new non-invasive and objective evaluation method for AS activity.

SPECT/CT Image-Derived Absorbed Dose to Red Marrow Correlates with Hematologic Toxicity in Patients Treated with [177Lu]Lu-DOTATATE.

Hematologic toxicity, although often transient, is the most common limiting adverse effect during somatostatin peptide receptor radionuclide therapy. This study investigated the association between Monte Carlo-derived absorbed dose to the red marrow (RM) and hematologic toxicity in patients being treated for their neuroendocrine tumors. Methods: Twenty patients each receiving 4 treatment cycles of [177Lu]Lu-DOTATATE were included. Multiple-time-point 177Lu SPECT/CT imaging-based RM dosimetry was performed using an artificial intelligence-driven workflow to segment vertebral spongiosa within the field of view (FOV). This workflow was coupled with an in-house macroscale/microscale Monte Carlo code that incorporates a spongiosa microstructure model. Absorbed dose estimates to RM in lumbar and thoracic vertebrae within the FOV, considered as representations of the whole-body RM absorbed dose, were correlated with hematologic toxicity markers at about 8 wk after each cycle and at 3- and 6-mo follow-up after completion of all cycles. Results: The median of absorbed dose to RM in lumbar and thoracic vertebrae within the FOV (D median,vertebrae) ranged from 0.019 to 0.11 Gy/GBq. The median of cumulative absorbed dose across all 4 cycles was 1.3 Gy (range, 0.6-2.5 Gy). Hematologic toxicity was generally mild, with no grade 2 or higher toxicity for platelets, neutrophils, or hemoglobin. However, there was a decline in blood counts over time, with a fractional value relative to baseline at 6 mo of 74%, 97%, 57%, and 97%, for platelets, neutrophils, lymphocytes, and hemoglobin, respectively. Statistically significant correlations were found between a subset of hematologic toxicity markers and RM absorbed doses, both during treatment and at 3- and 6-mo follow-up. This included a correlation between the platelet count relative to baseline at 6-mo follow up: D median,vertebrae (r = -0.64, P = 0.015), D median,lumbar (r = -0.72, P = 0.0038), D median,thoracic (r = -0.58, P = 0.029), and D average,vertebrae (r = -0.66, P = 0.010), where D median,lumbar and D median,thoracic are median absorbed dose to the RM in the lumbar and thoracic vertebrae, respectively, within the FOV and D average,vertebrae is the mass-weighted average absorbed dose of all vertebrae. Conclusion: This study found a significant correlation between image-derived absorbed dose to the RM and hematologic toxicity, including a relative reduction of platelets at 6-mo follow up. These findings indicate that absorbed dose to the RM can potentially be used to understand and manage hematologic toxicity in peptide receptor radionuclide therapy.

Pictorial review: challenges in distinguishing bilateral metaphyseal marrow abnormalities on magnetic resonance imaging.

The paediatric metaphysis is afflicted by a wide range of pathological processes as it is the most metabolically active and well-vascularised part of the developing skeleton. This review focuses on metaphyseal marrow signal change detected with magnetic resonance imaging, which is most often occult on radiographs. When bilateral, these imaging appearances frequently present a diagnostic quandary. This review assists the radiologist to confidently dismiss physiological signal change and confidently work through the differential diagnosis. This is achieved by illustrating a practical method of classifying signal change into four categories: physiological red marrow, red marrow reconversion, marrow infiltration, and oedema-like marrow signal intensity. In doing so, various pathological entities are reviewed along with imaging pearls and next-step investigations.