[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.

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 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 (

Comparative analysis of bone turnover markers in bone marrow and peripheral blood: implications for osteoporosis.

INTRODUCTION: This study examines bone turnover marker (BTM) variations between bone marrow and peripheral blood in osteoporotic and non-osteoporotic patients. BTMs offer insights into bone remodeling, crucial for understanding osteoporosis. METHODS: A total of 133 patients were categorized into osteoporotic and non-osteoporotic cohorts. BTMs-C-telopeptide cross-linked type 1 collagen (ß-CTX), serum osteocalcin (OC), Procollagen type I N-propeptide (P1NP), 25(OH)D-were measured in bone marrow and peripheral blood. Lumbar spine bone mineral density (BMD) was assessed. RESULTS: Osteoporotic patients exhibited elevated ß-CTX and OC levels in peripheral blood, indicating heightened bone resorption and turnover. ß-CTX levels in osteoporotic bone marrow were significantly higher. Negative correlations were found between peripheral blood ß-CTX and OC levels and lumbar spine BMD, suggesting their potential as osteoporosis severity indicators. No such correlations were observed with bone marrow markers. When analyzing postmenopausal women separately, we obtained consistent results. CONCLUSIONS: Elevated ß-CTX and OC levels in osteoporotic peripheral blood highlight their diagnostic significance. Negative ß-CTX and OC-BMD correlations underscore their potential for assessing osteoporosis severity. Discrepancies between peripheral blood and bone marrow markers emphasize the need for further exploration. This research advances our understanding of BTM clinical applications in osteoporosis diagnosis and treatment.

Pre-treatment [18F]FDG PET/CT for assessing bone marrow involvement and prognosis in patients with newly diagnosed peripheral T-cell lymphoma.

PURPOSE: To explore the value of [18F]fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) in assessing bone marrow involvement (BMI) and prognosis in newly diagnosed peripheral T-cell lymphomas (PTCLs) before treatment. METHODS: This retrospective study included 201 eligible PTCLs who received pre-bone marrow biopsy (BMB) and PET/CT. The status of bone marrow (BM) by PET was assessed using a visual examination and a quantitative index (the maximal standardized uptake value [SUVmax] of BM divided by the SUVmax of the liver [M/L]). RESULTS: Totally 148 patients had no evidence of BMI by PET or BMB; BMI was detected by both methods in 16 patients. The sensitivity and specificity of PET/CT for patients with confirmed BMI by BMB were 43.2% and 90.2%, respectively (κ = 0.353). In addition, 25 patients assessed by PET/CT staging (having stage I to II disease) had no evidence of BMI detected by both PET/CT and BMB. Image-guided biopsy was also recommended when PET/CT showed a focal FDG uptake outside the iliac crest. Survival analysis revealed that BMB was significant for overall survival (OS) (P = 0.020) while M/L for both progression free survival (P = 0.002) and OS (P < 0.001). In multivariate analysis, M/L (HR 1.825, 95% CI 1.071-3.110, P = 0.027) was an independent prognostic factor for OS. There were no statistical differences at the genetic level about BMI confirmed by PET or BMB. CONCLUSION: PET/CT has a complementary role in assessing BMI and an ability to predict prognosis in PTCL patients.

Assessment of lymph node area coverage with total marrow irradiation and implementation of total marrow and lymphoid irradiation using automated deep learning-based segmentation.

BACKGROUND: Total marrow irradiation (TMI) and total marrow and lymphoid irradiation (TMLI) have the advantages. However, delineating target lesions according to TMI and TMLI plans is labor-intensive and time-consuming. In addition, although the delineation of target lesions between TMI and TMLI differs, the clinical distinction is not clear, and the lymph node (LN) area coverage during TMI remains uncertain. Accordingly, this study calculates the LN area coverage according to the TMI plan. Further, a deep learning-based model for delineating LN areas is trained and evaluated. METHODS: Whole-body regional LN areas were manually contoured in patients treated according to a TMI plan. The dose coverage of the delineated LN areas in the TMI plan was estimated. To train the deep learning model for automatic segmentation, additional whole-body computed tomography data were obtained from other patients. The patients and data were divided into training/validation and test groups and models were developed using the "nnU-NET" framework. The trained models were evaluated using Dice similarity coefficient (DSC), precision, recall, and Hausdorff distance 95 (HD95). The time required to contour and trim predicted results manually using the deep learning model was measured and compared. RESULTS: The dose coverage for LN areas by TMI plan had V100% (the percentage of volume receiving 100% of the prescribed dose), V95%, and V90% median values of 46.0%, 62.1%, and 73.5%, respectively. The lowest V100% values were identified in the inguinal (14.7%), external iliac (21.8%), and para-aortic (42.8%) LNs. The median values of DSC, precision, recall, and HD95 of the trained model were 0.79, 0.83, 0.76, and 2.63, respectively. The time for manual contouring and simply modified predicted contouring were statistically significantly different. CONCLUSIONS: The dose coverage in the inguinal, external iliac, and para-aortic LN areas was suboptimal when treatment is administered according to the TMI plan. This research demonstrates that the automatic delineation of LN areas using deep learning can facilitate the implementation of TMLI.

Evaluation of bone marrow invasion on the machine learning of 18 F-FDG PET texture analysis in lower gingival squamous cell carcinoma.

OBJECTIVES: Lower gingival squamous cell carcinoma (LGSCC) has the potential to invade the alveolar bone. Traditionally, the diagnosis of LGSCC relied on morphological imaging, but inconsistencies between these assessments and surgical findings have been observed. This study aimed to assess the correlation between LGSCC bone marrow invasion and PET texture features and to enhance diagnostic accuracy by using machine learning. METHODS: A retrospective analysis of 159 LGSCC patients with pretreatment 18 F-fluorodeoxyglucose (FDG) PET/computed tomography (CT) examination from 2009 to 2017 was performed. We extracted radiomic features from the PET images, focusing on pathologic bone marrow invasion detection. Extracted features underwent the least absolute shrinkage and selection operator algorithm-based selection and were then used for machine learning via the XGBoost package to distinguish bone marrow invasion presence. Receiver operating characteristic curve analysis was performed. RESULTS: From the 159 patients, 88 qualified for further analysis (59 men; average age, 69.2 years), and pathologic bone marrow invasion was identified in 69 (78%) of these patients. Three significant radiological features were identified: Gray level co-occurrence matrix_Correlation, INTENSITY-BASED_IntensityInterquartileRange, and MORPHOLOGICAL_SurfaceToVolumeRatio. An XGBoost machine-learning model, using PET radiomic features to detect bone marrow invasion, yielded an area under the curve value of 0.83. CONCLUSION: Our findings highlighted the potential of 18 F-FDG PET radiomic features, combined with machine learning, as a promising avenue for improving LGSCC diagnosis and treatment. Using 18 F-FDG PET texture features may provide a robust and accurate method for determining the presence or absence of bone marrow invasion in LGSCC patients.

Deep learning and atlas-based models to streamline the segmentation workflow of total marrow and lymphoid irradiation.

PURPOSE: To improve the workflow of total marrow and lymphoid irradiation (TMLI) by enhancing the delineation of organs at risk (OARs) and clinical target volume (CTV) using deep learning (DL) and atlas-based (AB) segmentation models. MATERIALS AND METHODS: Ninety-five TMLI plans optimized in our institute were analyzed. Two commercial DL software were tested for segmenting 18 OARs. An AB model for lymph node CTV (CTV_LN) delineation was built using 20 TMLI patients. The AB model was evaluated on 20 independent patients, and a semiautomatic approach was tested by correcting the automatic contours. The generated OARs and CTV_LN contours were compared to manual contours in terms of topological agreement, dose statistics, and time workload. A clinical decision tree was developed to define a specific contouring strategy for each OAR. RESULTS: The two DL models achieved a median [interquartile range] dice similarity coefficient (DSC) of 0.84 [0.71;0.93] and 0.85 [0.70;0.93] across the OARs. The absolute median Dmean difference between manual and the two DL models was 2.0 [0.7;6.6]% and 2.4 [0.9;7.1]%. The AB model achieved a median DSC of 0.70 [0.66;0.74] for CTV_LN delineation, increasing to 0.94 [0.94;0.95] after manual revision, with minimal Dmean differences. Since September 2022, our institution has implemented DL and AB models for all TMLI patients, reducing from 5 to 2 h the time required to complete the entire segmentation process. CONCLUSION: DL models can streamline the TMLI contouring process of OARs. Manual revision is still necessary for lymph node delineation using AB models.

FDG PET/CT may replace bone marrow biopsy for the evaluation of bone marrow involvement in selected mature T- and natural killer-cell lymphomas: A meta-analysis.

PURPOSE: To systematically determine the role of FDG PET/CT for the diagnosis of bone marrow involvement in mature T- and natural killer (NK)-cell lymphomas. METHODS: The PubMed, Embase and Cochrane Library databases were searched to identify eligible studies. Data extraction and quality assessment were independently conducted. Then, pooled diagnostic performance with the 95 % confidence interval (CI) was calculated and further analyzed based on different interpretation criteria, tumor type and stage. RESULTS: Fifteen studies were eventually included for quantitative analysis. Overall, the methodological quality of included studies was acceptable. For detecting bone marrow involvement, FDG PET/CT achieved a poor sensitivity of 0.62 (95 % CI, 0.48-0.71) and a reasonable specificity of 0.92 (95 % CI, 0.87-0.96). Similar performance was observed for the specific type of extranodal NK/T-cell lymphoma (ENKTCL). In early-stage patients revealed by PET/CT, extremely small proportion (2/777) showed positive bone marrow biopsy, especially for the specific type of ENKTCL, whereas in advanced-stage patients, the specificity of FDG PET/CT dropped to 0.77 (95 % CI, 0.72-0.82). Regarding the interpretation, both diffuse and focal increased uptake patterns as positivity may result in increased sensitivity but decreased specificity compared with focal pattern alone as positivity. CONCLUSIONS: FDG PET/CT demonstrated excellent negative predictive value for detecting marrow involvement in early-stage patients with mature T- and NK-cell lymphomas, especially the ENKTCL. Conversely, FDG PET/CT showed poor performance for the diagnosis of bone marrow involvement in advanced-stage patients.

Comparison of the accuracy of commercial two-point and multi-echo Dixon MRI for quantification of fat in liver, paravertebral muscles, and vertebral bone marrow.

PURPOSE: Excess fat accumulation contributes significantly to metabolic dysfunction and diseases. This study aims to systematically compare the accuracy of commercially available Dixon techniques for quantification of fat fraction in liver, skeletal musculature, and vertebral bone marrow (BM) of healthy individuals, investigating biases and sex-specific influences. METHOD: 100 healthy White individuals (50 women) underwent abdominal MRI using two-point and multi-echo Dixon sequences. Fat fraction (FF), proton density fat fraction (PDFF) and T2* values were calculated for liver, paravertebral muscles (PVM) and vertebral BM (Th8-L5). Agreement and systematic deviations were assessed using linear correlation and Bland-Altman plots. RESULTS: High correlations between FF and PDFF were observed in liver (r = 0.98 for women; r = 0.96 for men), PVM (r = 0.92 for women; r = 0.93 for men) and BM (r = 0.97 for women; r = 0.95 for men). Relative deviations between FF and PDFF in liver (18.92 % for women; 13.32 % for men) and PVM (1.96 % for women; 11.62 % for men) were not significant. Relative deviations in BM were significant (38.13 % for women; 27.62 % for men). Bias correction using linear models reduced discrepancies. T2* times were significantly shorter in BM (8.72 ms for women; 7.26 ms for men) compared to PVM (13.45 ms for women; 13.62 ms for men) and liver (29.47 ms for women; 26.35 ms for men). CONCLUSION: While no significant differences were observed for liver and PVM, systematic errors in BM FF estimation using two-point Dixon imaging were observed. These discrepancies - mainly resulting from organ-specific T2* times - have to be considered when applying two-point Dixon approaches for assessment of fat content. As suitable correction tools, linear models could provide added value in large-scale epidemiological cohort studies. Sex-specific differences in T2* should be considered.

Cross-Modal Imaging Reveals Nanoparticle Uptake Dynamics in Hematopoietic Bone Marrow during Inflammation.

Nanoparticles have been employed to elucidate the innate immune cell biology and trace cells accumulating at inflammation sites. Inflammation prompts innate immune cells, the initial responders, to undergo rapid turnover and replenishment within the hematopoietic bone marrow. Yet, we currently lack a precise understanding of how inflammation affects cellular nanoparticle uptake at the level of progenitors of innate immune cells in the hematopoietic marrow. To bridge this gap, we aimed to develop imaging tools to explore the uptake dynamics of fluorescently labeled cross-linked iron oxide nanoparticles in the bone marrow niche under varying degrees of inflammation. The inflammatory models included mice that received intramuscular lipopolysaccharide injections to induce moderate inflammation and streptozotocin-induced diabetic mice with additional intramuscular lipopolysaccharide injections to intensify inflammation. In vivo magnetic resonance imaging (MRI) and fluorescence imaging revealed an elevated level of nanoparticle uptake at the bone marrow as the levels of inflammation increased. The heightened uptake of nanoparticles within the inflamed marrow was attributed to enhanced permeability and retention with increased nanoparticle intake by hematopoietic progenitor cells. Moreover, intravital microscopy showed increased colocalization of nanoparticles within slowly patrolling monocytes in these inflamed hematopoietic marrow niches. Our discoveries unveil a previously unknown role of the inflamed hematopoietic marrow in enhanced storage and rapid deployment of nanoparticles, which can specifically target innate immune cells at their production site during inflammation. These insights underscore the critical function of the hematopoietic bone marrow in distributing iron nanoparticles to innate immune cells during inflammation. Our findings offer diagnostic and prognostic value, identifying the hematopoietic bone marrow as an imaging biomarker for early detection in inflammation imaging, advancing personalized clinical care.

[The detecting value of virtual non-calcium technique of dual-energy CT for bone marrow edema around nontraumatic osteonecrosis of the femoral head].

Objective: To evaluate the value of virtual non-calcium (VNCa) technique of dual-energy CT (DECT) for detecting bone marrow edema (BME) around nontraumatic osteonecrosis of the femoral head (ONFH) using MRI as reference standard. Methods: Nontraumatic ONFH patients were prospectively studied in the Fourth Medical Center of Chinese PLA General Hospital from October 2022 to May 2023, and their MRI and DECT images were analyzed. The diagnostic efficiency of the subjective assessment of BME around ONFH by two radiologists in VNCa color-coded images were calculated using the MRI results as the reference standard. The BME ranges were compared between VNCa images and MRI. Traditional CT values and VNCa CT values were compared between normal bone marrow and BME. The receiver operator characteristic (ROC) curve was established based on the statistically different CT values, and the area under the curve (AUC) was calculated to find the threshold to distinguish normal bone marrow from BME and evaluate the diagnostic efficacy. Results: Thirty patients with ONFH were included, including 24 males and 6 females, aged (39±12) years. There were 18 bilateral hips and 12 unilateral hips, with a total of 48 hips, 34 hips of which showed BME on MRI. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of subjective detection of BME on VNCa color coded maps by two physicians were 97.1% (33/34) and 97.1% (33/34), 92.9% (13/14) and 71.4% (10/14), 97.1% (33/34) and 89.2% (33/37), 92.9% (13/14) and 90.9% (10/11), 95.8% (46/48) and 89.6% (43/48), respectively, with no statistical difference (all P>0.05).There was no statistical difference between VNCa color-coded images and MRI in the BME range (P=1.160). The traditional CT values measured by the two radiologists were in good agreement with VNCa CT values, with intraclass correlation coefficient (ICC) of 0.948 (95%CI: 0.908-0.971) and 0.982 (95%CI: 0.969-0.990), respectively. The traditional CT value of normal bone marrow was (400.7±82.8) HU, and that of BME was (443.7±65.7) HU, with no statistical difference (P=0.062). The VNCa CT value of normal bone marrow was (-103.1±27.8) HU, and that of BME was (-32.9±25.7) HU, with statistical difference (P<0.001). The AUC of distinguishing normal bone marrow from BME based on VNCa CT value was 0.958 (95%CI: 0.857-0.995). The best cut-off value was -74.5 HU, and when the VNCa CT value was higher than -74.5 HU, the sensitivity, specificity, PPV, NPV and accuracy of diagnosing BME were 97.1%, 92.9%, 97.1%, 92.9% and 95.8 %, respectively. Conclusion: The VNCa technique of DECT has high efficiency in detecting BME around ONFH, and can accurately demonstrate the range of BME.

Detection performance and prognostic value of initial bone marrow involvement in diffuse large B-cell lymphoma: a single centre 18F-FDG PET/CT and bone marrow biopsy evaluation study.

BACKGROUND: Detection of bone marrow involvement (BMI) in diffuse large B-cell lymphoma (DLBCL) typically relies on invasive bone marrow biopsy (BMB) that faces procedure limitations, while 18F-FDG PET/CT imaging offers a noninvasive alternative. The present study assesses the performance of 18F-FDG PET/CT in DLBCL BMI detection, its agreement with BMB, and the impact of BMI on survival outcomes. PATIENTS AND METHODS: This retrospective study analyzes baseline 18F-FDG PET/CT and BMB findings in145 stage II-IV DLBCL patients, evaluating both performance of the two diagnostic procedures and the impact of BMI on survival. RESULTS: DLBCL BMI was detected in 38 patients (26.2%) using PET/CT and in 18 patients (12.4%) using BMB. Concordant results were seen in 79.3% of patients, with 20.7% showing discordant results. Combining PET/CT and BMB data, we identified 29.7% of patients with BMI. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of PET/CT for detecting DLBCL BMI were 88.4%, 100%, 100%, 95.3%, and 96.5%, respectively, while BMB showed lower sensitivity (41.9%) and NPV (46.8%). The median overall survival (OS) was not reached in any gender subgroup, with 5-year OS rates of 82% (total), 84% (female), and 80% (male) (p = 0.461), while different International Prognostic Index (IPI) groups exhibited varied 5-year OS rates: 94% for low risk (LR), 91% for low-intermediate risk (LIR), 84% for high-intermediate risk (HIR), and 65% for high risk (HR) (p = 0.0027). Bone marrow involvement did not impact OS significantly (p = 0.979). CONCLUSIONS: 18F-FDG PET/CT demonstrated superior diagnostic accuracy compared to BMB. While other studies reported poorer overall and BMI 5-year OS in DLBCL, our findings demonstrated favourable survival data.

Carboxyl-Modified Quantum Dots for NIR-IIb Bone Marrow Imaging.

Real-time, noninvasive, and nonradiative bone imaging can directly visualize bone health but requires bone-targeted probes with high specificity. Herein, we propose that carboxyl-rich fluorescent nanoprobes are easily absorbed by macrophages in bone marrow during circulation, enabling optical bone marrow imaging in vivo. We used PbS/CdS core-shell quantum dots with NIR-IIb (1500-1700 nm) emission as substrates to prepare the carboxyl-rich nanoprobe. In vivo NIR-IIb fluorescence imaging with the nanoprobes showed high resolution and penetration depth in bone tissues and allowed for imaging-guided fracture diagnosis. Bone tissue slices showed substantial accumulation of carboxyl nanoprobes in the bone marrow and strong colocalization with macrophages. Similar results with CdSe quantum dots and an organic nanofluorophore suggest that carboxyl surface modification is effective to achieve bone marrow targeting, providing a novel strategy for developing bone/bone marrow imaging probes.

Feasibility of bone marrow edema detection using dual-energy cone-beam computed tomography.

BACKGROUND: Dual-energy (DE) detection of bone marrow edema (BME) would be a valuable new diagnostic capability for the emerging orthopedic cone-beam computed tomography (CBCT) systems. However, this imaging task is inherently challenging because of the narrow energy separation between water (edematous fluid) and fat (health yellow marrow), requiring precise artifact correction and dedicated material decomposition approaches. PURPOSE: We investigate the feasibility of BME assessment using kV-switching DE CBCT with a comprehensive CBCT artifact correction framework and a two-stage projection- and image-domain three-material decomposition algorithm. METHODS: DE CBCT projections of quantitative BME phantoms (water containers 100-165 mm in size with inserts presenting various degrees of edema) and an animal cadaver model of BME were acquired on a CBCT test bench emulating the standard wrist imaging configuration of a Multitom Rax twin robotic x-ray system. The slow kV-switching scan protocol involved a 60 kV low energy (LE) beam and a 120 kV high energy (HE) beam switched every 0.5° over a 200° angular span. The DE CBCT data preprocessing and artifact correction framework consisted of (i) projection interpolation onto matched LE and HE projections views, (ii) lag and glare deconvolutions, and (iii) efficient Monte Carlo (MC)-based scatter correction. Virtual non-calcium (VNCa) images for BME detection were then generated by projection-domain decomposition into an Aluminium (Al) and polyethylene basis set (to remove beam hardening) followed by three-material image-domain decomposition into water, Ca, and fat. Feasibility of BME detection was quantified in terms of VNCa image contrast and receiver operating characteristic (ROC) curves. Robustness to object size, position in the field of view (FOV) and beam collimation (varied 20-160 mm) was investigated. RESULTS: The MC-based scatter correction delivered > 69% reduction of cupping artifacts for moderate to wide collimations (> 80 mm beam width), which was essential to achieve accurate DE material decomposition. In a forearm-sized object, a 20% increase in water concentration (edema) of a trabecular bone-mimicking mixture presented as ∼15 HU VNCa contrast using 80-160 mm beam collimations. The variability with respect to object position in the FOV was modest (< 15% coefficient of variation). The areas under the ROC curve were > 0.9. A femur-sized object presented a somewhat more challenging task, resulting in increased sensitivity to object positioning at 160 mm collimation. In animal cadaver specimens, areas of VNCa enhancement consistent with BME were observed in DE CBCT images in regions of MRI-confirmed edema. CONCLUSION: Our results indicate that the proposed artifact correction and material decomposition pipeline can overcome the challenges of scatter and limited spectral separation to achieve relatively accurate and sensitive BME detection in DE CBCT. This study provides an important baseline for clinical translation of musculoskeletal DE CBCT to quantitative, point-of-care bone health assessment.

Differentiation of bone metastases from benign red marrow depositions: utilizing qualitative and quantitative analysis of conventional T1-weighted imaging and fat-suppressed T2-weighted imaging.

OBJECTIVES: To distinguish bone metastases (BMs) from benign red marrow depositions (BRMs) by qualitative and quantitative analyses of T1-weighted imaging and fat-suppressed T2-weighted imaging (T2 FS). METHODS: For 75 lesions including 38 BMs and 37 BRMs, two radiologists independently evaluated magnetic resonance images by qualitative (signal intensity [SI] of lesions compared to that of normal muscle [NM] or normal bone marrow [NBM]) and quantitative (parameters of the region of interests in the lesions, including T1 ratio [T1 SI ratio of lesion and NM], T2FMu ratio [T2 FS SI ratio of lesion and NM], and T2FMa ratio [T2 FS SI ratio of lesion and NBM]) analyses. RESULTS: Hyperintensity relative to NM or NBM on T2 FS was more frequent in BMs than in BRMs (100% vs 59.5%-78.4%, respectively; P ≤ 0.001) but also was present in more than half of BRMs. All quantitative parameters showed a significant difference between BMs and BRMs (T1 ratio, 1.075 vs 1.227 [P = 0.002]; T2FMu ratio, 2.094 vs 1.282 [P < 0.001]; T2FMa ratio, 3.232 vs 1.810 [P < 0.001]). The receiver operating characteristics areas under the curves of T2FMu and T2FMa ratios were clinically useful (0.781 and 0.841, respectively) and did not demonstrate statistically significant differences. CONCLUSIONS: The quantitative analysis of T2 FS facilitates distinguishing between BMs and BRMs, regardless of whether the reference was NM or NBM. ADVANCES IN KNOWLEDGE: Quantitative parameters derived from T2 FS facilitate differentiation of BMs BRMs without additional scans. The role of NBM as an internal standard for T2 FS to differentiate between BMs and BRMs is similar to that of NM.

Demonstration of magnetic resonance Z-spectral imaging for fatty acid characterization of bone marrow at 3 T.

Magnetic resonance Z-spectral imaging (ZSI) has emerged as a new approach to measure fat fraction (FF). However, its feasibility for fat spectral imaging remains to be elucidated. In this study, a single-slice ZSI sequence dedicated to fat spectral imaging was designed, and its capability for fatty acid characterization was investigated on peanut oil samples, a multiple-vial fat-water phantom with varied oil volumes, and vertebral body marrow in healthy volunteers and osteoporosis patients at 3 T. The peanut oil spectrum was also recorded with a 400-MHz NMR spectrometer. A Gaussian-Lorentzian sum model was used to resolve water and six fat signals of the pure oil sample or four fat signals of the fat-water phantom or vertebral bone marrow from Z spectra. Fat peak amplitudes were normalized to the total peak amplitude of water and all fat signals. Normalized fat peak amplitudes and FF were quantified and compared among vials of the fat-water phantom or between healthy volunteers and osteoporosis patients. An unpaired student's t-test and Pearson's correlation were conducted, with p less than 0.05 considered statistically significant. The results showed that the peanut oil spectra measured with the ZSI technique were in line with respective NMR spectra, with amplitudes of the six fat signal peaks significantly correlated between the two methods (y = x + 0.001, r = 0.996, p < 0.001 under a repetition time of 1.6 s; and y = 1.026x - 0.003, r = 0.996, p < 0.001 under a repetition time of 3.1 s). Moreover, ZSI-measured FF exhibited a significant correlation with prepared oil volumes (y = 0.876x + 1.290, r = 0.996, p < 0.001). The osteoporosis patients showed significantly higher normalized fat peak amplitudes and FF in the L4 vertebral body marrow than the healthy volunteers (all p < 0.01). In summary, the designed ZSI sequence is feasible for fatty acid characterization, and has the potential to facilitate the diagnosis and evaluation of diseases associated with fat alterations at 3 T.

Quantitative MRI reveals heterogeneous impacts of treatment on diseased bone marrow in a mouse model of myelofibrosis.

PURPOSE: Analyzing bone marrow in the hematologic cancer myelofibrosis requires endpoint histology in mouse models and bone marrow biopsies in patients. These methods hinder the ability to monitor therapy over time. Preclinical studies typically begin treatment before mice develop myelofibrosis, unlike patients who begin therapy only after onset of disease. Using clinically relevant, quantitative MRI metrics allowed us to evaluate treatment in mice with established myelofibrosis. METHODS: We used chemical shift-encoded fat imaging, DWI, and magnetization transfer sequences to quantify bone marrow fat, cellularity, and macromolecular components in a mouse model of myelofibrosis. We monitored spleen volume, the established imaging marker for treatment, with anatomic MRI. After confirming bone marrow disease by MRI, we randomized mice to treatment with an approved drug (ruxolitinib or fedratinib) or an investigational agent, navitoclax, for 33 days. We measured the effects of therapy over time with bone marrow and spleen MRI. RESULTS: All treatments produced heterogeneous responses with improvements in bone marrow evident in subsets of individual mice in all treatment groups. Reductions in spleen volume commonly occurred without corresponding improvement in bone marrow. MRI revealed patterns associated with effective and ineffective responses to treatment in bone marrow and identified regional variations in efficacy within a bone. CONCLUSIONS: Quantitative MRI revealed modest, heterogeneous improvements in bone marrow disease when treating mice with established myelofibrosis. These results emphasize the value of bone marrow MRI to assess treatment in preclinical models and the potential to advance clinical trials for patients.