Development and Validation of a Deep-Learning-Based Algorithm for Detecting and Classifying Metallic Implants in Abdominal and Spinal CT Topograms.

PURPOSE: To develop and validate a deep-learning-based algorithm (DLA) that is designed to segment and classify metallic objects in topograms of abdominal and spinal CT. METHODS: DLA training for implant segmentation and classification was based on a U-net-like architecture with 263 annotated hip implant topograms and 2127 annotated spine implant topograms. The trained DLA was validated with internal and external datasets. Two radiologists independently reviewed the external dataset consisting of 2178 abdomen anteroposterior (AP) topograms and 515 spine AP and lateral topograms, all collected in a consecutive manner. Sensitivity and specificity were calculated per pixel row and per patient. Pairwise intersection over union (IoU) was also calculated between the DLA and the two radiologists. RESULTS: The performance parameters of the DLA were consistently >95% in internal validation per pixel row and per patient. DLA can save 27.4% of reconstruction time on average in patients with metallic implants compared to the existing iMAR. The sensitivity and specificity of the DLA during external validation were greater than 90% for the detection of spine implants on three different topograms and for the detection of hip implants on abdominal AP and spinal AP topograms. The IoU was greater than 0.9 between the DLA and the radiologists. However, the DLA training could not be performed for hip implants on spine lateral topograms. CONCLUSIONS: A prototype DLA to detect metallic implants of the spine and hip on abdominal and spinal CT topograms improves the scan workflow with good performance for both spine and hip implants.

Comparative analysis of image quality and interchangeability between standard and deep learning-reconstructed T2-weighted spine MRI.

RATIONALE AND OBJECTIVES: MRI reconstruction of undersampled data using a deep learning (DL) network has been recently performed as part of accelerated imaging. Herein, we compared DL-reconstructed T2-weighted image (T2-WI) to conventional T2-WI regarding image quality and degenerative lesion detection. MATERIALS AND METHODS: Sixty-two patients underwent C-spine (n = 27) or L-spine (n = 35) MRIs, including conventional and DL-reconstructed T2-WI. Image quality was assessed with non-uniformity measurement and 4-scale grading of structural visibility. Three readers (R1, R2, R3) independently assessed the presence and types of degenerative lesions. Student t-test was used to compare non-uniformity measurements. Interprotocol and interobserver agreement of structural visibility was analyzed with Wilcoxon signed-rank test and weighted-κ values, respectively. The diagnostic equivalence of degenerative lesion detection between two protocols was assessed with interchangeability test. RESULTS: The acquisition time of DL-reconstructed images was reduced to about 21-58% compared to conventional images. Non-uniformity measurement was insignificantly different between the two images (p-value = 0.17). All readers rated DL-reconstructed images as showing the same or superior structural visibility compared to conventional images. Significantly improved visibility was observed at disk margin of C-spine (R1, p < 0.001; R2, p = 0.04) and dorsal root ganglia (R1, p = 0.03; R3, p = 0.02) and facet joint (R1, p = 0.04; R2, p < 0.001; R3, p = 0.03) of L-spine. Interobserver agreements of image quality were variable in each structure. Clinical interchangeability between two protocols for degenerative lesion detection was verified showing <5% in the upper bounds of 95% confidence intervals of agreement rate differences. CONCLUSIONS: DL-reconstructed T2-WI demonstrates comparable image quality and diagnostic performance with conventional T2-WI in spine imaging, with reduced acquisition time.

Quantification of Synovial Fluid Using Magnetic Resonance Fingerprinting Multicomponent Imaging in the Articular Cartilage of the Knee.

RATIONALE AND OBJECTIVES: The purpose of this study was to verify the feasibility of magnetic resonance fingerprinting (MRF)-derived synovial fluid fraction (SFF) mapping for quantifying subvoxel-sized cartilage defects. MATERIALS AND METHODS: MRF was performed on a 3-Tesla scanner and used to derive T2 and SFF maps. An ex vivo experiment was performed using bovine bone; different numbers of holes (4, 6, 8, 10, and 12) were drilled separately on the articular surface, and SFF values were compared among the drilled areas. In a clinical study, 16 osteoarthritis patients underwent sagittal 3D fast spinecho (FSE) and MRF scanning, and knee cartilage segmentation was performed on each image. For morphologic analysis, fluid-excluded images of the SFF (FEISFF) and T2 maps (FEIT2) were generated using the cartilage segmentations, and the whole-organ magnetic resonance imaging score (WORMS) of each FEI and 3D FSE image were compared using the kappa coefficient. For quantitative analysis, intact cartilage volumes in the SFF (VSFF) and T2 maps (VT2) were calculated, and their correlations with reference to the actual cartilage volume on 3D FSE images (V3D) were evaluated. RESULTS: In the ex vivo experiment, the SFF value increased as the number of holes increased. The kappa coefficients of the WORMS were 0.80 and 0.64 in the SFF and T2 maps, respectively, and substantial to almost perfect agreement was observed in the medial tibiofemoral joint. The V3D-VSFF and V3D-VT2 correlation coefficients differed by 0.03 or more in the medial tibiofemoral joint. CONCLUSION: The MRF-derived SFF map can feasibly evaluate small, invisible cartilage defects and quantify cartilage volumes.

Deep learning-based k-space-to-image reconstruction and super resolution for diffusion-weighted imaging in whole-spine MRI.

PURPOSE: To assess the feasibility of deep learning (DL)-based k-space-to-image reconstruction and super resolution for whole-spine diffusion-weighted imaging (DWI). METHOD: This retrospective study included 97 consecutive patients with hematologic and/or oncologic diseases who underwent DL-processed whole-spine MRI from July 2022 to March 2023. For each patient, conventional (CONV) axial single-shot echo-planar DWI (b = 50, 800 s/mm2) was performed, followed by DL reconstruction and super resolution processing. The presence of malignant lesions and qualitative (overall image quality and diagnostic confidence) and quantitative (nonuniformity [NU], lesion contrast, signal-to-noise ratio [SNR], contrast-to-noise ratio [CNR], and ADC values) parameters were assessed for DL and CONV DWI. RESULTS: Ultimately, 67 patients (mean age, 63.0 years; 35 females) were analyzed. The proportions of vertebrae with malignant lesions for both protocols were not significantly different (P: [0.55-0.99]). The overall image quality and diagnostic confidence scores were higher for DL DWI (all P ≤ 0.002) than CONV DWI. The NU, lesion contrast, SNR, and CNR of each vertebral segment (P ≤ 0.04) but not the NU of the sacral segment (P = 0.51) showed significant differences between protocols. For DL DWI, the NU was lower, and lesion contrast, SNR, and CNR were higher than those of CONV DWI (median values of all segments; 19.8 vs. 22.2, 5.4 vs. 4.3, 7.3 vs. 5.5, and 0.8 vs. 0.7). Mean ADC values of the lesions did not significantly differ between the protocols (P: [0.16-0.89]). CONCLUSIONS: DL reconstruction can improve the image quality of whole-spine diffusion imaging.

Imaging features and clinical significance of atypical pleural plaques mimicking bone tumors: a retrospective case series.

This study aimed to examine the imaging characteristics and clinical implications of atypical pleural lesions that mimic bone tumors and form along the inner margins of consecutive ribs. This retrospective analysis included 45 atypical pleural lesions arising from 13 patients who underwent chest computed tomography (CT) between April 2021 and March 2023. The clinical features, CT findings, and radiologic diagnoses prior to pathologic identification were examined. Pathological findings were reviewed in the surgically resected case. Subgroup analysis was performed based on the presence of concurrent typical pleural plaques. The mean age of the patients was 69.3±8.4 years with a predominance of males (76.9%). The lesions primarily exhibited unilateral involvement (84.6%), being most frequently located in the right mid-level posterior region. Calcification was present in 75.6% of cases, typically seen continuously along the ribs (82.4%). Adjacent rib changes were observed in 28.9% of cases. These lesions were frequently misdiagnosed as osteochondromas or bony spurs (55.6%) by thoracic radiologists. No significant growth was observed during follow-up (n=11, 47±41 months), and the pathological findings were consistent with pleural plaques. Patients with concurrent typical pleural plaques had more atypical pleural lesions without statistical significance (P=0.071) and showed a more even distribution (P=0.039). In conclusion, atypical pleural lesions resembling bone tumors along consecutive ribs represent a distinct subset of pleural plaques. Their unique distribution and morphology should be recognized by radiologists to avoid misinterpretation and unnecessary interventions.

An Updated Review of Magnetic Resonance Neurography for Plexus Imaging.

Magnetic resonance neurography (MRN) is increasingly used to visualize peripheral nerves in vivo. However, the implementation and interpretation of MRN in the brachial and lumbosacral plexi are challenging because of the anatomical complexity and technical limitations. The purpose of this article was to review the clinical context of MRN, describe advanced magnetic resonance (MR) techniques for plexus imaging, and list the general categories of utility of MRN with pertinent imaging examples. The selection and optimization of MR sequences are centered on the homogeneous suppression of fat and blood vessels while enhancing the visibility of the plexus and its branches. Standard 2D fast spin-echo sequences are essential to assess morphology and signal intensity of nerves. Moreover, nerve-selective 3D isotropic images allow improved visualization of nerves and multiplanar reconstruction along their course. Diffusion-weighted and diffusion-tensor images offer microscopic and functional insights into peripheral nerves. The interpretation of MRN in the brachial and lumbosacral plexi should be based on a thorough understanding of their anatomy and pathophysiology. Anatomical landmarks assist in identifying brachial and lumbosacral plexus components of interest. Thus, understanding the varying patterns of nerve abnormalities facilitates the interpretation of aberrant findings.

Development of a Semiquantitative Whole-Body MRI Scoring System for Multiple Myeloma.

Background In patients with multiple myeloma (MM), the serum marker ß2-microglobulin does not always accurately reflect tumor load. In contrast, whole-body (WB) MRI has shown high sensitivity for detecting bone lesions. Purpose To develop and validate a semiquantitative WB MRI scoring system for newly diagnosed MM and to compare it with the International Staging System (ISS) and Revised ISS (R-ISS). Materials and Methods This study included two retrospective groups (group 1, July 2015 to September 2021; group 2, February 2020 to September 2021) and one prospective group (group 3, October 2021 to February 2022) of patients with newly diagnosed MM. A new scoring system for MM was developed using spine MRI scans in group 1 and WB MRI scans in group 2 that integrated three features: (a) background marrow pattern, (b) number of focal bone lesions, and (c) presence of extramedullary or paramedullary lesions. The summed total score ranged from zero to nine. The interobserver agreement for each feature was assessed using Fleiss or Cohen weighted κ. WB MRI total scores in group 3 were compared across ISS and R-ISS stages using two-way analysis of variance. Results Groups 1, 2, and 3 included 103 patients (mean age, 62.1 years ± 9.1 [SD]; 60 men), 36 patients (mean age 65.4 years ± 11.3 [SD]; 19 women), and 39 participants (mean age, 62.0 years ± 11.7 [SD]; 20 men), respectively. The interobserver agreements for the three features composing the scoring system were substantial (κ range, 0.69-0.80). WB MRI total score increased with increasing ISS stage (mean score for ISS 1, 2, and 3 was 2.2, 4.2, and 5.8, respectively; P = .009) and R-ISS stage (mean score for R-ISS 1, 2, and 3 was 2.1, 3.8, and 5.9, respectively; P = .005). Conclusion The developed WB MRI scoring system for MM demonstrated substantial observer agreement and corresponded well with ISS and R-ISS stages. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Dragan and Messiou in this issue.

Diagnosis of Local Recurrence of Malignant Soft Tissue Tumors after Reconstructive Surgery on MRI.

PURPOSE: Magnetic resonance imaging (MRI) is useful in the diagnosis of local recurrence, but few studies have explored recurrence in MRI in patients after reconstructive surgery. The purpose of this study was to analyze MRI findings of locoregional recurrence following reconstructive surgery after malignant soft tissue tumor resection. METHOD: Fifty-three postoperative MRIs from 37 patients who underwent reconstructive surgery after malignant soft tissue tumor resection were retrospectively reviewed. A total of 76 enhancing lesions, including 40 locoregional recurrences and 36 postoperative changes, were analyzed regarding morphology (location on the transplanted tissue, border, and shape) and the signals on T1- and T2-weighted imaging (T1WI, T2WI), fat-suppressed (FS) T2WI, and contrast-enhanced FS T1WI. Diffusion-weighted imaging with an apparent diffusion coefficient was assessed. A chi-squared test and Fisher's exact test were used for statistical analysis. RESULTS: The most common site of recurrent tumors and postoperative changes was the peripheral margin on transplanted tissue (63% and 61%, respectively p = 0.907). Recurrent tumors commonly appeared with well-defined borders (75%) as well as nodular appearance (98%), hyperintensity on T2WI (85%) and FS-T2WI (95%), isointensity on T1WI (65%), impeded water diffusion (55%), and intense (50%) or moderate (45%) enhancement. Postoperative changes showed ill-defined borders (75%), nodular appearance (56%), facilitated water diffusion (69%), and moderate (86%) enhancement, which were significantly different from those of recurrent tumors (p ≤ 0.020). CONCLUSIONS: Common and partitioning MRI features of locoregional recurrence were well-defined borders, nodular shape, impeded water diffusion, and intense enhancement. Peripheral margins on transplanted tissue were common sites in both recurrent tumors and postoperative changes.

Ensemble learning-based radiomics with multi-sequence magnetic resonance imaging for benign and malignant soft tissue tumor differentiation.

Many previous studies focused on differentiating between benign and malignant soft tissue tumors using radiomics model based on various magnetic resonance imaging (MRI) sequences, but it is still unclear how to set up the input radiomic features from multiple MRI sequences. Here, we evaluated two types of radiomics models generated using different feature incorporation strategies. In order to differentiate between benign and malignant soft tissue tumors (STTs), we compared the diagnostic performance of an ensemble of random forest (R) models with single-sequence MRI inputs to R models with pooled multi-sequence MRI inputs. One-hundred twenty-five STT patients with preoperative MRI were retrospectively included and consisted of training (n = 100) and test (n = 25) sets. MRI included T1-weighted (T1-WI), T2-weighted (T2-WI), contrast-enhanced (CE)-T1-WI, diffusion-weighted images (DWIs, b = 800 sec/mm2) and apparent diffusion coefficient (ADC) maps. After tumor segmentation on each sequence, 100 original radiomic features were extracted from each sequence image and divided into three-feature sets: T features from T1- and T2-WI, CE features from CE-T1-WI, and D features from DWI and ADC maps. Four radiomics models were built using Lasso and R with four combinations of three-feature sets as inputs: T features (R-T), T+CE features (R-C), T+D features (R-D), and T+CE+D features (R-A) (Type-1 model). An ensemble model was built by soft voting of five, single-sequence-based R models (Type-2 model). AUC, sensitivity, specificity, and accuracy of each model was calculated with five-fold cross validation. In Type-1 model, AUC, sensitivity, specificity, and accuracy were 0.752, 71.8%, 61.1%, and 67.2% in R-T; 0.756, 76.1%, 70.4%, and 73.6% in R-C; 0.750, 77.5%, 63.0%, and 71.2% in R-D; and 0.749, 74.6%, 61.1%, and 68.8% R-A models, respectively. AUC, sensitivity, specificity, and accuracy of Type-2 model were 0.774, 76.1%, 68.5%, and 72.8%. In conclusion, an ensemble method is beneficial to incorporate features from multi-sequence MRI and showed diagnostic robustness for differentiating malignant STTs.

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Multiple myeloma, which is a proliferative disease of plasma cells that originate from a single clone, is the second most common hematologic malignancy following non-Hodgkin lymphoma. In the past, its diagnosis was made based on clinical findings (so-called "CRAB") and a skeletal survey using radiographs. However, since the implementation of the International Myeloma Working Group's revised guideline regarding the radiologic diagnosis of multiple myeloma, whole-body (WB) MRI has emerged to play a central role in the early diagnosis of multiple myeloma. Diffusion-weighted imaging and fat quantification using Dixon methods enable treatment response assessment by MRI. In keeping with the trend, a multi-institutional and multidisciplinary consensus for standardized image acquisition and reporting known as the Myeloma Response Assessment and Diagnostic System (MY-RADS) has recently been proposed. This review aims to describe the clinical application of WB-MRI based on MY-RADS in multiple myeloma, discuss its limitations, and suggest future directions for improvement.

Differentiating Multiple Myeloma and Osteolytic Bone Metastases on Contrast-Enhanced Computed Tomography Scans: The Feasibility of Radiomics Analysis.

Osteolytic lesions can be seen in both multiple myeloma (MM), and osteolytic bone metastasis on computed tomography (CT) scans. We sought to assess the feasibility of a CT-based radiomics model to distinguish MM from metastasis. This study retrospectively included patients with pre-treatment thoracic or abdominal contrast-enhanced CT from institution 1 (training set: 175 patients with 425 lesions) and institution 2 (external test set: 50 patients with 85 lesions). After segmenting osteolytic lesions on CT images, 1218 radiomics features were extracted. A random forest (RF) classifier was used to build the radiomics model with 10-fold cross-validation. Three radiologists distinguished MM from metastasis using a five-point scale, both with and without the assistance of RF model results. Diagnostic performance was evaluated using the area under the curve (AUC). The AUC of the RF model was 0.807 and 0.762 for the training and test set, respectively. The AUC of the RF model and the radiologists (0.653-0.778) was not significantly different for the test set (p ≥ 0.179). The AUC of all radiologists was significantly increased (0.833-0.900) when they were assisted by RF model results (p < 0.001). In conclusion, the CT-based radiomics model can differentiate MM from osteolytic bone metastasis and improve radiologists' diagnostic performance.

Prevalence and Associated Factors of Facet Joint Ankylosis in Patients With Axial Spondyloarthritis.

OBJECTIVE: To investigate the prevalence of facet joint ankylosis in the whole spine in axial spondyloarthritis (axSpA) using low-dose computed tomography (LDCT), and to identify factors associated with facet joint ankylosis. METHODS: Whole spine LDCT images from 161 patients with axSpA were examined, and the presence of facet joint ankylosis was assessed (right and left, C2-S1) by 2 readers. Facet joint ankylosis was scored from 0 to 46. Structural damage of vertebral body was assessed using CT Syndesmophyte Score (CTSS). Factors associated with ankylosed facet joint scores for the whole spine were identified using a generalized linear model with a negative binomial distribution. RESULTS: Seventy-nine patients (49%) and 70 patients (43%; reader 1 and reader 2, respectively) had ≥ 1 ankylosed facet joint. Facet joint ankylosis was most common in the thoracic spine. The mean score of facet joint ankylosis for the whole spine was 6.6 (SD 11.2) in reader 1 and 4.2 (SD 8.4) in reader 2. Whole spine facet joint ankylosis score positively correlated with Ankylosing Spondylitis Disease Activity Score (ASDAS) and CTSS. In multivariable analysis, the ankylosed facet joint score was associated with ASDAS, sacroiliitis, CTSS, and a history of uveitis in both readers. Uveitis history, ASDAS, and CTSS were associated with whole spine facet joint ankylosis score in subgroup analysis of only radiographic axSpA. CONCLUSION: The prevalence of ankylosed facet joints is high in axSpA, especially in the thoracic segment. The whole spine ankylosed facet joint score is significantly associated with a history of uveitis, ASDAS, sacroiliitis, and syndesmophyte score.

Diagnosis of Marginal Infiltration in Soft Tissue Sarcoma by Radiomics Approach Using T2-Weighted Dixon Sequence.

BACKGROUND: Determination of preoperative soft tissue sarcoma (STS) margin is crucial for patient prognosis. PURPOSE: To evaluate diagnostic performance of radiomics model using T2-weighted Dixon sequence for infiltration degree of STS margin. STUDY TYPE: Retrospective. POPULATION: Seventy-two STS patients consisted of training (n = 58) and test (n = 14) sets. FIELD STRENGTH/SEQUENCE: A 3.0 T; T2-weighted Dixon images. ASSESSMENT: Pathologic result of marginal infiltration in STS (circumscribed margin; n = 27, group 1, focally infiltrative margin; n = 31, group 2-A, diffusely infiltrative margin; n = 14, group 2-B) was the reference standard. Radiomic volume and shape (VS) and other (T2) features were extracted from entire tumor volume and margin, respectively. Twelve radiomics models were generated using four combinations of classifier algorithms (R, SR, LR, LSR) and three different inputs (VS, T2, VS + T2 [VST2] features) to differentiate the three groups. Three radiologists (reader 1, 2, 3) analyzed the marginal infiltration with 6-scale confidence score. STATISTICAL TESTS: Area under the receiver operating characteristic curve (AUC) and concordance rate. RESULTS: Averaged AUCs of R, SR, LR, LSR models were 0.438, 0.466, 0.438, 0.466 using VS features, 0.596, 0.584, 0.814, 0.815 using T2 features, and 0.581, 0.587, 0.821, 0.821 using VST2 features, respectively. The LR and LSR models constructed with T2 or VST2 features showed higher AUC and concordance rate compared to radiologists' analysis (AUC; 0.730, 0.675, 0.706, concordance rate; 0.46, 0.43, 0.47 in reader 1, 2, 3). DATA CONCLUSION: Radiomics model constructed with features from tumor margin on T2-weighted Dixon sequence is a promising method for differentiating infiltration degree of STS margin. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Role of MR Neurography for Evaluation of the Lumbosacral Plexus: A Scoping Review.

Purpose: MR neurography (MRN) is an imaging technique optimized to visualize the peripheral nerves. This review aimed to discover an optimized protocol for MRN of the lumbosacral plexus (LSP) and identify evidence for the clinical benefit of lumbosacral plexopathies. Materials and Methods: We performed a systematic search of the two medical databases until September 2021. 'Magnetic resonance imaging', 'lumbosacral plexus', 'neurologic disease', or equivalent terms were used to search the literature. We extracted information on indications, MRN protocols for LSP, and clinical efficacy from 55 studies among those searched. Results: MRN of the LSP is useful for displaying the distribution of peripheral nerve disease, guiding perineural injections, and assessing extraspinal causes of sciatica. Three-dimensional short-tau inversion recovery turbo spin-echo combined with vascular suppression is the mainstay of MRN. Conclusion: Future work on the MRN of LSP should be directed to technical maturation and clinical validation of efficacy.

Differentiation of multiple myelomas from osteolytic bone metastases: Diagnostic value of tumor homogeneity on Contrast-Enhanced CT.

OBJECTIVES: To investigate the diagnostic value of tumor homogeneity on contrast-enhanced (CE) computed tomography (CT) to differentiate multiple myeloma (MM) from osteolytic bone metastases (Mets). METHODS: This retrospective study included patients who were diagnosed with MM or Mets and had multiple (≥2) osteolytic bone tumors on pre-treatment CE-CT. Intratumoral homogeneity was assessed by coefficient of variation (CV, ratio of standard deviation to mean) of the density of a single lesion (CV-lesion). Intertumoral homogeneity was assessed as the CV of the densities of multiple lesions in one patient (CV-patient). A classification model was built from CT parameters using classification and regression tree (CART) analysis. Diagnostic performance of the model was evaluated using C-statistics. RESULTS: A total of 272 lesions (81 MM and 191 Mets) of 105 patients were analyzed. The mean CV-lesion and CV-patient of MM were significantly lower than those of Mets: 0.17 vs 0.26 for CV-lesion (p = 0.005) and 0.16 vs 0.23 for CV-patient (p = 0.013). Thickened struts were more common in MM than in Mets (49.1% vs 12.8%, p ≤ 0.001). In CART analysis, CV-lesion was the first partitioning predictor, followed by thickened struts and by CV patient. The CART model could distinguish MM from Mets in both the model development cohort (C-statistic: 0.843) and the temporal validation cohort (0.721, 0.686, and 0.686 for three reviewers, respectively). CONCLUSIONS: MM showed intratumoral and intertumoral homogeneity compared with Mets on CE-CT. The combination of CV-lesion and CV-patient can be helpful to radiologists in differentiation of MM from Mets. ADVANCES IN KNOWLEDGE: Our study showed that MM had intratumoral and intertumoral homogeneity compared with Mets on contrast-enhanced CT.

Detecting Multiple Myeloma Infiltration of the Bone Marrow on CT Scans in Patients with Osteopenia: Feasibility of Radiomics Analysis.

It is difficult to detect multiple myeloma (MM) infiltration of the bone marrow on computed tomography (CT) scans of patients with osteopenia. Our aim is to determine the feasibility of using radiomics analysis to detect MM infiltration of the bone marrow on CT scans of patients with osteopenia. The contrast-enhanced thoracic CT scans of 104 patients with MM and 104 age- and sex-matched controls were retrospectively evaluated. All individuals had decreased bone density on radiography. The study group was divided into development (n = 160) and temporal validation sets (n = 48). The radiomics model was developed using 805 texture features extracted from the bone marrow for a development set, using a Random Forest algorithm. The developed models were applied to evaluate a temporal validation set. For comparison, three radiologists evaluated the CTs for the possibility of MM infiltration in the bone marrow. The diagnostic performances were assessed and compared using an area under the receiver operating characteristic curve (AUC) analysis. The AUC of the radiomics model was not significantly different from those of the radiologists (p = 0.056-0.821). The radiomics analysis results showed potential for detecting MM infiltration in the bone marrow on CT scans of patients with osteopenia.

Can whole spine magnetic resonance imaging predict radiographic progression and inflammatory activity in axial spondyloarthritis?

OBJECTIVE: To investigate whether initial whole spine magnetic resonance imaging (MRI) predicts radiographic progression and inflammatory activity in patients with axial spondyloarthritis (axSpA). METHODS: A retrospective analysis of spine MRI and X-rays from 70 axSpA patients was conducted. The number of affected discovertebral units was determined according to the definition of pathologic lesions on spine MRI set down by the ASAS/OMERACT group. Radiographic progression was defined as an increase in the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS) of≥2 compared with baseline. The association of spine MRI with radiographic progression, cumulative C-reactive protein (CRP), and cumulative erythrocyte sedimentation rate (ESR) was investigated. RESULTS: The axSpA-relevant lesions on spine MRI at baseline were independent predictors of radiographic progression. Arthritis of the costovertebral and costotransverse joints on MRI showed the highest odds ratio at 3years (OR [95% CI]: 2.54 [1.29-5.02]). Receiver operating characteristic curve analysis revealed that the area under the curve (AUC) for radiographic progression at 2years was 0.89 [95% CI: 0.81-0.96] for structural lesions and 0.83 [95% CI: 0.72-0.94] for inflammatory lesions. Notably, subgroup analysis of 26 patients with mSASSS=0 showed that fatty metaplasia on MRI were highly predictive of radiographic progression at 3years (AUC [95% CI]: 0.87 [0.61-1.00]). Moreover, 3-year cumulative ESR and CRP values increased in proportion to the extent of inflammatory lesions on initial MRI. CONCLUSION: Initial MRI assessment of the whole spine may predict radiographic progression and subsequent systemic inflammatory burden in axSpA patients, particularly those without axSpA-relevant abnormalities on spine X-rays.

High-intensity focused ultrasound treatment for excessive subcutaneous fat in abdomen, upper arms, and thigh: A pilot study.

BACKGROUND: High-intensity focused ultrasound (HIFU) has been recently introduced as a non-invasive therapeutic modality for controlling excessive subcutaneous fat. OBJECTIVE: The efficacy and safety of the HIFU device for sculpting the abdomen, upper arm, and thigh were evaluated. MATERIALS AND METHODS: Ten subjects with more than 10 mm of subcutaneous fat in the abdomen, upper arm, and/or thigh were recruited. We evaluate mean change in the thickness and circumference of subcutaneous fat of each treated area measured using ultrasound 12 weeks after the procedure, the degree of pain, and subject and practitioner satisfaction 12 weeks after the procedure. RESULTS: The mean change of subcutaneous fat thickness in the abdomen, upper arm, and thigh measured using ultrasound 12 weeks after the procedure was -4.33 ± 2.42, -1.86 ± 1.35, and -1.86 ± 1.35 mm, respectively. Compared with pretreatment, subcutaneous fat thickness of the abdomen and upper arm was significantly reduced (p = 0.0020 and p = 0.0004, respectively), but not in the thigh (p = 0.0716). Highest patient satisfaction was for the abdomen. Pain was generally tolerable. CONCLUSION: The results from the present study indicate HIFU can be an effective and safe therapeutic modality for removing excessive subcutaneous fat in humans.

Fully automated segmentation of lumbar bone marrow in sagittal, high-resolution T1-weighted magnetic resonance images using 2D U-NET.

BACKGROUND: We investigated a 2-dimensional (2D) U-Net model to delineate lumbar bone marrow (BM) using a high resolution T1-weighted magnetic resonance imaging. METHOD: Healthy controls (n = 44, 836 images) and patients with hematologic diseases (n = 56, 1064 images) received MRI of the lumbar spines. Lumbar BM on each image was manually delineated by an experienced radiologist as a ground-truth. The 2D U-Net models were trained using a healthy lumbar BM only, diseased BM only, and using healthy and diseased BM combined, respectively. The models were validated using healthy and diseased subjects, separately. A repeated-measures analysis of variance was performed to compare segmentation accuracies with 2 validation cohorts among U-Net trained with healthy subjects (UNET_HC), U-Net trained with diseased subjects (UNET_HD), U-Net trained with all subjects including both healthy and diseased subjects (UNET_HCHD), and 3-dimensional Grow-Cut algorithm (3DGC). RESULTS: When validated with the healthy subjects, UNET_HC, UNET_HD, UNET_HCHD and 3DGC achieved the mean and standard deviation of the Dice Similarity Coefficient (DSC) of 0.9415 ± 0.07056, 0.9583 ± 0.05146, 0.9602 ± 0.0486 and 0.9139 ± 0.2039, respectively. When validated with the diseased subjects, DSCs of UNET_HC, UNET_HD, UNET_HCHD and 3DGC were 0.8303 ± 0.1073, 0.9502 ± 0.0217, 0.9502 ± 0.0217 and 0.8886 ± 0.2179, respectively. The U-Net models segmented BM better than the semi-automatic 3DGC (P < 0.0001), and UNET_HD produced better results than UNET_HC (P < 0.0001). CONCLUSIONS: We successfully constructed a fully automatic lumbar BM segmentation model for a high-resolution T1-weighted MRI using U-Net, which outperformed most of the previously reported approaches and the existing semi-automatic algorithm.

Association between facet joint ankylosis and functional impairment in patients with radiographic axial spondyloarthritis.

OBJECTIVES: To investigate the occurrence of facet joint ankylosis in the spine of patients with radiographic axial spondyloarthritis (r-axSpA) using low dose computed tomography (ldCT), and to examine the association between facet joint ankylosis and functional impairment. METHODS: A group of 126 patients with r-axSpA was selected from Incheon Saint Mary's axSpA observational cohort and whole spine ldCT data were examined. Facet joint (right and left, C2-S1) ankylosis was scored from 0-46 (total). The presence of facet joint ankylosis was assessed by two readers, each blinded to the patient data. The inter-reader reliability of facet joint ankylosis scoring was assessed using intraclass correlation coefficients (ICCs). The CT Syndesmophyte Score (CTSS) was assessed. Lumbar spinal mobility was evaluated using the modified Schober test. Functional impairment was measured using the Bath AS functional index (BASFI). RESULTS: The ICCs of ankylosed facet joint scores at the cervical, thoracic, lumbar and whole spine were 0.84, 0.88, 0.92 and 0.90, respectively. Facet joint ankylosis was most common in the thoracic spine. Scores for the whole spine correlated positively with the ASDAS, mSASSS and the syndesmophyte score. Multivariate analysis revealed that facet joint ankylosis was significantly associated with decreased lumbar motion. For both readers, the scores for the whole spine were independently associated with BASFI after adjusting for syndesmophyte score and disease activity. CONCLUSIONS: Facet joint ankylosis in patients with r-axSpA was associated with functional impairment and spinal mobility. Facet joints should be incorporated into a structural damage assessment method.