A retrospective external validation study of the Birmingham Atypical Cartilage Tumour Imaging Protocol (BACTIP) for the management of solitary central cartilage tumours of the proximal humerus and around the knee.

OBJECTIVES: This study aimed to externally validate the Birmingham Atypical Cartilage Tumour Imaging Protocol (BACTIP) recommendations for differentiation/follow-up of central cartilage tumours (CCTs) of the proximal humerus, distal femur, and proximal tibia and to propose BACTIP adaptations if the results provide new insights. METHODS: MRIs of 123 patients (45 ± 11 years, 37 men) with an untreated CCT with MRI follow-up (n = 62) or histopathological confirmation (n = 61) were retrospectively/consecutively included and categorised following the BACTIP (2003-2020 / Ghent University Hospital/Belgium). Tumour length and endosteal scalloping differences between enchondroma, atypical cartilaginous tumour (ACT), and high-grade chondrosarcoma (CS II/III/dedifferentiated) were evaluated. ROC-curve analysis for differentiating benign from malignant CCTs and for evaluating the BACTIP was performed. RESULTS: For lesion length and endosteal scalloping, ROC-AUCs were poor and fair-excellent, respectively, for differentiating different CCT groups (0.59-0.69 versus 0.73-0.91). The diagnostic performance of endosteal scalloping and the BACTIP was higher than that of lesion length. A 1° endosteal scalloping cut-off differentiated enchondroma from ACT + high-grade chondrosarcoma with a sensitivity of 90%, reducing the potential diagnostic delay. However, the specificity was 29%, inducing overmedicalisation (excessive follow-up). ROC-AUC of the BACTIP was poor for differentiating enchondroma from ACT (ROC-AUC = 0.69; 95%CI = 0.51-0.87; p = 0.041) and fair-good for differentiation between other CCT groups (ROC-AUC = 0.72-0.81). BACTIP recommendations were incorrect/unsafe in five ACTs and one CSII, potentially inducing diagnostic delay. Eleven enchondromas received unnecessary referrals/follow-up. CONCLUSION: Although promising as a useful tool for management/follow-up of CCTs of the proximal humerus, distal femur, and proximal tibia, five ACTs and one chondrosarcoma grade II were discharged, potentially inducing diagnostic delay, which could be reduced by adapting BACTIP cut-off values. CLINICAL RELEVANCE STATEMENT: Mostly, Birmingham Atypical Cartilage Tumour Imaging Protocol (BACTIP) assesses central cartilage tumours of the proximal humerus and the knee correctly. Both when using the BACTIP and when adapting cut-offs, caution should be taken for the trade-off between underdiagnosis/potential diagnostic delay in chondrosarcomas and overmedicalisation in enchondromas. KEY POINTS: • This retrospective external validation confirms the Birmingham Atypical Cartilage Tumour Imaging Protocol as a useful tool for initial assessment and follow-up recommendation of central cartilage tumours in the proximal humerus and around the knee in the majority of cases. • Using only the Birmingham Atypical Cartilage Tumour Imaging Protocol, both atypical cartilaginous tumours and high-grade chondrosarcomas (grade II, grade III, and dedifferentiated chondrosarcomas) can be misdiagnosed, excluding them from specialist referral and further follow-up, thus creating a potential risk of delayed diagnosis and worse prognosis. • Adapted cut-offs to maximise detection of atypical cartilaginous tumours and high-grade chondrosarcomas, minimise underdiagnosis and reduce potential diagnostic delay in malignant tumours but increase unnecessary referral and follow-up of benign tumours.

Diagnosis and monitoring denosumab therapy of giant cell tumors of bone: radiologic-pathologic correlation.

OBJECTIVE: To determine the value of CT and dynamic contrast-enhanced (DCE-)MRI for monitoring denosumab therapy of giant cell tumors of bone (GCTB) by correlating it to histopathology. MATERIALS AND METHODS: Patients with GCTB under denosumab treatment and monitored with CT and (DCE-)MRI (2012-2021) were retrospectively included. Imaging and (semi-)quantitative measurements were used to assess response/relapse. Tissue samples were analyzed using computerized segmentation for vascularization and number of neoplastic and giant cells. Pearson's correlation/Spearman's rank coefficient and Kruskal-Wallis tests were used to assess correlations between histopathology and radiology. RESULTS: Six patients (28 ± 8years; five men) were evaluated. On CT, good responders showed progressive re-ossification (+7.8HU/month) and cortical remodeling (woven bone). MRI showed an SI decrease relative to muscle on T1-weighted (-0.01 A.U./month) and on fat-saturated T2-weighted sequences (-0.03 A.U./month). Time-intensity-curves evolved from a type IV with high first pass, high amplitude, and steep wash-out to a slow type II. An increase in time-to-peak (+100%) and a decrease in Ktrans (-71%) were observed. This is consistent with microscopic examination, showing a decrease of giant cells (-76%), neoplastic cells (-63%), and blood vessels (-28%). There was a strong statistical significant inverse correlation between time-to-peak and microvessel density (ρ = -0.9, p = 0.01). Significantly less neoplastic (p = 0.03) and giant cells (p = 0.04) were found with a time-intensity curve type II, compared to a type IV. Two patients showed relapse after initial good response when stopping denosumab. Inverse imaging and pathological findings were observed. CONCLUSION: CT and (DCE-)MRI show a good correlation with pathology and allow adequate evaluation of response to denosumab and detection of therapy failure.

Evaluation of response to neoadjuvant chemotherapy in osteosarcoma using dynamic contrast-enhanced MRI: development and external validation of a model.

OBJECTIVE: To identify which dynamic contrast-enhanced (DCE-)MRI features best predict histological response to neoadjuvant chemotherapy in patients with an osteosarcoma. METHODS: Patients with osteosarcoma who underwent DCE-MRI before and after neoadjuvant chemotherapy prior to resection were retrospectively included at two different centers. Data from the center with the larger cohort (training cohort) was used to identify which method for region-of-interest selection (whole slab or focal area method) and which change in DCE-MRI features (time to enhancement, wash-in rate, maximum relative enhancement and area under the curve) gave the most accurate prediction of histological response. Models were created using logistic regression and cross-validated. The most accurate model was then externally validated using data from the other center (test cohort). RESULTS: Fifty-five (27 poor response) and 30 (19 poor response) patients were included in training and test cohorts, respectively. Intraclass correlation coefficient of relative DCE-MRI features ranged 0.81-0.97 with the whole slab and 0.57-0.85 with the focal area segmentation method. Poor histological response was best predicted with the whole slab segmentation method using a single feature threshold, relative wash-in rate <2.3. Mean accuracy was 0.85 (95%CI: 0.75-0.95), and area under the receiver operating characteristic curve (AUC-index) was 0.93 (95%CI: 0.86-1.00). In external validation, accuracy and AUC-index were 0.80 and 0.80. CONCLUSION: In this study, a relative wash-in rate of <2.3 determined with the whole slab segmentation method predicted histological response to neoadjuvant chemotherapy in osteosarcoma. Consistent performance was observed in an external test cohort.

Neural network algorithm for detection of erosions and ankylosis on CT of the sacroiliac joints: multicentre development and validation of diagnostic accuracy.

OBJECTIVES: To evaluate the feasibility and diagnostic accuracy of a deep learning network for detection of structural lesions of sacroiliitis on multicentre pelvic CT scans. METHODS: Pelvic CT scans of 145 patients (81 female, 121 Ghent University/24 Alberta University, 18-87 years old, mean 40 ± 13 years, 2005-2021) with a clinical suspicion of sacroiliitis were retrospectively included. After manual sacroiliac joint (SIJ) segmentation and structural lesion annotation, a U-Net for SIJ segmentation and two separate convolutional neural networks (CNN) for erosion and ankylosis detection were trained. In-training validation and tenfold validation testing (U-Net-n = 10 × 58; CNN-n = 10 × 29) on a test dataset were performed to assess performance on a slice-by-slice and patient level (dice coefficient/accuracy/sensitivity/specificity/positive and negative predictive value/ROC AUC). Patient-level optimisation was applied to increase the performance regarding predefined statistical metrics. Gradient-weighted class activation mapping (Grad-CAM++) heatmap explainability analysis highlighted image parts with statistically important regions for algorithmic decisions. RESULTS: Regarding SIJ segmentation, a dice coefficient of 0.75 was obtained in the test dataset. For slice-by-slice structural lesion detection, a sensitivity/specificity/ROC AUC of 95%/89%/0.92 and 93%/91%/0.91 were obtained in the test dataset for erosion and ankylosis detection, respectively. For patient-level lesion detection after pipeline optimisation for predefined statistical metrics, a sensitivity/specificity of 95%/85% and 82%/97% were obtained for erosion and ankylosis detection, respectively. Grad-CAM++ explainability analysis highlighted cortical edges as focus for pipeline decisions. CONCLUSIONS: An optimised deep learning pipeline, including an explainability analysis, detects structural lesions of sacroiliitis on pelvic CT scans with excellent statistical performance on a slice-by-slice and patient level. CLINICAL RELEVANCE STATEMENT: An optimised deep learning pipeline, including a robust explainability analysis, detects structural lesions of sacroiliitis on pelvic CT scans with excellent statistical metrics on a slice-by-slice and patient level. KEY POINTS: • Structural lesions of sacroiliitis can be detected automatically in pelvic CT scans. • Both automatic segmentation and disease detection yield excellent statistical outcome metrics. • The algorithm takes decisions based on cortical edges, rendering an explainable solution.

Erdheim-Chester disease: diffusion-weighted imaging and dynamic contrast-enhanced MRI provide useful information.

This is, to our knowledge, the first case report with in-depth analysis of bone marrow and bone lesions with diffusion-weighted imaging and dynamic contrast-enhanced MRI in Erdheim-Chester disease to date. We present a case of a 70-year-old woman who was referred for an X-ray of the pelvis, right femur and right knee after complaints of migratory arthralgia in hip and knee five months after an initial hip and knee trauma. Bone lesions on X-ray were identified. This case report highlights the strength and complementary use of modern multimodality multiparametric imaging techniques in the clinical radiological manifestations of Erdheim-Chester disease, in the differential diagnosis and in treatment response assessment, which is classically performed using 18FDG PET-CT. Erdheim-Chester disease is a rare form of non-Langerhans' cell histiocytosis, mainly affecting individuals in their fifth-seventh decade of life and without sex predominance. Apart from the typical bilateral symmetric lesions in long bone diaphyseal and metaphyseal regions and classically sparing the epiphyses, this multisystemic disease causes significant morbidity by infiltrating critical organs (the central nervous system, cardiovascular system, retroperitoneum, lungs and skin). With non-traumatic bone pain being the most common complaint, Erdheim-Chester disease is diagnosed most often in an incidental setting on imaging. The imaging workup classically consists of a multimodality approach using conventional radiography, CT, MRI, bone scintigraphy and 18FDG PET-CT. This case report extends this evaluation with diffusion-weighted imaging and dynamic contrast-enhanced imaging techniques.

MRI-based synthetic CT of the hip: can it be an alternative to conventional CT in the evaluation of osseous morphology?

OBJECTIVES: MRI is the gold standard for soft tissue evaluation in the hip joint. However, CT is superior to MRI in providing clear visualization of bony morphology. The aim of this study is to test the equivalency of MRI-based synthetic CT to conventional CT in quantitatively assessing bony morphology of the hip. MATERIALS AND METHODS: A prospective study was performed. Adult patients who underwent MRI and CT of the hips were included. Synthetic CT images were generated from MRI using a deep learning-based image synthesis method. Two readers independently performed clinically relevant measurements for hip morphology, including anterior and posterior acetabular sector angle, acetabular version angle, joint space width, lateral center-edge angle, sharp angle, alpha angle, and femoral head-neck offset on synthetic CT and CT. Inter-method, inter-reader, and intra-reader reliability and agreement were assessed using calculations of intraclass correlation coefficient, standard error of measurement, and smallest detectable change. The equivalency among CT and synthetic CT was evaluated using equivalency statistical testing. RESULTS: Fifty-four hips from twenty-seven participants were included. There was no reported hip pathology in the subjects. The observed agreement based on reliability and agreement parameters indicated a strong degree of concordance between CT and synthetic CT. Equivalence statistical testing showed that all synthetic CT measurements are equivalent to the CT measurements at the considered margins. CONCLUSION: In healthy individuals, we demonstrated equivalency of MRI-based synthetic CT to conventional CT for the quantitative evaluation of osseous hip morphology, thus obviating the radiation exposure of a pelvic CT examination. KEY POINTS: •MRI-based synthetic CT images can be generated from MRI using a deep learning-based image synthesis method. •MRI-based synthetic CT is equivalent to CT in the quantitative assessment of bony hip morphology in healthy individuals. •MRI-based synthetic CT is promising for use in preoperative diagnosis and surgery planning.

Review of diffusion-weighted imaging and dynamic contrast-enhanced MRI for multiple myeloma and its precursors (monoclonal gammopathy of undetermined significance and smouldering myeloma).

The last decades, increasing research has been conducted on dynamic contrast-enhanced and diffusion-weighted MRI techniques in multiple myeloma and its precursors. Apart from anatomical sequences which are prone to interpretation errors due to anatomical variants, other pathologies and subjective evaluation of signal intensities, dynamic contrast-enhanced and diffusion-weighted MRI provide additional information on microenvironmental changes in bone marrow and are helpful in the diagnosis, staging and follow-up of plasma cell dyscrasias. Diffusion-weighted imaging provides information on diffusion (restriction) of water molecules in bone marrow and in malignant infiltration. Qualitative evaluation by visually assessing images with different diffusion sensitising gradients and quantitative evaluation of the apparent diffusion coefficient are studied extensively. Dynamic contrast-enhanced imaging provides information on bone marrow vascularisation, perfusion, capillary resistance, vascular permeability and interstitial space, which are systematically altered in different disease stages and can be evaluated in a qualitative and a (semi-)quantitative manner. Both diffusion restriction and abnormal dynamic contrast-enhanced MRI parameters are early biomarkers of malignancy or disease progression in focal lesions or in regions with diffuse abnormal signal intensities. The added value for both techniques lies in better detection and/or characterisation of abnormal bone marrow otherwise missed or misdiagnosed on anatomical MRI sequences. Increased detection rates of focal lesions or diffuse bone marrow infiltration upstage patients to higher disease stages, provide earlier access to therapy and slower disease progression and allow closer monitoring of high-risk patients. Despite promising results, variations in imaging protocols, scanner types and post-processing methods are large, thus hampering universal applicability and reproducibility of quantitative imaging parameters. The myeloma response assessment and diagnosis system and the international myeloma working group provide a systematic multicentre approach on imaging and propose which parameters to use in multiple myeloma and its precursors in an attempt to overcome the pitfalls of dynamic contrast-enhanced and diffusion-weighted imaging.Single sentence summary statementDiffusion-weighted imaging and dynamic contrast-enhanced MRI provide important additional information to standard anatomical MRI techniques for diagnosis, staging and follow-up of patients with plasma cell dyscrasias, although some precautions should be taken on standardisation of imaging protocols to improve reproducibility and application in multiple centres.

Imaging of treatment response and minimal residual disease in multiple myeloma: state of the art WB-MRI and PET/CT.

Bone imaging has been intimately associated with the diagnosis and staging of multiple myeloma (MM) for more than 5 decades, as the presence of bone lesions indicates advanced disease and dictates treatment initiation. The methods used have been evolving, and the historical radiographic skeletal survey has been replaced by whole body CT, whole body MRI (WB-MRI) and [18F]FDG-PET/CT for the detection of bone marrow lesions and less frequent extramedullary plasmacytomas.Beyond diagnosis, imaging methods are expected to provide the clinician with evaluation of the response to treatment. Imaging techniques are consistently challenged as treatments become more and more efficient, inducing profound response, with more subtle residual disease. WB-MRI and FDG-PET/CT are the methods of choice to address these challenges, being able to assess disease progression or response and to detect "minimal" residual disease, providing key prognostic information and guiding necessary change of treatment.This paper provides an up-to-date overview of the WB-MRI and PET/CT techniques, their observations in responsive and progressive disease and their role and limitations in capturing minimal residual disease. It reviews trials assessing these techniques for response evaluation, points out the limited comparisons between both methods and highlights their complementarity with most recent molecular methods (next-generation flow cytometry, next-generation sequencing) to detect minimal residual disease. It underlines the important role of PET/MRI technology as a research tool to compare the effectiveness and complementarity of both methods to address the key clinical questions.

Predicting cytogenetic risk in multiple myeloma using conventional whole-body MRI, spinal dynamic contrast-enhanced MRI, and spinal diffusion-weighted imaging.

OBJECTIVES: Cytogenetic abnormalities are predictors of poor prognosis in multiple myeloma (MM). This paper aims to build and validate a multiparametric conventional and functional whole-body MRI-based prediction model for cytogenetic risk classification in newly diagnosed MM. METHODS: Patients with newly diagnosed MM who underwent multiparametric conventional whole-body MRI, spinal dynamic contrast-enhanced (DCE-)MRI, spinal diffusion-weighted MRI (DWI) and had genetic analysis were retrospectively included (2011-2020/Ghent University Hospital/Belgium). Patients were stratified into standard versus intermediate/high cytogenetic risk groups. After segmentation, 303 MRI features were extracted. Univariate and model-based methods were evaluated for feature and model selection. Testing was performed using receiver operating characteristic (ROC) and precision-recall curves. Models comparing the performance for genetic risk classification of the entire MRI protocol and of all MRI sequences separately were evaluated, including all features. Four final models, including only the top three most predictive features, were evaluated. RESULTS: Thirty-one patients were enrolled (mean age 66 ± 7 years, 15 men, 13 intermediate-/high-risk genetics). None of the univariate models and none of the models with all features included achieved good performance. The best performing model with only the three most predictive features and including all MRI sequences reached a ROC-area-under-the-curve of 0.80 and precision-recall-area-under-the-curve of 0.79. The highest statistical performance was reached when all three MRI sequences were combined (conventional whole-body MRI + DCE-MRI + DWI). Conventional MRI always outperformed the other sequences. DCE-MRI always outperformed DWI, except for specificity. CONCLUSIONS: A multiparametric MRI-based model has a better performance in the noninvasive prediction of high-risk cytogenetics in newly diagnosed MM than conventional MRI alone. CRITICAL RELEVANCE STATEMENT: An elaborate multiparametric MRI-based model performs better than conventional MRI alone for the noninvasive prediction of high-risk cytogenetics in newly diagnosed multiple myeloma; this opens opportunities to assess genetic heterogeneity thus overcoming sampling bias. KEY POINTS: • Standard genetic techniques in multiple myeloma patients suffer from sampling bias due to tumoral heterogeneity. • Multiparametric MRI noninvasively predicts genetic risk in multiple myeloma. • Combined conventional anatomical MRI, DCE-MRI, and DWI had the highest statistical performance to predict genetic risk. • Conventional MRI alone always outperformed DCE-MRI and DWI separately to predict genetic risk. DCE-MRI alone always outperformed DWI separately, except for the parameter specificity to predict genetic risk. • This multiparametric MRI-based genetic risk prediction model opens opportunities to noninvasively assess genetic heterogeneity thereby overcoming sampling bias in predicting genetic risk in multiple myeloma.

Relative Wash-In Rate in Dynamic Contrast-Enhanced Magnetic Resonance Imaging as a New Prognostic Biomarker for Event-Free Survival in 82 Patients with Osteosarcoma: A Multicenter Study.

BACKGROUND: The decreased perfusion of osteosarcoma in dynamic contrast-enhanced (DCE) MRI, reflecting a good histological response to neoadjuvant chemotherapy, has been described. PURPOSE: In this study, we aim to explore the potential of the relative wash-in rate as a prognostic factor for event-free survival (EFS). METHODS: Skeletal high-grade osteosarcoma patients, treated in two tertiary referral centers between 2005 and 2022, were retrospectively included. The relative wash-in rate (rWIR) was determined with DCE-MRI before, after, or during the second cycle of chemotherapy (pre-resection). A previously determined cut-off was used to categorize patients, where rWIR < 2.3 was considered poor and rWIR ≥ 2.3 a good radiological response. EFS was defined as the time from resection to the first event: local recurrence, new metastases, or tumor-related death. EFS was estimated using Kaplan-Meier's methodology. Multivariate Cox proportional hazard model was used to estimate the effect of histological response and rWIR on EFS, adjusted for traditional prognostic factors. RESULTS: Eighty-two patients (median age: 17 years; IQR: 14-28) were included. The median follow-up duration was 11.8 years (95% CI: 11.0-12.7). During follow-up, 33 events occurred. Poor histological response was not significantly associated with EFS (HR: 1.8; 95% CI: 0.9-3.8), whereas a poor radiological response was associated with a worse EFS (HR: 2.4; 95% CI: 1.1-5.0). In a subpopulation without initial metastases, the binary assessment of rWIR approached statistical significance (HR: 2.3; 95% CI: 1.0-5.2), whereas its continuous evaluation demonstrated a significant association between higher rWIR and improved EFS (HR: 0.7; 95% CI: 0.5-0.9), underlining the effect of response to chemotherapy. The 2- and 5-year EFS for patients with a rWIR ≥ 2.3 were 85% and 75% versus 55% and 50% for patients with a rWIR < 2.3. CONCLUSION: The predicted poor chemo response with MRI (rWIR < 2.3) is associated with shorter EFS even when adjusted for known clinical covariates and shows similar results to histological response evaluation. rWIR is a potential tool for future response-based individualized healthcare in osteosarcoma patients before surgical resection.

Machine Learning Pipeline for Predicting Bone Marrow Edema Along the Sacroiliac Joints on Magnetic Resonance Imaging.

OBJECTIVE: We aimed to develop and validate a fully automated machine learning (ML) algorithm that predicts bone marrow edema (BME) on a quadrant level in sacroiliac (SI) joint magnetic resonance imaging (MRI). METHODS: A computer vision workflow automatically locates the SI joints, segments regions of interest (ilium and sacrum), performs objective quadrant extraction, and predicts presence of BME, suggestive of inflammatory lesions, on a quadrant level in semicoronal slices of T1/T2-weighted MRI scans. Ground truth was determined by consensus among human readers. The inflammation classifier was trained using a ResNet18 backbone and five-fold cross-validated on scans of patients with spondyloarthritis (SpA) (n = 279), postpartum individuals (n = 71), and healthy subjects (n = 114). Independent SpA patient MRI scans (n = 243) served as test data set. Patient-level predictions were derived from aggregating quadrant-level predictions, ie, at least one positive quadrant. RESULTS: The algorithm automatically detects the SI joints with a precision of 98.4% and segments ilium/sacrum with an intersection over union of 85.6% and 67.9%, respectively. The inflammation classifier performed well in cross-validation: area under the curve (AUC) 94.5%, balanced accuracy (B-ACC) 80.5%, and F1 score 64.1%. In the test data set, AUC was 88.2%, B-ACC 72.1%, and F1 score 50.8%. On a patient level, the model achieved a B-ACC of 81.6% and 81.4% in the cross-validation and test data set, respectively. CONCLUSION: We propose a fully automated ML pipeline that enables objective and standardized evaluation of BME along the SI joints on MRI. This method has the potential to screen large numbers of patients with (suspected) SpA and is a step closer towards artificial intelligence-assisted diagnosis and follow-up.

Blurring and Irregularity of the Subchondral Cortex in Pediatric Sacroiliac Joints on T1 Images: Incidence of Normal Findings That Can Mimic Erosions.

OBJECTIVE: To determine prevalence of variations of subchondral bone appearance that may mimic erosions on T1-weighted magnetic resonance imaging (MRI) of pediatric sacroiliac (SI) joints according to age and sex. METHODS: With ethics committee approval and informed consent, SI joint MRIs of 251 children (132 girls), mean age 12.4 years (range 6.1-18.0 years), were obtained in 2 cohorts: 127 children imaged for nonrheumatic reasons, and 124 children with low back pain but no features of sacroiliitis at initial clinical MRI review. MRIs were reviewed by 3 experienced radiologists, blinded from each other, for 3 features of the cortical black line representing the subchondral bone plate on T1-weighted MRI: visibility, blurring, and irregularity. RESULTS: Based on agreement from 2 or more readers, the cortical black line was partially absent in 88.4% of the children, blurred in 34.7%, and irregular in 41.4%. All these features were most common on the iliac side of SI joints and at the first sacral vertebra level. Clearly visualized, sharply delineated SI joints with none of these features were seen in only 8.0% of children, or in 35.1% if we conservatively required agreement of all 3 readers to consider a feature present. There was no significant difference between sexes or cohorts; findings were similar across pediatric age groups. CONCLUSION: Understanding the normal MRI appearance of the developing SI joint is necessary to distinguish physiologic findings from disease. At least two-thirds (65%) of normal pediatric SI joints showed at least 1 feature that is a component of the adult definition of SI joint erosions, risking overdiagnosis of sacroiliitis.

Proton density fat fraction (PDFF) maps aid fat metaplasia evaluation in the sacroiliac joints in additional to T1WI: Improved diagnostic accuracy in axial spondyloarthritis.

PURPOSE: To evaluate the added value of qualitative and quantitative fat metaplasia analysis using proton-density fat fraction (PDFF) map in additional to T1-weighted imaging (T1WI) of the sacroiliac joints (SIJ) for diagnosis of axial spondyloarthritis (axSpA). METHOD: Patients aged 18-45 years with axSpA were enrolled. Non-SpA patients and healthy volunteers were included as controls. All participants underwent 3.0T MRI of the SIJs including semi-coronal T1WI and semi-coronal chemical-shift encoded MRI sequence for generating PDFF map. Each joint was divided into four quadrants for analysis. Two independent readers scored fat metaplasia on T1WI alone or with additional PDFF map and measured PDFF values in different reading sessions. Using clinical diagnosis as the reference, diagnostic accuracy of visual scores and PDFF measurements was evaluated by area under the receiver operating characteristic curve (AUC). Inter-reader agreement was evaluated by the intra-class correlation coefficient (ICC). RESULTS: Forty-nine patients with axSpA and thirty-six controls were included. Qualitative fat metaplasia scores using additional PDFF map performed better than using T1WI alone (AUC: Reader 1, 0.847 vs 0.795, p = 0.082; Reader 2, 0.785 vs 0.719, p = 0.048). AUCs of quantitative analysis using number of quadrants with PDFF value ≥75 % were higher than qualitative analysis using T1WI alone (Reader 1, 0.863 vs 0.795, p = 0.046; Reader 2, 0.823 vs 0.785, p = 0.011). ICCs were 0.854 to 0.922 for qualitative analysis and 0.935 for quantitative analysis. CONCLUSIONS: Additional PDFF map can increase the diagnostic accuracy for axSpA by qualitative and quantitative fat metaplasia analysis, in comparison to using T1WI alone.

The influence of cerebrospinal fluid on blood coagulation and the implications for ventriculovenous shunting.

OBJECTIVE: The effect of CSF on blood coagulation is not known. Enhanced coagulation by CSF may be an issue in thrombotic complications of ventriculoatrial and ventriculosinus shunts. This study aimed to assess the effect of CSF on coagulation and its potential effect on thrombotic events affecting ventriculovenous shunts. METHODS: Two complementary experiments were performed. In a static experiment, the effect on coagulation of different CSF mixtures was evaluated using a viscoelastic coagulation monitor. A dynamic experiment confirmed the amount of clot formation on the shunt surface in a roller pump model. RESULTS: CSF concentrations of 9% and higher significantly decreased the activated clotting time (ACT; 164.9 seconds at 0% CSF, 155.6 seconds at 9% CSF, and 145.1 seconds at 32% CSF). Increased clot rates (CRs) were observed starting at a concentration of 5% (29.3 U/min at 0% CSF, 31.6 U/min at 5% CSF, and 35.3 U/min at 32% CSF). The roller pump model showed a significantly greater percentage of shunt surface covered with deposits when the shunts were infused with CSF rather than Ringer's lactate solution (90% vs 63%). The amount of clot formation at the side facing the blood flow (impact side) tended to be lower than that at the side facing away from the blood flow (wake side; 71% vs 86%). CONCLUSIONS: Addition of CSF to blood accelerates coagulation. The CSF-blood-foreign material interaction promotes clot formation, which might result in thrombotic shunt complications. Further development of the ventriculovenous shunt technique should focus on preventing CSF-blood-foreign material interaction and stagnation of CSF in wake zones.