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Van Den Berghe T, Delbare F, Candries E, Lejoly M, Algoet C, Chen M, Laloo F, Huysse WCJ, Creytens D, Verstraete KL. 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. Eur Radiol 2024:10.1007/s00330-024-10604-y. [PMID: 38319428 DOI: 10.1007/s00330-024-10604-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 12/01/2023] [Accepted: 12/20/2023] [Indexed: 02/07/2024]
Abstract
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.
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Affiliation(s)
- Thomas Van Den Berghe
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium.
- Department of Diagnostic Sciences, Ghent University, Sint-Pietersnieuwstraat 25, 9000, Ghent, Belgium.
| | - Felix Delbare
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Sint-Pietersnieuwstraat 25, 9000, Ghent, Belgium
| | - Esther Candries
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Sint-Pietersnieuwstraat 25, 9000, Ghent, Belgium
| | - Maryse Lejoly
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Sint-Pietersnieuwstraat 25, 9000, Ghent, Belgium
| | - Chloé Algoet
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Sint-Pietersnieuwstraat 25, 9000, Ghent, Belgium
| | - Min Chen
- Department of Radiology, Peking University Shenzhen Hospital, Shenzhen, 518036, China
| | - Frederiek Laloo
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Sint-Pietersnieuwstraat 25, 9000, Ghent, Belgium
| | - Wouter C J Huysse
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Sint-Pietersnieuwstraat 25, 9000, Ghent, Belgium
| | - David Creytens
- Department of Pathology, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Koenraad L Verstraete
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Sint-Pietersnieuwstraat 25, 9000, Ghent, Belgium
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Lejoly M, Van Den Berghe T, Creytens D, Huysse W, Lapeire L, Sys G, Verstraete K. Diagnosis and monitoring denosumab therapy of giant cell tumors of bone: radiologic-pathologic correlation. Skeletal Radiol 2024; 53:353-364. [PMID: 37515643 DOI: 10.1007/s00256-023-04403-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 07/10/2023] [Accepted: 07/10/2023] [Indexed: 07/31/2023]
Abstract
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.
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Affiliation(s)
- Maryse Lejoly
- Department of Radiology and Medical Imaging, Ghent University Hospital, 1K12/Entrance 12 Route 1590, Corneel Heymanslaan 10, B-9000, Ghent, Belgium.
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium.
| | - Thomas Van Den Berghe
- Department of Radiology and Medical Imaging, Ghent University Hospital, 1K12/Entrance 12 Route 1590, Corneel Heymanslaan 10, B-9000, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - David Creytens
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Department of Pathology, Ghent University Hospital, Ghent, Belgium
| | - Wouter Huysse
- Department of Radiology and Medical Imaging, Ghent University Hospital, 1K12/Entrance 12 Route 1590, Corneel Heymanslaan 10, B-9000, Ghent, Belgium
| | - Lore Lapeire
- Department of Medical Oncology, Ghent University Hospital, Ghent University, Ghent, Belgium
| | - Gwen Sys
- Department of Orthopedics and Traumatology, Ghent University Hospital, Ghent University, Ghent, Belgium
| | - Koenraad Verstraete
- Department of Radiology and Medical Imaging, Ghent University Hospital, 1K12/Entrance 12 Route 1590, Corneel Heymanslaan 10, B-9000, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
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Kalisvaart GM, Van Den Berghe T, Grootjans W, Lejoly M, Huysse WCJ, Bovée JVMG, Creytens D, Gelderblom H, Speetjens FM, Lapeire L, van de Sande MAJ, Sys G, de Geus-Oei LF, Verstraete KL, Bloem JL. Evaluation of response to neoadjuvant chemotherapy in osteosarcoma using dynamic contrast-enhanced MRI: development and external validation of a model. Skeletal Radiol 2024; 53:319-328. [PMID: 37464020 PMCID: PMC10730632 DOI: 10.1007/s00256-023-04402-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 07/03/2023] [Accepted: 07/04/2023] [Indexed: 07/20/2023]
Abstract
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.
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Affiliation(s)
- Gijsbert M Kalisvaart
- Department of Radiology and Nuclear Medicine, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands.
| | - Thomas Van Den Berghe
- Department of Radiology and Medical Imaging, Ghent University Hospital, Ghent, Belgium
| | - Willem Grootjans
- Department of Radiology and Nuclear Medicine, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - Maryse Lejoly
- Department of Radiology and Medical Imaging, Ghent University Hospital, Ghent, Belgium
| | - Wouter C J Huysse
- Department of Radiology and Medical Imaging, Ghent University Hospital, Ghent, Belgium
| | - Judith V M G Bovée
- Department of Pathology, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - David Creytens
- Department of Pathology, Ghent University Hospital, Ghent, Belgium
| | - Hans Gelderblom
- Department of Medical Oncology, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - Frank M Speetjens
- Department of Medical Oncology, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - Lore Lapeire
- Department of Medical Oncology, Ghent University Hospital, Ghent, Belgium
| | - Michiel A J van de Sande
- Department of Orthopedics, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - Gwen Sys
- Department of Orthopedics, Ghent University Hospital, Ghent, Belgium
| | - Lioe-Fee de Geus-Oei
- Department of Radiology and Nuclear Medicine, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - Koenraad L Verstraete
- Department of Radiology and Medical Imaging, Ghent University Hospital, Ghent, Belgium
| | - Johan L Bloem
- Department of Radiology and Nuclear Medicine, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
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Roels J, De Craemer AS, Renson T, de Hooge M, Gevaert A, Van Den Berghe T, Jans L, Herregods N, Carron P, Van den Bosch F, Saeys Y, Elewaut D. Machine Learning Pipeline for Predicting Bone Marrow Edema Along the Sacroiliac Joints on Magnetic Resonance Imaging. Arthritis Rheumatol 2023; 75:2169-2177. [PMID: 37410803 DOI: 10.1002/art.42650] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 06/22/2023] [Accepted: 06/26/2023] [Indexed: 07/08/2023]
Abstract
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.
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Affiliation(s)
- Joris Roels
- Vlaams Instituut voor Biotechnologie - Universiteit Gent (VIB-UGent), Ghent-Zwijnaarde, and Ghent University, Ghent, Belgium
| | - Ann-Sophie De Craemer
- Vlaams Instituut voor Biotechnologie - Universiteit Gent (VIB-UGent), Ghent-Zwijnaarde, and Ghent University Hospital, Ghent, Belgium
| | - Thomas Renson
- Vlaams Instituut voor Biotechnologie - Universiteit Gent (VIB-UGent), Ghent-Zwijnaarde, and Ghent University Hospital, Ghent, Belgium
| | - Manouk de Hooge
- Vlaams Instituut voor Biotechnologie - Universiteit Gent (VIB-UGent), Ghent-Zwijnaarde, and Ghent University Hospital, Ghent, Belgium
| | - Arne Gevaert
- Vlaams Instituut voor Biotechnologie - Universiteit Gent (VIB-UGent), Ghent-Zwijnaarde, and Ghent University, Ghent, Belgium
| | | | | | | | - Philippe Carron
- Vlaams Instituut voor Biotechnologie - Universiteit Gent (VIB-UGent), Ghent-Zwijnaarde, and Ghent University Hospital, Ghent, Belgium
| | - Filip Van den Bosch
- Vlaams Instituut voor Biotechnologie - Universiteit Gent (VIB-UGent), Ghent-Zwijnaarde, and Ghent University Hospital, Ghent, Belgium
| | - Yvan Saeys
- Vlaams Instituut voor Biotechnologie - Universiteit Gent (VIB-UGent), Ghent-Zwijnaarde, and Ghent University, Ghent, Belgium
| | - Dirk Elewaut
- Vlaams Instituut voor Biotechnologie - Universiteit Gent (VIB-UGent), Ghent-Zwijnaarde, and Ghent University Hospital, Ghent, Belgium
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Van Den Berghe T, Babin D, Chen M, Callens M, Brack D, Maes H, Lievens J, Lammens M, Van Sumere M, Morbée L, Hautekeete S, Schatteman S, Jacobs T, Thooft WJ, Herregods N, Huysse W, Jaremko JL, Lambert R, Maksymowych W, Laloo F, Baraliakos X, De Craemer AS, Carron P, Van den Bosch F, Elewaut D, Jans L. Neural network algorithm for detection of erosions and ankylosis on CT of the sacroiliac joints: multicentre development and validation of diagnostic accuracy. Eur Radiol 2023; 33:8310-8323. [PMID: 37219619 DOI: 10.1007/s00330-023-09704-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 03/03/2023] [Accepted: 03/25/2023] [Indexed: 05/24/2023]
Abstract
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.
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Affiliation(s)
- Thomas Van Den Berghe
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium.
| | - Danilo Babin
- Department of Telecommunication and Information Processing - Image Processing and Interpretation (TELIN-IPI), Faculty of Engineering and Architecture, Ghent University - IMEC, Sint-Pietersnieuwstraat 41, 9000, Ghent, Belgium
| | - Min Chen
- Department of Radiology, Peking University Shenzhen Hospital, Shenzhen, 518036, China
| | - Martijn Callens
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Denim Brack
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Helena Maes
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Jan Lievens
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Marie Lammens
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Maxime Van Sumere
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Lieve Morbée
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Simon Hautekeete
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Stijn Schatteman
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Tom Jacobs
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Willem-Jan Thooft
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Nele Herregods
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Wouter Huysse
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Jacob L Jaremko
- Department of Radiology and Diagnostic Imaging and Rheumatology, University of Alberta, 8440 122 Street NW, Edmonton, Alberta, T6G 2B7, Canada
| | - Robert Lambert
- Department of Radiology and Diagnostic Imaging and Rheumatology, University of Alberta, 8440 122 Street NW, Edmonton, Alberta, T6G 2B7, Canada
| | - Walter Maksymowych
- Department of Radiology and Diagnostic Imaging and Rheumatology, University of Alberta, 8440 122 Street NW, Edmonton, Alberta, T6G 2B7, Canada
| | - Frederiek Laloo
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Xenofon Baraliakos
- Rheumazentrum Ruhrgebiet Herne, Ruhr-University Bochum, Claudiusstraße 45, 44649, Herne, Germany
| | - Ann-Sophie De Craemer
- Department of Rheumatology, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
- Vlaams Instituut voor Biotechnologie (VIB) Centre for Inflammation Research (IRC), Ghent University, Technologiepark 927, 9052, Ghent, Belgium
| | - Philippe Carron
- Department of Rheumatology, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
- Vlaams Instituut voor Biotechnologie (VIB) Centre for Inflammation Research (IRC), Ghent University, Technologiepark 927, 9052, Ghent, Belgium
| | - Filip Van den Bosch
- Department of Rheumatology, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
- Vlaams Instituut voor Biotechnologie (VIB) Centre for Inflammation Research (IRC), Ghent University, Technologiepark 927, 9052, Ghent, Belgium
| | - Dirk Elewaut
- Department of Rheumatology, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
- Vlaams Instituut voor Biotechnologie (VIB) Centre for Inflammation Research (IRC), Ghent University, Technologiepark 927, 9052, Ghent, Belgium
| | - Lennart Jans
- Department of Radiology and Medical Imaging, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
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Van Den Berghe T, Candries E, Everaert N, Saerens M, Van Dorpe J, Verstraete K. Erdheim-Chester disease: diffusion-weighted imaging and dynamic contrast-enhanced MRI provide useful information. Skeletal Radiol 2023:10.1007/s00256-022-04265-5. [PMID: 36602575 DOI: 10.1007/s00256-022-04265-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 12/09/2022] [Accepted: 12/12/2022] [Indexed: 01/06/2023]
Abstract
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.
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Affiliation(s)
- Thomas Van Den Berghe
- Department of Radiology, Ghent University Hospital and Ghent University, Ghent, Belgium.
| | - Esther Candries
- Department of Radiology, Ghent University Hospital and Ghent University, Ghent, Belgium
| | - Nicolas Everaert
- Department of Radiology, Ghent University Hospital and Ghent University, Ghent, Belgium
| | - Michael Saerens
- Department of Oncology, Ghent University Hospital and Ghent University, Ghent, Belgium
| | - Jo Van Dorpe
- Department of Pathology, Ghent University Hospital and Ghent University, Ghent, Belgium
| | - Koenraad Verstraete
- Department of Radiology, Ghent University Hospital and Ghent University, Ghent, Belgium
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Herregods N, Lambert RGW, Schiettecatte E, Dehoorne J, Renson T, Laloo F, Van Den Berghe T, Jans LBO, Jaremko JL. Blurring and Irregularity of the Subchondral Cortex in Pediatric Sacroiliac Joints on T1 Images: Incidence of Normal Findings That Can Mimic Erosions. Arthritis Care Res (Hoboken) 2023; 75:190-197. [PMID: 34235890 DOI: 10.1002/acr.24746] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 06/15/2021] [Accepted: 07/06/2021] [Indexed: 12/31/2022]
Abstract
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.
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Affiliation(s)
| | - Robert G W Lambert
- University of Alberta and Medical Imaging Consultants, Edmonton, Alberta, Canada
| | | | | | | | | | | | | | - Jacob L Jaremko
- University of Alberta and Medical Imaging Consultants, Edmonton, Alberta, Canada
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Morbée L, Chen M, Van Den Berghe T, Schiettecatte E, Gosselin R, Herregods N, Jans LBO. MRI-based synthetic CT of the hip: can it be an alternative to conventional CT in the evaluation of osseous morphology? Eur Radiol 2022; 32:3112-3120. [DOI: 10.1007/s00330-021-08442-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 10/12/2021] [Accepted: 10/25/2021] [Indexed: 12/13/2022]
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Lecouvet FE, Vekemans MC, Van Den Berghe T, Verstraete K, Kirchgesner T, Acid S, Malghem J, Wuts J, Hillengass J, Vandecaveye V, Jamar F, Gheysens O, Vande Berg BC. Imaging of treatment response and minimal residual disease in multiple myeloma: state of the art WB-MRI and PET/CT. Skeletal Radiol 2022; 51:59-80. [PMID: 34363522 PMCID: PMC8626399 DOI: 10.1007/s00256-021-03841-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 05/28/2021] [Accepted: 06/06/2021] [Indexed: 02/02/2023]
Abstract
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.
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Affiliation(s)
- Frederic E. Lecouvet
- Radiology Department, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, UCLouvain, Hippocrate Avenue 10, 1200 Brussels, Belgium
| | - Marie-Christiane Vekemans
- Haematology Unit, Cliniques Universitaires Saint-Luc, Institut de Recherche Expérimentale et Clinique (IREC), 1200 Brussels, Belgium
| | - Thomas Van Den Berghe
- Radiology Department, Universiteit Ghent, Sint-Pietersnieuwstraat 33, 9000 Gent, Belgium
| | - Koenraad Verstraete
- Radiology Department, Universiteit Ghent, Sint-Pietersnieuwstraat 33, 9000 Gent, Belgium
| | - Thomas Kirchgesner
- Radiology Department, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, UCLouvain, Hippocrate Avenue 10, 1200 Brussels, Belgium
| | - Souad Acid
- Radiology Department, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, UCLouvain, Hippocrate Avenue 10, 1200 Brussels, Belgium
| | - Jacques Malghem
- Radiology Department, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, UCLouvain, Hippocrate Avenue 10, 1200 Brussels, Belgium
| | - Joris Wuts
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, Avenue du Laerbeek 101, 1090 Jette, Belgium
| | - Jens Hillengass
- Departement of Medicine, Myeloma Unit, Park Comprehensive Cancer Center, Buffalo, NY USA
| | - Vincent Vandecaveye
- Radiology Department, Katholieke Univesiteit Leuven, Oude Markt, 13, 3000 Leuven, Belgium
| | - François Jamar
- Nuclear Medicine Department, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium
| | - Olivier Gheysens
- Nuclear Medicine Department, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium
| | - Bruno C. Vande Berg
- Radiology Department, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, UCLouvain, Hippocrate Avenue 10, 1200 Brussels, Belgium
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Vandersteene J, Baert E, Planckaert GMJ, Van Den Berghe T, Van Roost D, Dewaele F, Henrotte MMDM, De Somer F. The influence of cerebrospinal fluid on blood coagulation and the implications for ventriculovenous shunting. J Neurosurg 2018. [PMID: 29701547 DOI: 10.3171/2017.11.jns171510.] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVEThe 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.METHODSTwo 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.RESULTSCSF 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%).CONCLUSIONSAddition 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.
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Vandersteene J, Baert E, Planckaert GMJ, Van Den Berghe T, Van Roost D, Dewaele F, Henrotte MMDM, De Somer F. The influence of cerebrospinal fluid on blood coagulation and the implications for ventriculovenous shunting. J Neurosurg 2018:1-8. [PMID: 29701547 DOI: 10.3171/2017.11.jns171510] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2017] [Accepted: 11/04/2017] [Indexed: 11/06/2022]
Abstract
OBJECTIVEThe 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.METHODSTwo 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.RESULTSCSF 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%).CONCLUSIONSAddition 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.
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