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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; 34:4988-5006. [PMID: 38319428 DOI: 10.1007/s00330-024-10604-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [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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Hong R, Li Q, Ma J, Lu C, Zhong Z. Computed tomography-based radiomics machine learning models for differentiating enchondroma and atypical cartilaginous tumor in long bones. ROFO-FORTSCHR RONTG 2024. [PMID: 39074797 DOI: 10.1055/a-2344-5398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/31/2024]
Abstract
To explore the value of CT-based radiomics machine learning models for differentiating enchondroma from atypical cartilaginous tumor (ACT) in long bones and methods to improve model performance.59 enchondromas and 53 ACTs in long bones confirmed by pathology were collected retrospectively. The features were extracted from preoperative CT images of these patients, and least absolute shrinkage and selection operator (LASSO) regression was used for feature selection and dimensionality reduction. The selected features were used to construct classification models by thirteen machine learning algorithms. The data set was randomly divided into a training set and a test set at a proportion of 7:3 by ten-fold cross-validation to evaluate the performance of these models.A total of 1199 features were extracted, 9 features were selected, and 13 radiomics machine learning models were constructed. The area under the curve (AUC) of 11 models was more than 0.8, and that of 3 models was more than 0.9. The Extremely Randomized Trees model achieved the best performance (AUC = 0.9375 ± 0.0884), followed by the Adaptive Boosting model (AUC = 0.9188 ± 0.1010) and the Linear Discriminant Analysis model (AUC = 0.9062 ± 0.1459).CT-based radiomics machine learning models had great ability to distinguish enchondroma and ACT in long bones. By using filters to deeply mine high-order features in the original image and selecting appropriate machine learning algorithms, the performance of the model can be improved. · CT-based radiomics machine learning models can distinguish enchondroma and ACT in long bones.. · Using filters and selecting advanced machine learning algorithms can improve model performance.. · Clinical features have limited utility in distinguishing enchondroma and ACT in long bones.. · Hong R, Li Q, Ma J et al. Computed tomography-based radiomics machine learning models for differentiating enchondroma and atypical cartilaginous tumor in long bones. Fortschr Röntgenstr 2024; DOI 10.1055/a-2344-5398.
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Affiliation(s)
- Rui Hong
- Radiology, The Third Hospital of Hebei Medical University, Shijiazhuang, China
| | - Qian Li
- Radiology, The Third Hospital of Hebei Medical University, Shijiazhuang, China
| | - Jielin Ma
- Oncology, The Third Hospital of Hebei Medical University, Shijiazhuang, China
| | - Chunmiao Lu
- Radiology, The Third Hospital of Hebei Medical University, Shijiazhuang, China
| | - Zhiwei Zhong
- Radiology, The Third Hospital of Hebei Medical University, Shijiazhuang, China
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Breden S, Beischl S, Hinterwimmer F, Consalvo S, Lenze U, von Eisenhart-Rothe R, Pohlig F, Knebel C. Childhood Tumors around the Knee Revisited: Predilection Sites for Most Entities Confirmed. J Clin Med 2024; 13:4405. [PMID: 39124672 PMCID: PMC11313464 DOI: 10.3390/jcm13154405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2024] [Revised: 07/14/2024] [Accepted: 07/26/2024] [Indexed: 08/12/2024] Open
Abstract
Background: The diagnostic work-up of musculoskeletal tumors is a multifactorial process. During the early phase, differential diagnoses are made using basic radiological imaging. In this phase, part of the decision making is based on the patient's age, as well as the incidence and predilection sites of different entities. Unfortunately, this information is based on older and fragmented data. In this study, we retrospectively evaluated all soft-tissue and bone tumors around the knee in children treated at our tertiary center in the last 20 years, with the aim of verifying the data used today. Methods: In this retrospective study, the databank of our tertiary center was used to give an overview of treated tumors around the knee in children. Results: We were able to include 224 children with bone and soft-tissue tumors around the knee. The cohort consisted of 184 bone tumors, of which 144 were benign and 40 malignant. The 40 soft-tissue tumors comprised 30 benign and 10 malignant masses. The most common lesions were osteochondromas (88) in the bone and tenosynovial giant-cell tumors (12) in the soft tissue. Conclusions: With this original work, we were able to verify and supplement earlier studies, as well as deepen our insight into these very rare diseases.
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Affiliation(s)
- Sebastian Breden
- Department of Orthopedics and Sports Orthopedics, Klinikum Rechts der Isar, Technical University of Munich, 81675 Munich, Germany
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Yoon H, Lee SK, Kim JY, Joo MW. Quantitative Bone SPECT/CT of Central Cartilaginous Bone Tumors: Relationship between SUVmax and Radiodensity in Hounsfield Unit. Cancers (Basel) 2024; 16:1968. [PMID: 38893090 PMCID: PMC11171356 DOI: 10.3390/cancers16111968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 05/17/2024] [Accepted: 05/19/2024] [Indexed: 06/21/2024] Open
Abstract
(1) Background: it is challenging to determine the accurate grades of cartilaginous bone tumors. Using bone single photon emission computed tomography (SPECT)/computed tomography (CT), maximum standardized uptake value (SUVmax) was found to be significantly associated with different grades of cartilaginous bone tumor. The inquiry focused on the effect of the tumor matrix on SUVmax. (2) Methods: a total of 65 patients from 2017 to 2022 with central cartilaginous bone tumors, including enchondromas and low-to-intermediate grade chondrosarcomas, who had undergone bone SPECT/CT were retrospectively enrolled. The SUVmax was recorded and any aggressive CT findings of cartilaginous bone tumor and Hounsfield units (HU) of the chondroid matrix as mean, minimum, maximum, and standard deviation (SD) were reviewed on CT scans. Pearson's correlation analysis was performed to determine the relationship between CT features and SUVmax. Subgroup analysis was also performed between the benign group (enchondroma) and the malignant group (grade 1 and 2 chondrosarcoma) for comparison of HU values and SUVmax. (3) Results: a significant negative correlation between SUVmax and HU measurements, including HUmax, HUmean, and HUSD, was found. The subgroup analysis showed significantly higher SUVmax in the malignant group, with more frequent CT aggressive features, and significantly lower HUSD in the malignant group than in the benign group. (4) Conclusions: it was observed that higher SUVmax and lower HUSD were associated with a higher probability of having a low-to-intermediate chondrosarcoma with aggressive features and a less calcified tumor matrix.
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Affiliation(s)
- Hyukjin Yoon
- Division of Nuclear Medicine, Department of Radiology, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
| | - Seul Ki Lee
- Department of Radiology, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
| | - Jee-Young Kim
- Department of Radiology, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
| | - Min Wook Joo
- Department of Orthopaedic Surgery, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
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Scholte CHJ, Dorleijn DMJ, Krijvenaar DT, van de Sande MAJ, van Langevelde K. Wait-and-scan: an alternative for curettage in atypical cartilaginous tumours of the long bones. Bone Joint J 2024; 106-B:86-92. [PMID: 38160684 DOI: 10.1302/0301-620x.106b1.bjj-2023-0467.r1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
Aims Due to its indolent clinical behaviour, the treatment paradigm of atypical cartilaginous tumours (ACTs) in the long bones is slowly shifting from intralesional resection (curettage) and local adjuvants, towards active surveillance through wait-and-scan follow-up. In this retrospective cohort study performed in a tertiary referral centre, we studied the natural behaviour of ACT lesions by active surveillance with MRI. Clinical symptoms were not considered in the surveillance programme. Methods The aim of this study was to see whether active surveillance is safe regarding malignant degeneration and local progression. In total, 117 patients were evaluated with MRI assessing growth, cortical destruction, endosteal scalloping, periosteal reaction, relation to the cortex, and perilesional bone marrow oedema. Patients received up to six follow-up scans. Results At the time of the first follow-up MRI, 8% of the lesions showed growth (n = 9), 86% remained stable (101), and 6% decreased in size (n = 7). During the third follow-up, with a mean follow-up time of 60 months (SD 23), 24 patients were scanned, of whom 13% had lesions that had grown and 13% lesions that had decreased in size. After 96 months (SD 37), at the sixth follow-up MRI, 100% of the lesions remained stable. None of the lesions showed malignant progression and although some lesions grew in size (mean 1 mm (SD 0.8)), no malignant progression occurred. Conclusion We conclude that active surveillance with MRI is safe for ACTs in the long bones in the short- and mid-term follow-up.
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Affiliation(s)
- Claire H J Scholte
- Department of Orthopedics, Leiden University Medical Center, Leiden, Netherlands
| | | | - Duco T Krijvenaar
- Department of Orthopedics, Leiden University Medical Center, Leiden, Netherlands
| | | | - K van Langevelde
- Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
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Goel S, Dhaniwala N, Singh R, Suneja A, Jadawala VH. Exostosis of Ulna With Developmental Deformity of the Left Forearm: A Rare Case. Cureus 2023; 15:e50528. [PMID: 38226087 PMCID: PMC10788317 DOI: 10.7759/cureus.50528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Accepted: 12/14/2023] [Indexed: 01/17/2024] Open
Abstract
This case report presents a rare occurrence of exostosis of the ulna associated with a developmental deformity of the left forearm in a 15-year-old female. The patient reported a history of trauma resulting in a supracondylar humerus fracture managed conservatively eight years prior. The patient presented with a two-year history of pain and swelling over the left forearm. Clinical examination revealed a firm, non-tender, immobile swelling closely associated with the ulna, accompanied by a 20-degree cubitus varus deformity and forearm shortening. Radiographs and computed tomography scans confirmed the presence of a solitary external bony protuberance over the ulna shaft, communicating with the medullary cavity. A preliminary diagnosis of osteochondroma was established based on clinical and imaging findings. The patient underwent extraperiosteal en bloc resection of the lesion under supraclavicular nerve block anesthesia. A histopathological examination confirmed the diagnosis. Postoperative physiotherapy was initiated, and at the one-month follow-up, the patient reported being pain-free. This case highlights the rarity of exostosis of the ulna with associated developmental deformity, emphasizing the importance of a comprehensive diagnostic approach. Early surgical intervention resulted in a successful outcome, underscoring the significance of timely management in improving patient outcomes and quality of life.
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Affiliation(s)
- Sachin Goel
- Orthopaedics, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Nareshkumar Dhaniwala
- Orthopaedics, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Rahul Singh
- Orthopaedics, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Anmol Suneja
- Orthopaedics, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Vivek H Jadawala
- Orthopaedics, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
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Kim JH, Lee SK. Classification of Chondrosarcoma: From Characteristic to Challenging Imaging Findings. Cancers (Basel) 2023; 15:cancers15061703. [PMID: 36980590 PMCID: PMC10046282 DOI: 10.3390/cancers15061703] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 03/08/2023] [Accepted: 03/08/2023] [Indexed: 03/18/2023] Open
Abstract
Chondrosarcomas can be classified into various forms according to the presence or absence of a precursor lesion, location, and histological subtype. The new 2020 World Health Organization (WHO) Classification of Tumors of Soft Tissue and Bone classifies chondrogenic bone tumors as benign, intermediate (locally aggressive), or malignant, and separates atypical cartilaginous tumors (ACTs) and chondrosarcoma grade 1 (CS1) as intermediate and malignant tumors. respectively. Furthermore, the classification categorizes chondrosarcomas (including ACT) into eight subtypes: central conventional (grade 1 vs. 2–3), secondary peripheral (grade 1 vs. 2–3), periosteal, dedifferentiated, mesenchymal, and clear cell chondrosarcoma. Most chondrosarcomas are the low-grade, primary central conventional type. The rarer subtypes include clear cell, mesenchymal, and dedifferentiated chondrosarcomas. Comprehensive analysis of the characteristic imaging findings can help differentiate various forms of chondrosarcomas. However, distinguishing low-grade chondrosarcomas from enchondromas or high-grade chondrosarcomas is radiologically and histopathologically challenging, even for experienced radiologists and pathologists.
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Affiliation(s)
- Jun-Ho Kim
- Department of Orthopaedic Surgery, Center for Joint Diseases, Kyung Hee University Hospital at Gangdong, Seoul 05278, Republic of Korea
| | - Seul Ki Lee
- Department of Radiology, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
- Correspondence:
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