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Abstract ObjectiveTo assess the diagnostic performance of MRI-based texture analysis for differentiating enchondromas and chondrosarcomas, especially on fat-suppressed proton density (FS-PD) images.Materials and methodsThe whole tumor volumes of 23 chondrosarcomas and 24 enchondromas were manually segmented on both FS-PD and T1-weighted images. A total of 861 radiomic features were extracted. SelectKBest was used to select the features. The data were randomly split into training (n = 36) and test (n = 10) for T1-weighted and training (n = 37) and test (n = 10) for FS-PD datasets. Fivefold cross-validation was performed. Fifteen machine learning models were created using the training set. The best models for T1-weighted, FS-PD, and T1-weighted + FS-PD images were selected in terms of accuracy and area under the curve (AUC).ResultsThere were 7 men and 16 women in the chondrosarcoma group (mean ± standard deviation age, 45.65 ± 11.24) and 7 men and 17 women in the enchondroma group (mean ± standard deviation age, 46.17 ± 11.79). Naive Bayes was the best model for accuracy and AUC for T1-weighted images (AUC = 0.76, accuracy = 80%, recall = 80%, precision = 80%, F1 score = 80%). The best model for FS-PD images was the K neighbors classifier for accuracy and AUC (AUC = 1.00, accuracy = 80%, recall = 80%, precision = 100%, F1 score = 89%). The best model for T1-weighted + FS-PD images was logistic regression for accuracy and AUC (AUC = 0.84, accuracy = 80%, recall = 60%, precision = 100%, F1 score = 75%).ConclusionMRI-based machine learning models have promising results in the discrimination of enchondroma and chondrosarcoma based on radiomic features obtained from both FS-PD and T1-weighted images.

Introduction Percutaneous cryoablation is a first-line therapeutic option for primary neoplasms and metastatic lesions of the musculoskeletal system. Treatment of abdominal wall tumors is challenging as surgical resection can be highly morbid and necessitate complex reconstructive surgery; the efficacy of cryoablation for abdominal wall tumors may be limited by inadequate posterior margins owing to the proximity of intra-abdominal organs. With laparoscopy and insufflation, peritoneal structures can be safely mobilized away from the abdominal wall, allowing for adequate deep margin freeze and visualization of the ice ball. We present two patients with abdominal wall soft tissue tumors treated with a novel approach of laparoscopic-assisted, percutaneous ultrasound-guided cryoablation. Patients and Methods Patient 1 is a 65-year-old female with metastatic extraskeletal myxoid chondrosarcoma, stable on systemic therapy, who presented with a new soft tissue metastasis to the abdominal wall. Resection would have necessitated a highly morbid complex abdominal wall reconstruction with mesh. Patient 2 is a 35-year-old female with a large abdominal wall desmoid tumor, diagnosed after miscarriage. Resection was relatively contraindicated owing to the morbidity of a complex abdominal wall reconstruction and concerns regarding potential future pregnancies after surgery. Results Both patients underwent procedures in the outpatient setting after discussion at multidisciplinary sarcoma tumor board. Laparoscopic enterolysis was performed to mobilize the bowel away from the abdominal wall, to allow direct visualization of the peritoneal aspect of the tumor, and to confirm adequacy of the posterior margin freeze of the lesion. Laparoscopic transversus abdominus preperitoneal (TAPP) blocks with local anesthetic were performed for postoperative pain control. Interventional radiology performed an ultrasound-guided cryoablation consisting of two freeze and thaw cycles. Both patients recovered well without complications and were without radiographic evidence of persistent or recurrent disease at 12 and 18 months postoperatively, respectively. Conclusion We report a novel approach of laparoscopic-assisted cryoablation for the treatment of abdominal wall soft tissue tumors. This allowed for successful minimally invasive local control of these large tumors that would have otherwise required highly morbid resections with complex abdominal wall reconstruction and mesh repair.

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. Graphical Abstract

There is discrepancy in the histologic concordance of pre-operative biopsy grading and post-surgical resection grading of periacetabular chondrosarcoma. This discrepancy poses a question as to whether the chosen treatment should depend upon on the initial assessment of the tumor grade. This is a retrospective review of patients with periacetabular cartilaginous tumors who were treated between the years 2000 and 2022 at a single institution. All patients included in the analysis underwent surgical resection. The pre-operative biopsy and post-surgical resection histological grades were compared. Concordance and treatment implications were evaluated. Twenty-two pre-operative Image Guided Core Needle Biopsies (IGCNB) were performed. There was concordance between pre-operative and surgical resection histological grade in only 9 cases, giving a (9/22) 40.9% accuracy rate. In total there were 13 cases of discrepancy between pre-operative biopsy and surgical resection regarding histological grade. In 12 cases of discrepancy, surgical resection histopathology revealed a higher grade than that of pre-operative biopsy histopathology. In one case of discrepancy, pre-operative IGCNB biopsy histology revealed a high-grade chondrosarcoma while the surgical resection histology revealed an intermediate-grade. There were no situations in which the plan made based on a preoperative biopsy resulted in an inappropriate treatment decision, even when there was not concordance between preoperative diagnosis and diagnosis after definitive resection. Significant discrepancy in grading was observed with pre-operative IGCNB of periacetabular cartilaginous lesions. However, while 12 out of the 13 discordant cases (92.3%) underestimated the true grade of the tumor, there was no impact on appropriateness of the selected treatment, suggesting that accuracy of grade is not an important factor to consider in this location.

Objective To evaluate the study quality and clinical value of radiomics studies on chondrosarcoma. Methods PubMed, Embase, Web of Science, China National Knowledge Infrastructure, and Wanfang Data were searched for articles on radiomics for evaluating chondrosarcoma as of January 31, 2022. The study quality was assessed according to Radiomics Quality Score (RQS), Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) checklist, Image Biomarker Standardization Initiative (IBSI) guideline, and modified Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. The level of evidence supporting clinical use of radiomics on chondrosarcoma differential diagnosis was determined based on meta-analyses. Results Twelve articles were included. The median RQS was 10.5 (range, −3 to 15), with an adherence rate of 36%. The adherence rate was extremely low in domains of high-level evidence (0%), open science and data (17%), and imaging and segmentation (35%). The adherence rate of the TRIPOD checklist was 61%, and low for section of title and abstract (13%), introduction (42%), and results (56%). The reporting rate of pre-processing steps according to the IBSI guideline was 60%. The risk of bias and concern of application were mainly related to the index test. The meta-analysis on differential diagnosis of enchondromas vs. chondrosarcomas showed a diagnostic odds ratio of 43.90 (95% confidential interval, 25.33–76.10), which was rated as weak evidence. Conclusions The current scientific and reporting quality of radiomics studies on chondrosarcoma was insufficient. Radiomics has potential in facilitating the optimization of operation decision-making in chondrosarcoma. Key Points • Among radiomics studies on chondrosarcoma, although differential diagnostic models showed promising performance, only pieces of weak level of evidence were reached with insufficient study quality . • Since the RQS rating, the TRIPOD checklist, and the IBSI guideline have largely overlapped with each other, it is necessary to establish one widely acceptable methodological and reporting guideline for radiomics research . • The TRIPOD model typing, the phase classification of image mining studies, and the level of evidence category are useful tools to assess the gap between academic research and clinical application, although their modifications for radiomics studies are needed .

Background Differentiating chondroid tumors is crucial for proper patient management. This study aimed to develop a deep learning model (DLM) for classifying enchondromas, atypical cartilaginous tumors (ACT), and high-grade chondrosarcomas using CT images. Methods This retrospective study analyzed chondroid tumors from two independent cohorts. Tumors were segmented on CT images. A 2D convolutional neural network was developed and tested using split-sample and geographical validation. Four radiologists blinded to patient data and the DLM results with various levels of experience performed readings of the external test dataset for comparison. Performance metrics included accuracy, sensitivity, specificity, and area under the curve (AUC). Results CTs from 344 patients (175 women; age = 50.3 ± 14.3 years;) with diagnosed enchondroma ( n  = 124), ACT ( n  = 92) or high-grade chondrosarcoma ( n  = 128) were analyzed. The DLM demonstrated comparable performance to radiologists ( p  > 0.05), achieving an AUC of 0.88 for distinguishing enchondromas from chondrosarcomas and 0.82 for differentiating enchondromas from ACTs. The DLM and musculoskeletal expert showed similar performance in differentiating ACTs from high-grade chondrosarcomas ( p  = 0.26), with an AUC of 0.64 and 0.56, respectively. Conclusions The DLM reliably differentiates benign from malignant cartilaginous tumors and is particularly useful for the differentiation between ACTs and Enchondromas, which is challenging based on CT images only. However, the differentiation between ACTs and high-grade chondrosarcomas remains difficult, reflecting known diagnostic challenges in radiology.

Spinal chondrosarcomas are uncommon malignant bone tumors that are rare in children. The location and imaging features of the lesion help in formulating a differential diagnosis, though in certain instances the lack of typical imaging findings may elude the differential of a chondrosarcoma. There are only a few reported cases in literature and owing to its rarity and lack of specific management protocols in this age group, making treatment decisions can be complex. We report a case of spinal chondrosarcoma in a young girl, where the treatment of choice was primary surgical resection. Transarterial embolization was performed to reduce tumor vascularity and aid the surgery.

This study was performed to investigate the diagnostic value of radiomics models constructed by fat suppressed T2-weighted imaging (T2WI-FS) and contrast-enhanced T1-weighted imaging (CET1) based on magnetic resonance imaging (MRI) for differentiation of osteosarcoma (OS) and chondrosarcoma (CS). In this retrospective cohort study, we included all inpatients with pathologically confirmed OS or CS from Second Xiangya Hospital of Central South University (Hunan, China) as of October 2020. Demographic and imaging variables were extracted from electronic medical records and compared between OS and CS group. Totals of 530 radiomics features were extracted from CET1 and T2WI-FS sequences based on MRI. The least absolute shrinkage and selection operator (LASSO) method was used for screening and dimensionality reduction of the radiomics model. Multivariate logistic regression analysis was performed to construct the radiomics model, and receiver operating characteristic curve (ROC) was generated to evaluate the diagnostic accuracy of the radiomics model. The training cohort and validation cohort included 87 and 29 patients, respectively. 8 CET1 features and 15 T2WI-FS features were screened based on the radiomics features. In the training group, the area under the receiver-operator characteristic curve (AUC) value for CET1 and T2WI-FS sequences in the radiomics model was 0.894 (95% CI 0.817–0.970) and 0.970 (95% CI 0.940–0.999), respectively. In the validation group, the AUC value for CET1 and T2WI-FS sequences in the radiomics model was 0.821 (95% CI 0.642–1.000) and 0.899 (95% CI 0.785–1.000), respectively. In this study, we developed a radiomics model based on T2WI-FS and CET1 sequences to differentiate between OS and CS. This model exhibits good performance and can help clinicians make decisions and optimize the use of healthcare resources.

Background To develop a multiclass radiomics model for differentiating chondroid bone tumors using preoperative MRI. Methods This retrospective study included 120 patients (92 enchondromas, 16 low-grade chondrosarcomas, and 12 intermediate-to-high-grade chondrosarcomas) who underwent contrast-enhanced MRI between 2009 and 2019. Tumor segmentation was manually performed by a musculoskeletal radiologist and validated by a senior radiologist. We used least absolute shrinkage and selection operator (LASSO) and random forest (RF) for feature selection and classification, with and without synthetic minority oversampling technique (SMOTE). Model performance was evaluated using five-fold cross-validation with average precision, accuracy, area under the curve (AUC), and weighted kappa statistics. Results The LASSO + RF model based on all sequences achieved the highest accuracy (0.826 ± 0.065) and AUC (0.967 ± 0.027). The highest mAP (0.750 ± 0.095) was observed in the SMOTE-enhanced T2WI-based model, highlighting the potential impact of class imbalance. Quadratic weighted kappa values ranged from 0.648 to 0.731 across models, indicating substantial agreement with pathological results. Conclusions Preoperative MRI-based radiomics provides a robust method for the classification of chondroid bone tumors, potentially enhancing clinical decision-making.

Gross total resection (GTR) is the mainstay therapy for chordomas and chondrosarcomas to have the best prognosis. The aims of this study were to specify the limits of EEA, emphasize the need for additional combined approaches for tumors beyond these limitations for high resection rates, discuss the prognostic factors and operative nuances that affect GTR, and present the causes and characteristics of early and late recurrences. We retrospectively analyzed the endoscopic endonasal surgeries in the Pituitary Research Center and Neurosurgery Department of the Kocaeli University Faculty of Medicine, Turkey between January 2004 and December 2019. We retrospectively reviewed the medical data, radiological images, and surgical videos of patients, and 72 patients with chordoma and chondrosarcoma were included in the study. Based on pathology reports, 72 patients (seven pediatric) were identified, to whom 91 endoscopic operations were performed. We determined the surgical limitations for each clival segment as superior, middle, and inferior. Then, we divided these into three subgroups according to whether the tumor shows dural invasion (extradural chordoma, large extradural - minimal intradural component, and minimal extradural - large intradural component). The tumors of 19 (26.4%), 25 (26.4%), and nine (12.5%) patients originated from the superior, middle, and inferior clivus, respectively. Nineteen (26.4%) patients had panclival involvement. GTR was performed in 47 (65.3%) the patients. The GTR rate in patients with panclival tumors was 47.3% (9/19). The experience, lateralization, dural involvement, and origin of the clivus affecting GTR were analyzed. Extradural – intradural extensions were verified as negative predictor factors for GTR, whereas tumors located in the superior (OR: 16.710, p=0.030) and middle (OR: 11.154, p=0.023) segments were positive predictive factors for GTR. An increasing experience in endoscopic surgery significantly increases the GTR rates by widening the surgical limitations. Due to dense bone infiltration and adhesion to critical neurovascular structures, recurrence rates are high despite performing GTR. Although surgery and adjuvant treatments improve the 5-year survival of patients, the mortality rates remain high. Therefore, surgery of these tumors should be performed by experienced centers. In addition to surgical and adjuvant therapies, targeted molecular and translational biological therapies are also needed for chordomas and chondrosarcomas in the future. •Chordomas and chondrosarcomas are locally aggressive, pathologically benign tumors.•Bone infiltration and anatomical adhesions affect resection rates.•Endoscopic approach is the most effective surgery for clival lesions.•But it has limitations and additional combined surgery should be required.•Reasons for rapid recurrence on chordomas are still not clearly understood.