MRI features of low-grade and high-grade chondrosarcoma in enchondromatosis

Rare radiological manifestation of enchondromatosis in children: Columnar pattern: A retrospective cohort study

The columnar cartilage pattern is characterized by parallel aligned cartilage tissue columns related to the physis without matrix calcification separated by the surrounding osseous tissue. Usually, it is seen in patients with multiple enchondromas. The objective of this study was to elucidate the clinical and radiological features of this rare radiological pattern in the physis, which remains unfamiliar to most physician. We retrospectively evaluated the clinical features and imaging findings of 15 patients (9 men and 6 women) who have a columnar pattern with varied spectrum of enchondromatosis. On X-ray and computed tomography (CT) examination, all these lesions were seen as vertical or oblique oriented tubular zones, which have relatively low radiologic density compared with normal bone. The lesions have similar signal characteristics relative to epiphyseal cartilage plates, on T1W and T2W magnetic resonance images. Columnar pattern was observed in different appearances from one single column in one physis to multiple columns in multiple physis. The mean follow-up was 62 months (range: 36-96 months). The mean age was 9.7 (range: 4-14) years at the initial admission. Eight patients had 3 or less affected physis. Five patients had only one affected physis. We defined these patients' group who had up to 3 affected physis as "limited enchondromatosis with columnar pattern (LE-CP)." We observed that most of the columnar cartilage was turning into the normal bone via endochondral ossification. Based on our observations, the columnar pattern is a rare manifestation of the enchondromas. Columnar pattern, along with the related physis, acts as a normal endochondral ossification process, and surgery is not necessary unless there is a risk of fracture or severe deformity. Further awareness of this unique subset of patients may improve our understanding of the disease and lead to better patient outcomes. We have modified non-hereditarily enchondromatosis into 2 categories: limited enchondromatosis with the columnar pattern and multiple enchondromatosis. We believe that LE-CM reflects a developmental anomaly of the physis rather than a true neoplasia, and it acts as a normal endochondral ossification process. Level IV (case series).

Preoperative prediction of histopathological grading in patients with chondrosarcoma using MRI-based radiomics with semantic features

BACKGROUND

Distinguishing high-grade from low-grade chondrosarcoma is extremely vital not only for guiding the development of personalized surgical treatment but also for predicting the prognosis of patients. We aimed to establish and validate a magnetic resonance imaging (MRI)-based nomogram for predicting preoperative grading in patients with chondrosarcoma.

METHODS

Approximately 114 patients (60 and 54 cases with high-grade and low-grade chondrosarcoma, respectively) were recruited for this retrospective study. All patients were treated via surgery and histopathologically proven, and they were randomly divided into training (n = 80) and validation (n = 34) sets at a ratio of 7:3. Next, radiomics features were extracted from two sequences using the least absolute shrinkage and selection operator (LASSO) algorithms. The rad-scores were calculated and then subjected to logistic regression to develop a radiomics model. A nomogram combining independent predictive semantic features with radiomic by using multivariate logistic regression was established. The performance of each model was assessed by the receiver operating characteristic (ROC) curve analysis and the area under the curve, while clinical efficacy was evaluated via decision curve analysis (DCA).

RESULTS

Ultimately, six optimal radiomics signatures were extracted from T1-weighted imaging (T1WI) and T2-weighted imaging with fat suppression (T2WI-FS) sequences to develop the radiomics model. Tumour cartilage abundance, which emerged as an independent predictor, was significantly related to chondrosarcoma grading (p < 0.05). The AUC values of the radiomics model were 0.85 (95% CI, 0.76 to 0.95) in the training sets, and the corresponding AUC values in the validation sets were 0.82 (95% CI, 0.65 to 0.98), which were far superior to the clinical model AUC values of 0.68 (95% CI, 0.58 to 0.79) in the training sets and 0.72 (95% CI, 0.57 to 0.87) in the validation sets. The nomogram demonstrated good performance in the preoperative distinction of chondrosarcoma. The DCA analysis revealed that the nomogram model had a markedly higher clinical usefulness in predicting chondrosarcoma grading preoperatively than either the rad-score or clinical model alone.

CONCLUSION

The nomogram based on MRI radiomics combined with optimal independent factors had better performance for the preoperative differentiation between low-grade and high-grade chondrosarcoma and has potential as a noninvasive preoperative tool for personalizing clinical plans.

Chondroma Arising from the Temporomandibular Joint: A Case Report

Periarticular chondromas are common in the humerus and femur but rarely occur in the temporomandibular joint. We report a case of a chondroma in the anterior part of the ear. One year prior to his visit, a 53-year-old man became aware of swelling in the right cheek region which gradually increased in size. In the anterior part of the right ear, there was a palpable 25 mm tumor, elastic and hard, with poor mobility and without tenderness. A contrast-enhanced computed tomography CT showed a mass lesion with diffuse calcification or ossification in the upper pole of the parotid gland and areas of poor contrast within. A magnetic resonance imaging showed a low-signal mass lesion at the parotid gland with some high signals in both T1 and T2. Fine-needle aspiration cytology did not lead to diagnosis. Using a nerve monitoring system, the tumor was resected with normal tissue of the upper pole of the parotid gland in the same way as for a benign parotid tumor. Distinguishing between pleomorphic adenoma, including diffuse microcalcification of the parotid gland and cartilaginous tumors of the temporomandibular joint, may be sometimes difficult. In such cases, surgical resection may be a beneficial treatment option.

Development and validation of a MRI-based combined radiomics nomogram for differentiation in chondrosarcoma

Objective

This study aims to develop and validate the performance of an unenhanced magnetic resonance imaging (MRI)-based combined radiomics nomogram for discrimination between low-grade and high-grade in chondrosarcoma.

Methods

A total of 102 patients with 44 in low-grade and 58 in high-grade chondrosarcoma were enrolled and divided into training set (n=72) and validation set (n=30) with a 7:3 ratio in this retrospective study. The demographics and unenhanced MRI imaging characteristics of the patients were evaluated to develop a clinic-radiological factors model. Radiomics features were extracted from T1-weighted (T1WI) images to construct radiomics signature and calculate radiomics score (Rad-score). According to multivariate logistic regression analysis, a combined radiomics nomogram based on MRI was constructed by integrating radiomics signature and independent clinic-radiological features. The performance of the combined radiomics nomogram was evaluated in terms of calibration, discrimination, and clinical usefulness.

Results

Using multivariate logistic regression analysis, only one clinic-radiological feature (marrow edema OR=0.29, 95% CI=0.11-0.76, P=0.012) was found to be independent predictors of differentiation in chondrosarcoma. Combined with the above clinic-radiological predictor and the radiomics signature constructed by LASSO [least absolute shrinkage and selection operator], a combined radiomics nomogram based on MRI was constructed, and its predictive performance was better than that of clinic-radiological factors model and radiomics signature, with the AUC [area under the curve] of the training set and the validation set were 0.78 (95%CI =0.67-0.89) and 0.77 (95%CI =0.59-0.94), respectively. DCA [decision curve analysis] showed that combined radiomics nomogram has potential clinical application value.

Conclusion

The MRI-based combined radiomics nomogram is a noninvasive preoperative prediction tool that combines clinic-radiological feature and radiomics signature and shows good predictive effect in distinguishing low-grade and high-grade bone chondrosarcoma, which may help clinicians to make accurate treatment plans.

Peripheral and periosteal chondrosarcoma: MRI-pathological correlation in 58 cases

OBJECTIVE

To determine whether MRI can distinguish atypical cartilaginous tumour/grade 1 peripheral/periosteal chondrosarcoma (ACT/Gd1 PP-CS) from high-grade peripheral/periosteal chondrosarcoma (HG-PP-CS) or dedifferentiated peripheral/periosteal chondrosarcoma (DD-PP-CS).

MATERIALS AND METHODS

Retrospective review of patients diagnosed between January 2007 and December 2020 who had undergone resection of PP-CS. Data collected included age, sex, and skeletal location. Histological tumour grades based on surgical resection were classified as ACT/grade 1 PP-CS, HG-PP-CS, or DD-PP-CS. A variety of MRI features were reviewed independently by 2 musculoskeletal radiologists blinded to final diagnosis and compared between the 3 groups. For statistical analysis, HG-PP-CS and DD-PP-CS were combined.

RESULTS

Fifty-eight patients fulfilled the inclusion criteria, 31 (53%) males and 27 (47%) females with a mean age at diagnosis of 46.1 years (range 11-83 years), 14 (24%) of whom had an underlying diagnosis of diaphyseal aclasis. Forty-one (70.7%) cases were peripheral and 17 (29.3%) periosteal, 38 (66%) involving the flat bones, 15 (26%) the major long bones, 3 (5%) the spine, and 2 (3%) the bones of the hands and feet. Final histology revealed 33 (57%) ACT/Gd1-PP-CS, 18 (31%) HG-PP-CS, and 7 (12%) DD-PP-CS. Periosteal tumours were 16 times more likely to be HG/DD-CS compared to peripheral tumours (p < 0.001). Intra-medullary tumour extension was predictive of HG/DD-CS (p = 0.004) for both tumour types, while cap thickness (p = 0.04) and a diffuse cap type (p = 0.03) were differentiating features of low-grade and high-grade peripheral CS.

DISCUSSION

A variety of features can help differentiate low-grade from high-grade peripheral/periosteal CS, the most significant being origin from the bone surface.

Update on the imaging features of the enchondromatosis syndromes

Ollier disease and Maffucci syndrome are the commonest enchondromatosis subtypes, arising from non-hereditary mutations in the IDH1 and IDH2 genes, presenting in childhood and being characterised by multiple enchondromas. Maffucci syndrome also includes multiple soft tissue haemangiomas. Aside from developing bony masses, osseous deformity and pathological fracture, ~ 40% of these patients develop secondary central chondrosarcoma, and there is increased risk of non-skeletal malignancies such as gliomas and mesenchymal ovarian tumours. In this review, we outline the molecular genetics, pathology and multimodality imaging features of solitary enchondroma, Ollier disease and Maffucci syndrome, along with their associated skeletal complications, in particular secondary chondrosarcoma. Given the lifelong risk of malignancy, imaging follow-up will also be explored. Metachondromatosis, a rare enchondromatosis subtype characterised by enchondromas and exostoses, will also be briefly outlined.

Diagnostic Value of CT- and MRI-Based Texture Analysis and Imaging Findings for Grading Cartilaginous Tumors in Long Bones

Objective

To confirm the diagnostic performance of computed tomography (CT)-based texture analysis (CTTA) and magnetic resonance imaging (MRI)-based texture analysis for grading cartilaginous tumors in long bones and to compare these findings to radiological features.

Materials and Methods

Twenty-nine patients with enchondromas, 20 with low-grade chondrosarcomas and 16 with high-grade chondrosarcomas were included retrospectively. Clinical and radiological information and 9 histogram features extracted from CT, T1WI, and T2WI were evaluated. Binary logistic regression analysis was performed to determine predictive factors for grading cartilaginous tumors and to establish diagnostic models. Another 26 patients were included to validate each model. Receiver operating characteristic (ROC) curves were generated, and accuracy rate, sensitivity, specificity and positive/negative predictive values (PPV/NPV) were calculated.

Results

On imaging, endosteal scalloping, cortical destruction and calcification shape were predictive for grading cartilaginous tumors. For texture analysis, variance, mean, perc.01%, perc.10%, perc.99% and kurtosis were extracted after multivariate analysis. To differentiate benign cartilaginous tumors from low-grade chondrosarcomas, the imaging features model reached the highest accuracy rate (83.7%) and AUC (0.841), with a sensitivity of 75% and specificity of 93.1%. The CTTA feature model best distinguished low-grade and high-grade chondrosarcomas, with accuracies of 71.9%, and 80% in the training and validation groups, respectively; T1-TA and T2-TA could not distinguish them well. We found that the imaging feature model best differentiated benign and malignant cartilaginous tumors, with an accuracy rate of 89.2%, followed by the T1-TA feature model (80.4%).

Conclusions

The imaging feature model and CTTA- or MRI-based texture analysis have the potential to differentiate cartilaginous tumors in long bones by grade. MRI-based texture analysis failed to grade chondrosarcomas.