Radiologic differentiation of enchondromas, atypical cartilaginous tumors, and high‐grade chondrosarcomas—Improving tumor‐specific treatment: A paradigm in transit?

Evaluation of the value of dynamic contrast-enhanced MRI for the diagnosis and follow-up of central cartilage tumors

OBJECTIVES

To evaluate the value of (dynamic) contrast-enhanced MRI for the diagnosis and follow-up of central cartilage tumors (CCT) of the proximal humerus, distal femur and proximal tibia.

MATERIALS & METHODS

97 patients (44 ± 11 years, 31men) with a CCT (histopathologically proven and/or > 2 years follow-up (5 ± 3 years)) were retrospectively/consecutively included at the Ghent University Hospital (Belgium, 2003-2021). Thickness of the enhancing rim and dynamic contrast-enhanced MRI parameters of the entire tumor were calculated. Tumor volumes were calculated to assess tumor growth. Significant differences between enchondromas, atypical cartilaginous tumors, high-grade chondrosarcomas, tumors with and without growth at follow-up were evaluated and ROC-curves were analyzed.

RESULTS

A significant difference (p = 0.015) existed in enhancing rim thickness between high-grade chondrosarcomas and other groups. A ROC-curve with an AUC of 0.89 and cut-off value of 1.2 mm had a sensitivity of 100 % and a specificity of 64 % to identify high-grade chondrosarcomas. A significant correlation was found between the relative maximal enhancement (Rel-Emax) of the whole tumor compared to muscle and the absolute growth rate (ρ = 0.75, p < 0.001). Lesions with a Rel-Emax < 1 remained stable or showed regression during follow-up (mean -0.1 ± 0.3 ml/year). Lesions with a Rel-Emax between 1 and 2 showed little growth (mean + 0.2 ± 0.2 ml/year), and lesions with a Rel-Emax > 2 had the highest growth rate (mean 0.4 ± 0.2 ml/year).

CONCLUSION

A thick enhancing rim > 1.2 mm has a high sensitivity to detect high-grade chondrosarcomas. The higher the Rel-Emax of the whole tumor compared to muscle, the higher the growth rate of a CCT.

Follow-up analysis of lesion characteristics of enchondromas and atypical cartilaginous tumours of the knee and shoulder region on MRI

OBJECTIVE

Enchondromas (ECs) and atypical cartilaginous tumours (ACTs), respectively, represent benign and intermediate cartilaginous bone tumours. Differentiation between these tumour entities bears difficulties, as histology and MRI cannot always provide exact diagnoses. Observation of the natural course of ECs/ACTs via follow-up MRIs might support tumour distinction without needing biopsy harbouring sampling error.

MATERIALS AND METHODS

Reports of patients that had undergone MRI exams of the knee (n = 44.762) or shoulder (n = 21.550) at a single radiology institute between 01.01.2007 and 01.03.2020 were searched for ECs/ACTs with at least one follow-up MRI. Scans of 176 patients (with 182 cartilage lesions) fulfilling these criteria were subsequently re-examined together with corresponding MRI reports to evaluate morphological tumour development over time, focusing on potential alterations of lesion size, tumour-related oedema, and scalloping.

RESULTS

Median follow-up time was 27 ± 53 months for knee tumours and 26 ± 32 months for shoulder lesions. Presence of tumour growth was significantly higher in ACTs than in ECs both at the knee (p = 0.04) and shoulder (p = 0.03). While ACTs were associated with median tumour growth rates of 0.039 mm/month (knee) and 0.083 mm/month (shoulder), ECs of the knee and shoulder showed lower median growth rates equivalent to 0.0 mm/month (p < 0.01, p < 0.01). ECs and ACTs both presented stable regarding tumour-related oedema and scalloping during follow-up.

CONCLUSION

ACTs and ECs show different tumour growth rates. Growth rates are slow for both, ECs and ACTs, supporting the current concept of watchful waiting. ECs may decrease in size. Follow-up MRIs may support the radiological differentiation of cartilage lesions.

KEY POINTS

Question Both singular MRI and histological examination have limitations regarding differentiation of enchondromas (EC) and atypical cartilaginous tumours (ACTs). Findings Median ACT growth rates were 0.039 mm/month (knee) and 0.083 mm/month (shoulder), while median growth rates of EC in the knee and shoulder were 0.0 mm/month. Clinical relevance Active surveillance is a safe strategy when dealing with ECs and ACTs of the long bones; follow-up MRIs may support tumour distinction of cartilage lesions, as ECs and ACTs show different growth behaviour.

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.

X-rays radiomics-based machine learning classification of atypical cartilaginous tumour and high-grade chondrosarcoma of long bones

BACKGROUND

Atypical cartilaginous tumour (ACT) and high-grade chondrosarcoma (CS) of long bones are respectively managed with active surveillance or curettage and wide resection. Our aim was to determine diagnostic performance of X-rays radiomics-based machine learning for classification of ACT and high-grade CS of long bones.

METHODS

This retrospective, IRB-approved study included 150 patients with surgically treated and histology-proven lesions at two tertiary bone sarcoma centres. At centre 1, the dataset was split into training (n = 71 ACT, n = 24 high-grade CS) and internal test (n = 19 ACT, n = 6 high-grade CS) cohorts, respectively, based on the date of surgery. At centre 2, the dataset constituted the external test cohort (n = 12 ACT, n = 18 high-grade CS). Manual segmentation was performed on frontal view X-rays, using MRI or CT for preliminary identification of lesion margins. After image pre-processing, radiomic features were extracted. Dimensionality reduction included stability, coefficient of variation, and mutual information analyses. In the training cohort, after class balancing, a machine learning classifier (Support Vector Machine) was automatically tuned using nested 10-fold cross-validation. Then, it was tested on both the test cohorts and compared to two musculoskeletal radiologists' performance using McNemar's test.

FINDINGS

Five radiomic features (3 morphology, 2 texture) passed dimensionality reduction. After tuning on the training cohort (AUC = 0.75), the classifier had 80%, 83%, 79% and 80%, 89%, 67% accuracy, sensitivity, and specificity in the internal (temporally independent) and external (geographically independent) test cohorts, respectively, with no difference compared to the radiologists (p ≥ 0.617).

INTERPRETATION

X-rays radiomics-based machine learning accurately differentiates between ACT and high-grade CS of long bones.

FUNDING

AIRC Investigator Grant.

Prevalence and characteristics of benign cartilaginous tumours of the shoulder joint. An MRI-based study

OBJECTIVE

Enchondromas (EC) of the shoulder joint are benign intraosseous cartilage neoplasms, with atypical cartilaginous tumours (ACT) representing their intermediate counterpart. They are usually found incidentally on clinical imaging performed for other reasons. Thus far the prevalence of ECs of the shoulder has been analysed in only one study reaching a figure of 2.1%.

MATERIALS AND METHODS

The aim of the current study was to validate this number via retrospective analysis of a 45 times larger, uniform cohort consisting of 21.550 patients who had received an MRI of the shoulder at a single radiologic centre over a time span of 13.2 years.

RESULTS

Ninety-three of 21.550 patients presented with at least one cartilaginous tumour. Four patients showed two lesions at the same time resulting in a total number of 97 cartilage tumours (89 ECs [91.8%], 8 ACTs [8.2%]). Based on the 93 patients, the overall prevalence was 0.39% for ECs and 0.04% for ACTs. Mean size of the 97 ECs/ACTs was 2.3 ± 1.5 cm; most neoplasms were located in the proximal humerus (96.9%), in the metaphysis (60.8%) and peripherally (56.7%). Of all lesions, 94 tumours (96.9%) were located in the humerus and 3 (3.1%) in the scapula.

CONCLUSION

Frequency of EC/ACT of the shoulder joint appears to have been overestimated, with the current study revealing a prevalence of 0.43%.

Wait-and-scan: an alternative for curettage in atypical cartilaginous tumours of the long bones

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.

Prevalence and characteristics of benign cartilaginous tumours of the knee joint as identified on MRI scans

BACKGROUND

Enchondromas (EC) and atypical cartilaginous tumours (ACT) of the knee joint represent benign/intermediate chondromatous neoplasms of the bone that are most commonly discovered incidentally. Based on small to intermediate-sized cohorts, the prevalence of cartilaginous tumours of the knee as visible in MRI is estimated at 0.2-2.9%. This study aimed at verifying/challenging these numbers via retrospective examination of a larger, uniform patient cohort.

METHODS

Between 01.01.2007 and 01.03.2020, 44,762 patients had received an MRI of the knee for any indication at a radiologic centre. Of these, 697 patients presented with MRI reports positive for cartilaginous lesions. In a three-step workflow, 46 patients were excluded by a trained co-author, a radiologist and an orthopaedic oncologist, as wrongly being diagnosed for a cartilage tumour.

RESULTS

Of 44,762 patients, 651 presented with at least one EC/ACT indicating a prevalence of 1.45% for benign/intermediate cartilaginous tumours of the knee joint (EC: 1.4%; ACTs: 0.05%). As 21 patients showed 2 chondromatous lesions, altogether 672 tumours (650 ECs [96.7%] and 22 ACTs [3.3%]) could be analysed in terms of tumour characteristics: With a mean size of 1.6 ± 1.1 cm, most lesions were located in the distal femur (72.9%), in the metaphysis of the respective bone (58.9%) and centrally in the medullary canal (57.4%).

CONCLUSIONS

This study revealed an overall prevalence of 1.45% for cartilage lesions around the knee joint. Whilst a constant increase in prevalence was found for ECs over 13.2 years, prevalence remained constant for ACTs.

Curettage or Resection? A Review on the Surgical Treatment of Low-Grade Chondrosarcomas

Introduction Low-grade chondrosarcomas (LG-CS), including atypical cartilaginous tumors (ACT), are locally aggressive lesions. The focus of the discussion sits on the differential diagnosis between benign lesions or aggressive cartilaginous tumors and on their treatment: intralesional curettage or wide resection. This study presents the results obtained in the surgical treatment of 21 cases of LG-CS. Methods This retrospective study includes 21 consecutive patients from a single center with LG-CS who underwent surgery from 2013 to 2021. Fourteen were located in the appendicular skeleton, and seven in the axial (shoulder blade, spine, or pelvis). Mortality rate, recurrence, metastatic disease, overall survival, recurrence-free survival, and metastatic disease-free survival were analyzed for each type of procedure and each disease location. Operative complications and residual tumors were also recorded in cases where resection was performed. Survival was calculated using the Kaplan-Meier method. Results Thirteen patients underwent intralesional curettage (11 appendicular and 2 axial lesions), and eight underwent wide resection (5 axial and 3 appendicular). There were six recurrences during the follow-up, 43% of the axial lesions recurred, rising to 100% in axial curetted ones. Appendicular LG-CS recurred in 21% of cases, and only 18% of curetted appendicular lesions were not eradicated. The overall survival for the entire follow-up is 90.5%, and the 5-year survival rate is 83% (12 patients have adequate follow-up). Recurrence-free and metastasis-free survival were higher in resection cases, with 75% and 87.5%, vs. curettage 69.2% and 76.9%, respectively. In 9% of cases, the preoperative biopsy was inconsistent with the pathology of the surgical specimen. Discussion LG-CS and ACT are described as having high survival and low potential for metastatic disease. For this reason, these lesions are subject to a change in treatment philosophy to reflect these characteristics. Intra-lesional curettage is advocated as a less invasive technique for eradicating atypical cartilage tumors and has fewer and less severe complications, which was in accordance with our findings. Diagnosis, however, is challenging; misgrading is frequent and should be considered. Because of this risk of under-treating higher-grade lesions, some authors still defend wide-resection as the treatment of choice. We observed a trend towards longer survival, less recurrence, and metastatic disease with wide resection. Metastatic disease was higher than expected, present in 19% of cases, and always associated with local recurrence. Conclusion LG-CS is still a diagnostic and treatment challenge; patient selection is fundamental. Overall survival is high, independent of treatment choice or lesion location. We found a higher rate of metastatic disease than described in the literature; this, coupled with a misgrading rate of 9%, reflects the difficulty of preoperative diagnosis and the risk of treating high-grade chondrosarcomas as a low-grade lesion. More studies should be carried out with larger samples to obtain statistically robust results.

Classification of Chondrosarcoma: From Characteristic to Challenging Imaging Findings

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.

Can low-grade chondrosarcoma in flat bones be treated with intralesional curettage and cryotherapy?

BACKGROUND AND OBJECTIVES

Chondrosarcomas in flat bones are thought to be more aggressive in their behavior, and little is known about intralesional treatment outcomes of low-grade chondrosarcoma in these locations. We tried to find the differences between patients who had low-grade chondrosarcoma in their flat bones versus those with long bone involvement with regard to (1) disease outcome, (2) functional outcome, and (3) treatment complications.

METHODS

We retrospectively reviewed 44 patients with primary low-grade chondrosarcoma who were treated with intralesional curettage and cryotherapy. The patients were divided by location of tumor, group I (flat bones, seven patients) and group II (long bones, 37 patients).

RESULTS

The local recurrence rate was higher in group I with 5 years disease-free survival of 80.0% in group I and 97.0% in group II (p = 0.001). All recurrent cases were noted to have initially presented with soft tissue extension (Enneking stage IB). The mean Musculoskeletal Tumor Society score at the last follow-up was 21.7 in group I and 27.9 in group II (p = 0.045).

CONCLUSIONS

Intralesional curettage and cryotherapy for low-grade chondrosarcoma appear to be a safe and reasonable surgical option for patients with lesions confined to bone (Enneking stage IA).

LEVEL OF EVIDENCE

Level III, retrospective cohort study. See the Guidelines for Authors for a complete description of levels of evidence.

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.

The influence of site on the incidence and diagnosis of solitary central cartilage tumours of the femur. A 21st century perspective

OBJECTIVE

To determine the incidence of central cartilage tumours (CCTs) in the femur and the impact of site (proximal, mid and distal thirds) on tumour grade. To compare study results with historically published data.

MATERIALS AND METHODS

Retrospective review of solitary CCTs arising in the femur over the past 13 years. Data collected included location (proximal, mid and distal thirds) and final diagnosis in terms of tumour grade based on imaging features ± histology. Case material collected from three bone tumour textbooks provided historical data.

RESULTS

430 solitary CCTs were included in the femur. 73% cases arose in the distal, 3.7% in the mid and 23% in the proximal femur. The ratio of "benign" (combining enchondroma and atypical cartilaginous tumour (ACT)) to higher grade chondrosarcoma (CS) was 11:1 in the distal, 1:1 in the mid and 1:1.5 in the proximal femur, the distribution of benign to malignant tumours being significantly different between the regions (F test, p < 0.05). Comparison with historical data showed a reversal of the benign (enchondroma) to malignant (ACT and higher grade CS) of 30%:70%-84%:16% in the current series.

CONCLUSIONS

The site of origin of a CCT in the femur has an impact on final diagnosis with CS uncommon in the distal as compared with the mid and proximal femur. This is in contradistinction to historical data where the incidence of CS exceeded that of enchondroma at all sites.

Der atypische chondrogene Tumor

Hintergrund

Atypische chondrogene Tumoren (ACT) der kurzen und langen Röhrenknochen, früher als Chondrosarkome G1 bezeichnet, verhalten sich lokal aggressiv, haben aber ein sehr geringes Metastasierungspotenzial. Die Abgrenzung zu benignen Enchondromen ist aus klinischer, radiologischer und histopathologischer Sicht komplex.

Ziel der Arbeit

Epidemiologie, Diagnostik und Therapie von ACT unter besonderer Berücksichtigung der Abgrenzung zu Enchondromen werden dargestellt.

Material und Methoden

Es erfolgt die Zusammenfassung der internationalen Fachliteratur zu ACT und Enchondromen.

Ergebnisse

Die Inzidenz von Enchondromen, und mehr noch von ACT, ist über die Jahre angestiegen, was auf häufiger werdende Diagnostik hinweist. Im Gegensatz zu Enchondromen können ACT mit Schmerzen verbunden sein und radiologische Zeichen aggressiven Wachstums, wie tiefes endosteales Scalloping, aufweisen. Die alleinige Biopsie zur Differenzierung zwischen Enchondromen und ACT ist oft nicht hilfreich, da aufgrund der punktuellen Probegewebsentnahme ein „sampling error“ resultieren kann. Die definitive operative Therapie von ACT der langen und kurzen Röhrenknochen hat sich über die letzten Jahre gewandelt, weg von einer radikalen Tumorentfernung hin zu intraläsionaler Kürettage. Ein Zuwarten ist bei radiologischem Verdacht auf das Vorliegen eines Enchondroms regelmäßigen Verlaufskontrollen mittels Magnetresonanztomographie (MRT) möglich.

Schlussfolgerungen

ACT weisen im Gegensatz zu Enchondromen radiologische Zeichen eines aggressiven Wachstums auf. Die heutzutage bevorzugte Therapie besteht aus einer intraläsionalen Kürettage. Sowohl Diagnostik als auch Therapie und Nachsorge von kartilaginären Tumoren sollten an einem spezialisierten Tumorzentrum erfolgen.

Assessment of central cartilaginous tumor of the appendicular bone: inter-observer and intermodality agreement and comparison of diagnostic performance of CT and MRI

BACKGROUND

Diagnostic performance, inter-observer agreement, and intermodality agreement between computed tomography (CT) and magnetic resonance imaging (MRI) in the depiction of the major distinguishing imaging features of central cartilaginous tumors have not been investigated.

PURPOSE

To determine the inter-observer and intermodality agreement of CT and MRI in the evaluation of central cartilaginous tumors of the appendicular bones, and to compare their diagnostic performance.

MATERIAL AND METHODS

Two independent radiologists retrospectively reviewed preoperative CT and MRI. Inter-observer and intermodality agreement between CT and MRI in the assessment of distinguishing imaging features, including lesion size, deep endosteal scalloping, cortical expansion, cortical disruption, pathologic fracture, soft tissue extension, and peritumoral edema, were evaluated. The agreement with histopathology and the accuracy of the radiologic diagnoses made with CT and MRI were also analyzed.

RESULTS

A total of 72 patients were included. CT and MRI showed high inter-observer and intermodality agreements with regard to size, deep endosteal scalloping, cortical expansion, cortical disruption, and soft tissue extension (ICC = 0.96-0.99, k = 0.60-0.90). However, for the evaluation of pathologic fracture, MRI showed only moderate inter-observer agreement (k = 0.47). Peritumoral edema showed only fair intermodality agreement (k = 0.28-0.33) and moderate inter-observer agreement (k = 0.46) on CT. Both CT and MRI showed excellent diagnostic performance, with high agreement with the histopathology (k = 0.89 and 0.87, respectively) and high accuracy (91.7% for both CT and MRI).

CONCLUSION

CT and MRI showed high inter-observer and intermodality agreement in the assessment of several distinguishing imaging features of central cartilaginous tumors of the appendicular bones and demonstrated comparable diagnostic performance.

Radiomics of Musculoskeletal Sarcomas: A Narrative Review

Bone and soft-tissue primary malignant tumors or sarcomas are a large, diverse group of mesenchymal-derived malignancies. They represent a model for intra- and intertumoral heterogeneities, making them particularly suitable for radiomics analyses. Radiomic features offer information on cancer phenotype as well as the tumor microenvironment which, combined with other pertinent data such as genomics and proteomics and correlated with outcomes data, can produce accurate, robust, evidence-based, clinical-decision support systems. Our purpose in this narrative review is to offer an overview of radiomics studies dealing with Magnetic Resonance Imaging (MRI)-based radiomics models of bone and soft-tissue sarcomas that could help distinguish different histotypes, low-grade from high-grade sarcomas, predict response to multimodality therapy, and thus better tailor patients’ treatments and finally improve their survivals. Although showing promising results, interobserver segmentation variability, feature reproducibility, and model validation are three main challenges of radiomics that need to be addressed in order to translate radiomics studies to clinical applications. These efforts, together with a better knowledge and application of the “Radiomics Quality Score” and Image Biomarker Standardization Initiative reporting guidelines, could improve the quality of sarcoma radiomics studies and facilitate radiomics towards clinical translation.

MRI radiomics-based machine learning classification of atypical cartilaginous tumour and grade II chondrosarcoma of long bones

Background

Atypical cartilaginous tumour (ACT) and grade II chondrosarcoma (CS2) of long bones are respectively managed with watchful waiting or curettage and wide resection. Preoperatively, imaging diagnosis can be challenging due to interobserver variability and biopsy suffers from sample errors. The aim of this study is to determine diagnostic performance of MRI radiomics-based machine learning in differentiating ACT from CS2 of long bones.

Methods

One-hundred-fifty-eight patients with surgically treated and histology-proven cartilaginous bone tumours were retrospectively included at two tertiary bone tumour centres. The training cohort consisted of 93 MRI scans from centre 1 (n=74 ACT; n=19 CS2). The external test cohort consisted of 65 MRI scans from centre 2 (n=45 ACT; n=20 CS2). Bidimensional segmentation was performed on T1-weighted MRI. Radiomic features were extracted. After dimensionality reduction and class balancing in centre 1, a machine-learning classifier (Extra Trees Classifier) was tuned on the training cohort using 10-fold cross-validation and tested on the external test cohort. In centre 2, its performance was compared with an experienced musculoskeletal oncology radiologist using McNemar's test.

Findings

After tuning on the training cohort (AUC=0.88), the machine-learning classifier had 92% accuracy (60/65, AUC=0.94) in identifying the lesions in the external test cohort. Its accuracies in correctly classifying ACT and CS2 were 98% (44/45) and 80% (16/20), respectively. The radiologist had 98% accuracy (64/65) with no difference compared to the classifier (p=0.134).

Interpretation

Machine learning showed high accuracy in classifying ACT and CS2 of long bones based on MRI radiomic features.

Funding

ESSR Young Researchers Grant.

Prevalence of Enchondromas of the Proximal Femur in Adults as an Incidental Finding on MRI of the Pelvis

Objective  To determine the prevalence of enchondroma in adults as an incidental finding in the proximal femur on magnetic resonance imaging (MRI). Materials and Methods  A retrospective review of the MRI scans of the pelvis in a series of adult patients was conducted. All presented with nononcological musculoskeletal complaints. The site, size, and appearances of the enchondromas were identified according to criteria from previous studies. Results  A total of 1,209 proximal femora in 610 patients were reviewed and a total of 9 enchondromas were identified. These ranged from 0.6 to 2.5 cm in length (mean 1.3 cm). None showed aggressive features suggestive of malignancy. Three cases (33%) underwent follow-up MRI scans which showed no change in size or morphology. Conclusion  The prevalence on MRI of incidental enchondromas arising in the proximal femur is 0.7%. This is three to four times less common than seen in the proximal humerus and around the knee.

Effects of Interobserver Variability on 2D and 3D CT- and MRI-Based Texture Feature Reproducibility of Cartilaginous Bone Tumors

This study aims to investigate the influence of interobserver manual segmentation variability on the reproducibility of 2D and 3D unenhanced computed tomography (CT)- and magnetic resonance imaging (MRI)-based texture analysis. Thirty patients with cartilaginous bone tumors (10 enchondromas, 10 atypical cartilaginous tumors, 10 chondrosarcomas) were retrospectively included. Three radiologists independently performed manual contour-focused segmentation on unenhanced CT and T1-weighted and T2-weighted MRI by drawing both a 2D region of interest (ROI) on the slice showing the largest tumor area and a 3D ROI including the whole tumor volume. Additionally, a marginal erosion was applied to both 2D and 3D segmentations to evaluate the influence of segmentation margins. A total of 783 and 1132 features were extracted from original and filtered 2D and 3D images, respectively. Intraclass correlation coefficient ≥ 0.75 defined feature stability. In 2D vs. 3D contour-focused segmentation, the rates of stable features were 74.71% vs. 86.57% (p < 0.001), 77.14% vs. 80.04% (p = 0.142), and 95.66% vs. 94.97% (p = 0.554) for CT and T1-weighted and T2-weighted images, respectively. Margin shrinkage did not improve 2D (p = 0.343) and performed worse than 3D (p < 0.001) contour-focused segmentation in terms of feature stability. In 2D vs. 3D contour-focused segmentation, matching stable features derived from CT and MRI were 65.8% vs. 68.7% (p = 0.191), and those derived from T1-weighted and T2-weighted images were 76.0% vs. 78.2% (p = 0.285). 2D and 3D radiomic features of cartilaginous bone tumors extracted from unenhanced CT and MRI are reproducible, although some degree of interobserver segmentation variability highlights the need for reliability analysis in future studies.

Midterm MRI Follow-Up of Untreated Enchondroma and Atypical Cartilaginous Tumors in the Long Bones

Simple Summary

Over the last decade the incidence of enchondroma and atypical cartilaginous bone tumors (ACTs) increased enormously. Management of these tumors in the long bones is shifting towards active surveillance, as negative side effects of surgical treatment seem to outweigh the potential benefits. To support development of evidence-based guidelines for active surveillance, we studied the natural course of enchondroma and ACTs in the long bones. In this study, MRI analysis of 128 cases was performed with a minimum interval of 24 months between baseline and last MRI. Our data showed that the majority of the cartilaginous tumors (87%) remained stable or showed regression on MRI. Only 13% showed some progression on MRI, although none of the tumors developed characteristics of high-grade chondrosarcoma. Based on our results, active surveillance is considered safe for enchondroma and ACTs of the long bones, and follow-up schemes should be tailored on natural course.

Abstract

Management of atypical cartilaginous tumors (ACTs) in the long bones is shifting towards active surveillance to avoid unnecessary surgeries. The frequency and duration of active surveillance for these tumors is unclear as there is little knowledge of its biological behavior. In this retrospective study, we examined the natural course of enchondroma and ACTs through active surveillance. A total of 128 central cartilaginous tumors, located in the long bones, with a minimum interval of 24 months between baseline and last MRI were included. MRI characteristics (e.g., size, scalloping, fat entrapment) were scored and tumors were classified according to the changes between MRIs. Mean follow-up of this study was 50 months, range = 25–138 months. The majority of the cartilaginous tumors (87%) remained stable (n = 65) or showed regression (n = 46) on MRI. A total of 87% of the cases that developed tumor regression presented with entrapped fat at diagnosis. Only 13% (n = 17) showed some progression on MRI, although none of the tumors developed characteristics of high-grade chondrosarcoma. Based on our results, active surveillance is considered safe for enchondroma and ACTs of the long bones. We propose active surveillance for all asymptomatic enchondroma or ACTs in the long bones irrespective of tumor size, and follow-up schemes should be tailored on natural course.

Incidental long bone cartilage lesions: is any further imaging workup needed?

OBJECTIVE

To determine the rate of chondrosarcoma in incidentally discovered painless long bone cartilage lesions and to determine if any further imaging is needed.

MATERIALS AND METHODS

A cartilage lesion was said to be an enchondroma when it had characteristic matrix mineralization and no aggressive features. Search of all imaging reports and tumor board files for keywords enchondroma, cartilage lesion, chondroid, and chondrosarcoma. Retrospective review of medical records and imaging studies from 4.5-year period. Data points collected included patient age, sex, lesion site, size, symptoms, type of imaging, imaging appearance, and length of follow-up. Only patients with no pain were included as enchondroma. Patients with final diagnosis of chondrosarcoma were included for comparison of all features.

RESULTS

Only 1/73 (1.4%) patients with an initial incidentally discovered painless lesion was later diagnosed, with new symptoms, as atypical cartilage tumor. Average age was 59.4 years. Bones involved were the femur (n = 33), humerus (n = 30), tibia (n = 7), fibula (n = 2), and ulna (n = 1). Average enchondroma size was 3.9 cm (range 1.4-11.5). Average follow-up was 47 months (range 2-196 months). Eleven long bone chondrosarcomas were identified. All chondrosarcoma patients had pain and aggressive imaging findings.

CONCLUSION

Our study reveals that the rate of chondrosarcoma in incidentally found painless chondroid lesions without aggressive features in long bones is low. Imaging follow-up may be needed only in the setting of new symptoms.

CT radiomics-based machine learning classification of atypical cartilaginous tumours and appendicular chondrosarcomas

Background

Clinical management ranges from surveillance or curettage to wide resection for atypical to higher-grade cartilaginous tumours, respectively. Our aim was to investigate the performance of computed tomography (CT) radiomics-based machine learning for classification of atypical cartilaginous tumours and higher-grade chondrosarcomas of long bones.

Methods

One-hundred-twenty patients with histology-proven lesions were retrospectively included. The training cohort consisted of 84 CT scans from centre 1 (n=55 G1 or atypical cartilaginous tumours; n=29 G2-G4 chondrosarcomas). The external test cohort consisted of the CT component of 36 positron emission tomography-CT scans from centre 2 (n=16 G1 or atypical cartilaginous tumours; n=20 G2-G4 chondrosarcomas). Bidimensional segmentation was performed on preoperative CT. Radiomic features were extracted. After dimensionality reduction and class balancing in centre 1, the performance of a machine-learning classifier (LogitBoost) was assessed on the training cohort using 10-fold cross-validation and on the external test cohort. In centre 2, its performance was compared with preoperative biopsy and an experienced radiologist using McNemar's test.

Findings

The classifier had 81% (AUC=0.89) and 75% (AUC=0.78) accuracy in identifying the lesions in the training and external test cohorts, respectively. Specifically, its accuracy in classifying atypical cartilaginous tumours and higher-grade chondrosarcomas was 84% and 78% in the training cohort, and 81% and 70% in the external test cohort, respectively. Preoperative biopsy had 64% (AUC=0.66) accuracy (p=0.29). The radiologist had 81% accuracy (p=0.75).

Interpretation

Machine learning showed good accuracy in classifying atypical and higher-grade cartilaginous tumours of long bones based on preoperative CT radiomic features.

Funding

ESSR Young Researchers Grant.

Conventional Cartilaginous Tumors: Evaluation and Treatment

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Enchondromas are benign cartilaginous lesions that rarely require surgical intervention.

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Atypical cartilaginous tumors (ACTs), also referred to as grade-1 chondrosarcomas, may be managed without any intervention or with extended intralesional curettage and bone-void filling.

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High-grade chondrosarcomas, or grade-2 and 3 chondrosarcomas, should be managed aggressively with wide resection.

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Chemotherapy and radiation do not currently play a role in the treatment of chondrosarcomas.

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Differentiating an enchondroma from an ACT and an ACT from a high-grade chondrosarcoma can be difficult and requires clinical experience, radiographic and advanced imaging, and possibly a biopsy. Ultimately, a multidisciplinary team that includes a musculoskeletal oncologist, a radiologist, and a pathologist is needed to make the most appropriate diagnosis and treatment plan for each patient.

Acral Dedifferentiated Chondrosarcoma: Report of a Case Arising in the Proximal Phalanx of the Fourth Finger

Dedifferentiated chondrosarcoma is a well-recognized entity, but its occurrence in the distal extremities is exceedingly rare. We present the case of a 49-year-old woman who experienced local recurrence of an "enchondroma" of the proximal phalanx of the fourth finger of the left hand, which had been initially treated with intralesional curettage at another hospital 4 years before, and 1 year before for a local recurrence. The imaging findings indicated an aggressive behavior, and an incisional biopsy showed a highly cellular proliferation of spindle and pleomorphic elements without evidence of matrix production intermixed with few fragments of a well-differentiated cartilaginous neoplasm with bland cellular atypia, focal nuclear hyperchromatism, and binucleation. An isocitrate dehydrogenase 2 R172S mutation was detected. The final diagnosis was dedifferentiated chondrosarcoma. Despite amputation of the fourth finger, the patient developed lung metastases and further local relapse. Recurrent cartilaginous tumors of the extremities should not be underestimated and should be followed in view of the possible acquisition of aggressive clinical behavior.

MRI radiomics-based machine-learning classification of bone chondrosarcoma

PURPOSE

To evaluate the diagnostic performance of machine learning for discrimination between low-grade and high-grade cartilaginous bone tumors based on radiomic parameters extracted from unenhanced magnetic resonance imaging (MRI).

METHODS

We retrospectively enrolled 58 patients with histologically-proven low-grade/atypical cartilaginous tumor of the appendicular skeleton (n = 26) or higher-grade chondrosarcoma (n = 32, including 16 appendicular and 16 axial lesions). They were randomly divided into training (n = 42) and test (n = 16) groups for model tuning and testing, respectively. All tumors were manually segmented on T1-weighted and T2-weighted images by drawing bidimensional regions of interest, which were used for first order and texture feature extraction. A Random Forest wrapper was employed for feature selection. The resulting dataset was used to train a locally weighted ensemble classifier (AdaboostM1). Its performance was assessed via 10-fold cross-validation on the training data and then on the previously unseen test set. Thereafter, an experienced musculoskeletal radiologist blinded to histological and radiomic data qualitatively evaluated the cartilaginous tumors in the test group.

RESULTS

After feature selection, the dataset was reduced to 4 features extracted from T1-weighted images. AdaboostM1 correctly classified 85.7 % and 75 % of the lesions in the training and test groups, respectively. The corresponding areas under the receiver operating characteristic curve were 0.85 and 0.78. The radiologist correctly graded 81.3 % of the lesions. There was no significant difference in performance between the radiologist and machine learning classifier (P = 0.453).

CONCLUSIONS

Our machine learning approach showed good diagnostic performance for classification of low-to-high grade cartilaginous bone tumors and could prove a valuable aid in preoperative tumor characterization.