MRI assessment of surrounding tissues in soft-tissue sarcoma during neoadjuvant chemotherapy can help predicting response and prognosis

Inferring malignancy grade of soft tissue sarcomas from magnetic resonance imaging features: A systematic review

PURPOSE

Systematic reviews on the grading of STS using MRI are lacking. This review analyses the role of different MRI features in inferring the histological grade of STS.

MATERIALS AND METHODS

A systematic review was conducted and is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) checklist. The electronic databases of PubMed/MEDLINE were systematically searched for literature addressing the correlation of MRI findings in soft tissue sarcoma with tumor grade. As keywords "MRI", "magnetic resonance imaging", "sarcoma", "grade", "grading", and "FNCLCC" have been selected.

RESULTS

14 studies have been included in this systematic review. Tumor size (p = 0.015 (51 patients) to p = 0.81 (36 patients)), tumor margin (p < 0.001 (95 patients) to 0.93 (36 patients)), necrosis (p = 0.004 (50 patients) to p = 0.65 (95 patients)), peritumoral edema (p = 0.002 (130 patients) to p = 0.337 (40 patients)), contrast enhancement (p < 0.01 (50 patients) to 0.019 (51 patients)) and polycyclic/multilobulated tumor configuration (p = 0.008 (71 patients)) were significantly associated with STS malignancy grade in most of the included studies. Heterogeneity in T2w images (p = 0.003 (130 patients) to 0.202 (40 patients)), signal intensity in T1w images/ hemorrhage (p = 0.02 (130 patients) to 0.5 (31 patients)), peritumoral contrast enhancement (p < 0.001 (95 patients) to 0.253 (51 patients)) and tumoral diffusion restriction (p = 0.01 (51 patients) to 0.53 (52 patients)) were regarded as significantly associated with FNCLCC grade in some of the studies which investigated these features. Most other MRI features were not significant.

CONCLUSION

Several MRI features, such as tumor size, necrosis, peritumoral edema, peritumoral contrast enhancement, intratumoral contrast enhancement, and polycyclic/multilobulated tumor configuration may indicate the malignancy grade of STS. However, further studies are needed to gain consensus.

Role of magnetic resonance imaging in the prediction of histological grade in soft tissue sarcomas

BACKGROUND

Soft tissue sarcomas are rare malignant tumors with significant heterogeneity. The importance of classifying histological grades is fundamental to defining the treatment approach.

OBJECTIVE

To evaluate magnetic resonance imaging (MRI) in predicting the histological grade of soft tissue sarcomas.

METHODS

A retrospective observational study included patients over 18 years undergoing MRI and primary tumor surgery at AC Camargo Cancer Center from January 2015 to June 2022. Two radiologists evaluated MRI criteria (size, margin definition, heterogeneity of the T2 signal, high-intensity peritumoral signal on T2, and postperitumoral contrast), and a grading prediction score was calculated. χ2 and logistic regression analyses were conducted.

RESULTS

Sixty-eight patients were included (38 men; median: 48 years). Moreover, 52 high-grade and 16 low-grade tumors were observed. The MRI criteria associated with histological grade were peritumoral high-intensity T2-weighted signals (p < 0.001) and peritumoral postcontrast enhancement (p = 0.006). Logistic regression confirmed their significance (odds ratio [OR]: 11.8 and 8.8, respectively). Each score point increment doubled the chance of high-grade tumors (OR: 2.0; p = 0.014).

CONCLUSION

MRI effectively predicts histological grades of soft tissue sarcomas. Peritumoral high-intensity T2-weighted signals and peritumoral postcontrast enhancement are valuable indicators of high-grade tumors. This highlights MRI's importance in treatment decision-making for sarcoma patients.

[Predictive factors assessment of pathological response to neoadjuvant radiotherapy of soft tissue sarcomas]

PURPOSE

Conserving surgery combined with radiotherapy in presence of local recurrence risk factors is standard treatment of soft tissue sarcomas, a group of rare and heterogeneous tumours. Radiotherapy is performed before or after surgery. In neoadjuvant setting, late radiation-induced toxicity is reduced and pathological response to radiotherapy could be achieved. A complete pathological response to radiotherapy has recently been shown to predict better survival. Our study aims at identifying predictive factors of pathological response to neoadjuvant radiotherapy (clinical, radiological or histological) of soft tissue sarcomas.

PATIENTS AND METHODS

Clinical, imaging (MRI: perilesional oedema, necrosis, tumour heterogeneity, vasculonervous relationships) and pathological (pathological subtype, tumour grade, anticipated/obtained resection quality) data were retrospectively collected. Tumour response (imaging and pathological), patient outcome, acute and late radiation-induced toxicity, predictive factors of pathological response to neoadjuvant radiotherapy were studied. The 2-test or exact-Fisher test (qualitative variables) and by Student's t-test or Kruskal-Wallis test (quantitative variables) were used for statistical analysis.

RESULTS

From April 2017 to April 2021, neoadjuvant radiotherapy (50Gy in 25 fractions) followed by surgical excision was performed to 36 consecutive patients with liposarcomas (n=17/36), or undifferentiated sarcomas (n=8/36). MRI response was complete in 1 patient, partial in 9 patients (n=9/36, 25%), stable in 21 patients (n=21/36, 58%) or in progression in 5 patients (n=5/36, 14%). Pathological response was observed in 22 patients (61%). No grade 3-4 acute radiation-induced toxicity was observed. Regarding late toxicity, 28% of patients had grade 1-2 oedema (n=10/36), 39% had a grade 1 fibrosis (n=14/36), and 30% grade 1 pain (n=11/36). No predictive factors of response to radiotherapy was statistically significant.

CONCLUSIONS

Neoadjuvant radiotherapy is well-tolerated. No clinical, radiological or pathological predictive factors was identified for radiotherapy tumour response.

The Impact of Edema on MRI Radiomics for the Prediction of Lung Metastasis in Soft Tissue Sarcoma

INTRODUCTION

This study aimed to evaluate whether radiomic features extracted solely from the edema of soft tissue sarcomas (STS) could predict the occurrence of lung metastasis in comparison with features extracted solely from the tumoral mass.

MATERIALS AND METHODS

We retrospectively analyzed magnetic resonance imaging (MRI) scans of 32 STSs, including 14 with lung metastasis and 18 without. A segmentation of the tumor mass and edema was assessed for each MRI examination. A total of 107 radiomic features were extracted for each mass segmentation and 107 radiomic features for each edema segmentation. A two-step feature selection process was applied. Two predictive features for the development of lung metastasis were selected from the mass-related features, as well as two predictive features from the edema-related features. Two Random Forest models were created based on these selected features; 100 random subsampling runs were performed. Key performance metrics, including accuracy and area under the ROC curve (AUC), were calculated, and the resulting accuracies were compared.

RESULTS

The model based on mass-related features achieved a median accuracy of 0.83 and a median AUC of 0.88, while the model based on edema-related features achieved a median accuracy of 0.75 and a median AUC of 0.79. A statistical analysis comparing the accuracies of the two models revealed no significant difference.

CONCLUSION

Both models showed promise in predicting the occurrence of lung metastasis in soft tissue sarcomas. These findings suggest that radiomic analysis of edema features can provide valuable insights into the prediction of lung metastasis in soft tissue sarcomas.

Role of Imaging in Initial Prognostication of Locally Advanced Soft Tissue Sarcomas

BACKGROUND

Although imaging is central in the initial staging of patients with soft tissue sarcomas (STS), it remains underused and few radiological features are currently used in practice for prognostication and to help guide the best therapeutic strategy. Yet, several prognostic qualitative and quantitative characteristics from magnetic resonance imaging (MRI) and positron emission tomography (PET) have been identified over these last decades.

OBJECTIVE

After an overview of the current validated prognostic features based on baseline imaging and their integration into prognostic tools, such as nomograms used by clinicians, the aim of this review is to summarize more complex and innovative MRI, PET, and radiomics features, and to highlight their role to predict indirectly (through histologic grade) or directly the patients' outcomes.

Distinct patterns of the natural evolution of soft tissue sarcomas on pre-treatment MRIs captured with delta-radiomics correlate with gene expression profiles

OBJECTIVES

Radiomics of soft tissue sarcomas (STS) is assumed to correlate with histologic and molecular tumor features, but radiogenomics analyses are lacking. Our aim was to identify if distinct patterns of natural evolution of STS obtained from consecutive pre-treatment MRIs are associated with differential gene expression (DGE) profiling in a pathway analysis.

METHODS

All patients with newly diagnosed STS treated in a curative intent in our sarcoma reference center between 2008 and 2019 and with two available pre-treatment contrast-enhanced MRIs were included in this retrospective study. Radiomics features (RFs) were extracted from fat-sat contrast-enhanced T1-weighted imaging. Log ratio and relative change in RFs were calculated and used to determine grouping of samples based on a consensus hierarchical clustering. DGE and oncogenesis pathway analysis were performed in the delta-radiomics groups identified in order to detect associations between delta-radiomics patterns and transcriptomics features of STS. Secondarily, the prognostic value of the delta-radiomics groups was investigated.

RESULTS

Sixty-three patients were included (median age: 63 years, interquartile range: 52.5-70). The consensus clustering identified 3 reliable delta-radiomics patient groups (A, B, and C). On imaging, group B patients were characterized by increase in tumor heterogeneity, necrotic signal, infiltrative margins, peritumoral edema, and peritumoral enhancement before the treatment start (p value range: 0.0019-0.0244), and, molecularly, by downregulation of natural killer cell-mediated cytotoxicity genes and upregulation of Hedgehog and Hippo signaling pathways. Group A patients were characterized by morphological stability of pre-treatment MRI traits and no local relapse (log-rank p = 0.0277).

CONCLUSIONS

This study highlights radiomics and transcriptomics convergence in STS. Proliferation and immune response inhibition were hyper-activated in the STS that were the most evolving on consecutive imaging.

KEY POINTS

• Three consensual and stable delta-radiomics clusters were identified and captured the natural patterns of morphological evolution of STS on pre-treatment MRIs. • These 3 patterns were explainable and correlated with different well-known semantic radiological features with an ascending gradient of pejorative characteristics from the A group to C group to B group. • Gene expression profiling stressed distinct patterns of up/downregulated oncogenetic pathways in STS from B group in keeping with its most aggressive radiological evolution.

Added value of contrast-enhanced ultrasound to conventional ultrasound for characterization of indeterminate soft-tissue tumors

OBJECTIVE

To assess the added value of contrast-enhanced ultrasound (CEUS) to conventional ultrasound in differentiating benign soft-tissue tumors from malignant ones.

METHODS

197 soft-tissue tumors underwent ultrasound examination with confirmed histopathology were retrospectively evaluated. The radiologists classified all the tumors as benign, malignant, or indeterminate according to ultrasound features. The indeterminate tumors underwent CEUS were reviewed afterwards for malignancy identification by using individual and combined CEUS features.

RESULTS

Ultrasound analysis classified 62 soft-tissue tumors as benign, 111 tumors as indeterminate and 24 tumors as malignant. There 104 indeterminate tumors were subject to CEUS. Three CEUS features including enlargement of enhancement area, infiltrative enhancement boundary, and intratumoral arrival time difference were significantly associated with the tumor nature in both univariable and multivariable analysis for the indeterminate tumors (all p < 0.05). When at least one out of the three discriminant CEUS features were present, the best sensitivity of 100% for malignancy identification was obtained with the specificity of 66.7% and the AUC of 0.833. When at least two of the three discriminant CEUS features were present, the best area under the receiver operating characteristic curve (AUC) of 0.924 for malignancy identification was obtained. The combination of at least two discriminant CEUS features showed much better diagnostic performance than the optimal combination of ultrasound features in terms of AUC (0.924 vs 0.608, p < 0.0001), sensitivity (94.0% vs 42.0%, p < 0.0001), and specificity (90.7% vs 79.6%, p = 0.210) for the indeterminate tumors.

CONCLUSION

The combination CEUS features of enlargement of enhancement area, infiltrative enhancement boundary and intratumoral arrival time difference are valuable to improve the discriminating performance for indeterminate soft-tissue tumors on conventional ultrasound.

ADVANCES IN KNOWLEDGE

The combination of peritumoral and arrival-time CEUS features can improve the discriminating performance for indeterminate soft-tissue tumors on conventional ultrasound.

Soft Tissue Sarcomas: The Role of Quantitative MRI in Treatment Response Evaluation

BACKGROUND

Although curative surgery remains the cornerstone of the therapeutic strategy in patients with soft tissue sarcomas (STS), neoadjuvant radiotherapy and chemotherapy (NART and NACT, respectively) are increasingly used to improve operability, surgical margins and patient outcome. The best imaging modality for locoregional assessment of STS is MRI but these tumors are mostly evaluated in a qualitative manner.

OBJECTIVE

After an overview of the current standard of care regarding treatment for patients with locally advanced STS, this review aims to summarize the principles and limitations of (i) the current methods used to evaluate response to neoadjuvant treatment in clinical practice and clinical trials in STS (RECIST 1.1 and modified Choi criteria), (ii) quantitative MRI sequences (i.e., diffusion weighted imaging and dynamic contrast enhanced MRI), and (iii) texture analyses and (delta-) radiomics.

Radiomics Analysis of Fat-Saturated T2-Weighted MRI Sequences for the Prediction of Prognosis in Soft Tissue Sarcoma of the Extremities and Trunk Treated With Neoadjuvant Radiotherapy

Purpose

To create a prognostic prediction radiomics model for soft tissue sarcoma (STS) of the extremities and trunk treated with neoadjuvant radiotherapy.

Methods

This study included 62 patients with STS of the extremities and trunk who underwent magnetic resonance imaging (MRI) before neoadjuvant radiotherapy. After tumour segmentation and preprocessing, 851 radiomics features were extracted. The radiomics score was constructed according to the least absolute shrinkage and selection operator (LASSO) method. Survival analysis (disease-free survival; DFS) was performed using the log-rank test and Cox’s proportional hazards regression model. The nomogram model was established based on the log-rank test and Cox regression model. Harrell’s concordance index (C-index), calibration curve and receiver operating characteristic (ROC) curve analysis were used to evaluate the prognostic factors. The clinical utility of the model was assessed by decision curve analysis (DCA).

Results

The univariate survival analysis showed that tumour location (p = 0.032), clinical stage (p = 0.022), tumour size (p = 0.005) and the radiomics score were correlated with DFS (p < 0.05). The multivariate analysis showed that tumour location, tumour size, and the radiomics score were independent prognostic factors for DFS (p < 0.05). The combined clinical-radiomics model based on the multivariate analysis showed the best predictive ability for DFS (C-index: 0.781; Area Under Curve: 0.791). DCA revealed that the use of the radiomics score-based nomogram was associated with better benefit gains relative to the prediction of 2-year DFS events than other models in the threshold probability range between 0.12 and 0.38.

Conclusion

The radiomics score from pretreatment MRI is an independent prognostic factor for DFS in patients with STS of the extremities and trunk. The radiomics score-based nomogram could improve prognostic stratification ability and thus contribute to individualized therapy for STS patients.

Magnetic resonance imaging of soft tissue sarcoma: features related to prognosis

Magnetic Resonance Imaging is a fundamental tool in the evaluation of soft tissue sarcoma. Imaging features are relevant for the assessment of treatment strategies, surgical planning and also for patients' prognosis prediction. Among soft tissue sarcoma and also other malignancies, the size of the mass is usually considered the prognostic key element in diagnostic imaging. Moreover, several other features should be obtained from MRI studies with prognostic implications in all type of soft tissue sarcoma: peritumoral enhancement, signs of necrosis, deep location, ill-defined borders/signs of infiltrations. Focusing on soft tissue sarcoma subtypes, some other magnetic resonance imaging features are more specific and related to prognosis. In myxofibrosarcoma the magnetic resonance imaging "tail sign" and a "water-like" appearance on fluid-sensitive sequences, due to rich myxoid matrix content, are both associated with higher risk of local recurrence after surgical excision; nevertheless, the "tail sign" is also related to a higher risk of distant metastases at diagnosis. The "tail sign" is associated with higher risk of local recurrence after surgical excision in undifferentiated pleomorphic sarcoma as well. In patients affected by synovial sarcoma, the "triple sign" identifiable in magnetic resonance imaging (T2w sequences) is associated with decreased disease-free survival and indicates the simultaneous presence of solid cellular elements (intermediate signal intensity), hemorrhage or necrosis (high signal intensity) and fibrotic regions (low signal intensity). In addition, absence of calcifications are associated with reduced disease-free survival in patients affected by synovial sarcoma. Signal heterogeneity is associated with worst prognosis in all type of soft tissue sarcoma, particularly in myxoid liposarcoma. In recent years, several new quantitative tools applied on magnetic resonance imaging have been proved to predict patients' prognosis. Above all the new tools, radiomics seems to be one of the most promising, and, has been proved to have the capability in discriminating low-grade from high-grade soft tissue sarcomas. Therefore, magnetic resonance imaging studies in patients with soft tissue sarcoma should be accurately evaluated and their results should be taken into account for prognostic assessment.

Imaging response evaluation after neoadjuvant treatment in soft tissue sarcomas: Where do we stand?

Soft tissue sarcomas (STS) represent a broad family of rare tumours for which surgery with radiotherapy represents first-line treatment. Recently, neoadjuvant chemo-radiotherapy has been increasingly used in high-risk patients in an effort to reduce surgical morbidity and improve clinical outcomes. An adequate understanding of the efficacy of neoadjuvant therapies would optimise patient care, allowing a tailored approach. Although response evaluation criteria in solid tumours (RECIST) is the most common imaging method to assess tumour response, Choi criteria and functional and molecular imaging (DWI, DCE-MRI and ¹⁸F-FDG-PET) seem to outperform it in the discrimination between responders and non-responders. Moreover, the radiologic-pathology correlation of treatment-related changes remains poorly understood. In this review, we provide an overview of the imaging assessment of tumour response in STS undergoing neoadjuvant treatment, including conventional imaging (CT, MRI, PET) and advanced imaging analysis. Future directions will be presented to shed light on potential advances in pre-surgical imaging assessments that have clinical implications for sarcoma patients.

Value of intravoxel incoherent motion and diffusion kurtosis imaging in predicting peritumoural infiltration of soft-tissue sarcoma: a prospective study based on MRI-histopathology comparisons

AIM

To investigate the performance of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) in the identification of peritumoural infiltration of soft-tissue sarcoma (STS).

MATERIALS AND METHODS

From July 2018 to January 2020, 34 STS patients who underwent 3-T magnetic resonance imaging (MRI), including IVIM and DKI, were reviewed. The standard apparent diffusion coefficient (ADC), true diffusion (D), pseudo-diffusion coefficient (D∗), perfusion fraction (f), mean kurtosis (MK), and mean diffusion (MD) of each lesion were analysed independently by two observers. An MRI-histopathology control method was used to ensure the correspondence of MRI sections with histopathological sections. Differences in STS with and without infiltration were evaluated. The area under the curve (AUC) was used to determine the best cut-off point for different parameters. Interobserver agreement was assessed using the intraclass correlation coefficient.

RESULTS

Standard ADC, D, MK, and MD values reliably distinguished STS that had positive and negative infiltration. The MD value had the best diagnostic performance. Use of an MD cut-off value of 2.35 × 10^-3 mm²/s to distinguish positive and negative infiltration had an AUC of 0.85, accuracy of 88.2%, sensitivity of 94.4%, and specificity of 81.3%. The two independent observers had nearly perfect agreement for all parameters.

CONCLUSION

The standard ADC and D value of IVIM, and the MK and MD values of DKI reliably identify the presence of peritumoural infiltration of STS.

Magnetic resonance imaging assessment of chemotherapy-related adipocytic maturation in myxoid/round cell liposarcomas: specificity and prognostic value

OBJECTIVE

To investigate the specificity, clinical implication and prognostic value of MRI adipocytic maturation (MAM) in myxoid/round cells liposarcomas (MRC-LPS) treated with neoadjuvant chemotherapy (NAC).

METHODS

Of the 89 patients diagnosed with MRC-LPS at our sarcoma reference center between 2008 and 2018, 28 were included as they were treated with NAC, surgery and radiotherapy. All patients underwent contrast-enhanced MRIs at baseline and late evaluation. A control cohort of 13 high-grade pleomorphic and dedifferentiated LPS with same inclusion criteria was used to evaluate the specificity of MAM in MRC-LPS. Two radiologists analyzed the occurrence of MAM, changes in the tumor architecture, shape and surrounding tissues during NAC. Pathological features of tumor samples were reviewed and correlated with MRI. Metastatic relapse-free survival was estimated with Kaplan-Meier curves and Cox models. Associations between prognostic T1-based delta-radiomics features and MAM were investigated with Student t-test.

RESULTS

MAM was more frequent in MRC-LPS (p = 0.045) and not specific of any type of chemotherapy (p = 0.7). Regarding MRC-LPS, 14 out of 28 patients (50%) demonstrated MAM. Eight patients showed metastatic relapses. MAM was not associated with metastatic relapse-free survival (p = 0.9). MAM correlated strongly with the percentage of histological adipocytic differentiation on surgical specimen (p < 0.001), which still expressed the tumor marker NY-ESO-1. None of the prognostic T1-based delta-radiomics features was associated with MAM.

CONCLUSION

MAM seems a neutral event during NAC.

ADVANCES IN KNOWLEDGE

MAM predominated in MRC-LPS and was not specific of a type of chemotherapy. Occurrence of MAM was not associated with better patients' metastasis free survival.