CT-response patterns and the role of CT-textural features in inoperable abdominal/retroperitoneal soft tissue sarcomas treated with trabectedin

Pseudoprogression in patients with uterine leiomyosarcoma treated with first-line single-agent doxorubicin

AIM

To evaluate the incidence of pseudoprogression in patients with metastatic or inoperable uterine leiomyosarcoma (LMS) treated with first-line single-agent doxorubicin.

METHODS

The Royal Marsden NHS Foundation Trust Sarcoma Unit database was searched to identify all patients with metastatic or inoperable LMS treated with first-line doxorubicin from January 2006 to January 2022. Patients with available computed tomography scans performed at baseline and during doxorubicin therapy were included. Response evaluation criteria in solid tumours v1.1 and Choi criteria were applied. Any increase in the sum of the longest diameter that decreased on the subsequent scan was labelled as pseudoprogression.

RESULTS

The total number of patients evaluated was 52. In total, 19% (n = 10) of patients treated with doxorubicin showed pseudoprogression. However, pseudoprogression at the time of the second scan was not associated with time to doxorubicin failure. Choi criteria identified 30% (n = 3) of pseudoprogressors as responding.

CONCLUSION

Despite the use of doxorubicin as first-line therapy for soft-tissue sarcomas for over 40 years, pseudoprogression has not been described. This retrospective study shows that pseudoprogression occurs in 19% of patients with metastatic/inoperable uterine LMS treated with first-line doxorubicin. Choi criteria were not consistently able to differentiate pseudoprogression from true progression. It is imperative that oncologists and radiologists are aware of this as symptomatically stable/improving patients may benefit from continued treatment despite initial radiological growth in tumour size.

Can CT texture analysis parameters be used as imaging biomarkers for prediction of malignancy in canine splenic tumors?

Splenic hemangiosarcoma has morphological similarities to benign nodular hyperplasia. Computed tomography (CT) texture analysis can analyze the texture of images that the naive human eye cannot detect. Recently, there have been attempts to incorporate CT texture analysis with artificial intelligence in human medicine. This retrospective, analytical design study aimed to assess the feasibility of CT texture analysis in splenic masses and investigate predictive biomarkers of splenic hemangiosarcoma in dogs. Parameters for dogs with hemangiosarcoma and nodular hyperplasia were compared, and an independent parameter that could differentiate between them was selected. Discriminant analysis was performed to assess the ability to discriminate the two splenic masses and compare the relative importance of the parameters. A total of 23 dogs were sampled, including 16 splenic nodular hyperplasia and seven hemangiosarcoma. In each dog, total 38 radiomic parameters were extracted from first-, second-, and higher-order matrices. Thirteen parameters had significant differences between hemangiosarcoma and nodular hyperplasia. Skewness in the first-order matrix and GLRLM_LGRE and GLZLM_ZLNU in the second, higher-order matrix were determined as independent parameters. A discriminant equation consisting of skewness, GLZLM_LGZE, and GLZLM_ZLNU was derived, and the cross-validation verification result showed an accuracy of 95.7%. Skewness was the most influential parameter for the discrimination of the two masses. The study results supported using CT texture analysis to help differentiate hemangiosarcoma from nodular hyperplasia in dogs. This new diagnostic approach can be used for developing future machine learning-based texture analysis tools.

Radiomics in the Setting of Neoadjuvant Radiotherapy: A New Approach for Tailored Treatment

Simple Summary

This review based on a literature search aims at showing the impact of Texture Analysis in the prediction of response to neoadjuvant radiotherapy and/or chemoradiotherapy. The manuscript explores radiomics approaches in different fields of neoadjuvant radiotherapy, including esophageal cancer, lung cancer, sarcoma and rectal cancer in order to shed a light in the setting of neoadjuvant radiotherapy that can be used to tailor the best subsequent therapeutical strategy.

Abstract

Introduction: Neoadjuvant radiotherapy is currently used mainly in locally advanced rectal cancer and sarcoma and in a subset of non-small cell lung cancer and esophageal cancer, whereas in other diseases it is under investigation. The evaluation of the efficacy of the induction strategy is made possible by performing imaging investigations before and after the neoadjuvant therapy and is usually challenging. In the last decade, texture analysis (TA) has been developed to help the radiologist to quantify and identify the parameters related to tumor heterogeneity, which cannot be appreciated by the naked eye. The aim of this narrative is to review the impact of TA on the prediction of response to neoadjuvant radiotherapy and or chemoradiotherapy. Materials and Methods: Key references were derived from a PubMed query. Hand searching and ClinicalTrials.gov were also used. Results: This paper contains a narrative report and a critical discussion of radiomics approaches in different fields of neoadjuvant radiotherapy, including esophageal cancer, lung cancer, sarcoma, and rectal cancer. Conclusions: Radiomics can shed a light on the setting of neoadjuvant therapies that can be used to tailor subsequent approaches or even to avoid surgery in the future. At the same, these results need to be validated in prospective and multicenter trials.

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.

Personalising sarcoma care using quantitative multimodality imaging for response assessment

Over the last decades, technological developments in the field of radiology have resulted in a widespread use of imaging for personalising medicine in oncology, including patients with a sarcoma. New scanner hardware, imaging protocols, image reconstruction algorithms, radiotracers, and contrast media, enabled the assessment of the physical and biological properties of tumours associated with response to treatment. In this context, medical imaging has the potential to select sarcoma patients who do not benefit from (neo-)adjuvant treatment and facilitate treatment adaptation. Due to the biological heterogeneity in sarcomas, the challenge at hand is to acquire a practicable set of imaging features for specific sarcoma subtypes, allowing response assessment. This review provides a comprehensive overview of available clinical data on imaging-based response monitoring in sarcoma patients and future research directions. Eventually, it is expected that imaging-based response monitoring will help to achieve successful modification of (neo)adjuvant treatments and improve clinical care for these patients.

Eribulin Provides a Remarkable Effect in Trabectedin-Resistant Myxoid Liposarcoma

Adriamycin-based chemotherapy is commonly used for malignant soft tissue sarcoma including myxoid liposarcoma. However, in the case of unavailability or failure of the adriamycin-based regimen, trabectedin or eribulin can produce a good antitumor effect for myxoid liposarcoma. We relate the experience of a 64-year-old female with myxoid liposarcoma, who noticed a nodule on her left thigh and visited our institute. At initial presentation, the tumor was 18.7 cm in diameter, and the magnetic resonance imaging (MRI) showed a malignant lipomatous tumor with a myxoid component. We recommended that she undergo treatment; however, she refused. Three years later, the tumor had grown larger, so she finally decided to undergo treatment. A needle biopsy revealed a myxoid liposarcoma. The tumor massively involved the neurovascular structures; we thus determined that hip disarticulation was inevitable. Two years later, metastases in the right thigh, left lung, right ileum, and abdominal space were pointed out and chemotherapy was initiated. Adriamycin was unusable due to cardiac dysfunction, so trabectedin was administered; however, the tumors progressed. Eribulin was subsequently started and has been considerably effective for more than 2 years without severe adverse effects. In conclusion, we experienced a case showing the remarkable and long-lasting effect of eribulin against trabectedin-resistant myxoid liposarcoma.

Systematic review of sarcomas radiomics studies: Bridging the gap between concepts and clinical applications?

OBJECTIVES

Sarcomas are a model for intra- and inter-tumoral heterogeneities making them particularly suitable for radiomics analyses. Our purposes were to review the aims, methods and results of radiomics studies involving sarcomas METHODS: Pubmed and Web of Sciences databases were searched for radiomics or textural studies involving bone, soft-tissues and visceral sarcomas until June 2020. Two radiologists evaluated their objectives, results and quality of their methods, imaging pre-processing and machine-learning workflow helped by the items of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2), Image Biomarker Standardization Initiative (IBSI) and 'Radiomics Quality Score' (RQS). Statistical analyses included inter-reader agreements, correlations between methodological assessments, scientometrics indices, and their changes over years, and between RQS, number of patients and models performance.

RESULTS

Fifty-two studies were included involving: soft-tissue sarcomas (29/52, 55.8 %), bone sarcomas (15/52, 28.8 %), gynecological sarcomas (6/52, 11.5 %) and mixed sarcomas (2/52, 3.8 %), mostly imaged with MRI (36/52, 69.2 %), for a total of distinct patients. Median RQS was 4.5 (28.4 % of the maximum, range: -7 - 17). Performances of predictive models and number of patients negatively correlated (p = 0.027). None of the studies detailed all the items from the IBSI guidelines. There was a significant increase in studies' impact factors since the establishing of the RQS in 2017 (p = 0.038).

CONCLUSION

Although showing promising results, further efforts are needed to make sarcoma radiomics studies reproducible with an acceptable level of evidence. A better knowledge of the RQS and IBSI reporting guidelines could improve the quality of sarcoma radiomics studies and accelerate clinical applications.

CT-morphologic and CT-textural patterns of response in inoperable soft tissue sarcomas treated with pazopanib-a preliminary retrospective cohort study

OBJECTIVE

To analyze patterns of response in soft tissue sarcomas exposed to pazopanib using CT-morphologic and textural features and their suitability for evaluating therapeutic response.

METHODS

Retrospective evaluation of CT response and texture patterns in 33 patients (23 female; mean age: 61.2 years, range, 30-85 years) with soft tissue sarcomas treated with pazopanib from October 2008 to July 2017. Response evaluation was based on modified (m)CHOI-criteria and RECISTv.1.1 and classified as partial response (PR), stable disease (SD), progressive disease (PD). The following CT-texture (CTTA)-parameters were calculated: mean, entropy and uniformity of intensity/average/skewness/entropy of co-occurrence matrix and contrast of neighboring-gray-level-dependence-matrix.

RESULTS

Following mCHOI-criteria, 12 patients achieved PR, 7 SD and 14 PD. As per RECISTv.1.1 9 patients obtained PR, 9 SD and 15 PD. Frequent patterns of response were tumor liquefaction and necrosis (n=4/33, 12.1% each). Further patterns included shrinkage and cavitation (n=2/33, 6.1% each). In responders, differences in mean heterogeneity (p=0.01), intensity (p=0.03), average (p=0.03) and entropy of skewness (p=0.01) were found at follow-up whereas in non-responders, CTTA-parameters did not change significantly. Baseline-CTTA-features differed between responders and non-responders in terms of uniformity of skewness (p=0.045). Baseline-CTTA-parameters did not correlate with any morphologic response pattern.

CONCLUSION

Most frequent patterns of response to pazopanib were tumor liquefaction and necrosis. Single CT-textural features show strong association with the response to pazopanib-although limited in relation to specific response patterns.

ADVANCES IN KNOWLEDGE

Tumor liquefication and necrosis are important patterns of response to pazopanib. CT-texture analysis has limited associations with specific response patterns.