Evaluation of Soft Tissue Sarcoma Response to Preoperative Chemoradiotherapy Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging

Habitat escalated adaptive therapy (HEAT): a phase 2 trial utilizing radiomic habitat-directed and genomic-adjusted radiation dose (GARD) optimization for high-grade soft tissue sarcoma

BACKGROUND

Soft tissue sarcomas (STS), have significant inter- and intra-tumoral heterogeneity, with poor response to standard neoadjuvant radiotherapy (RT). Achieving a favorable pathologic response (FPR ≥ 95%) from RT is associated with improved patient outcome. Genomic adjusted radiation dose (GARD), a radiation-specific metric that quantifies the expected RT treatment effect as a function of tumor dose and genomics, proposed that STS is significantly underdosed. STS have significant radiomic heterogeneity, where radiomic habitats can delineate regions of intra-tumoral hypoxia and radioresistance. We designed a novel clinical trial, Habitat Escalated Adaptive Therapy (HEAT), utilizing radiomic habitats to identify areas of radioresistance within the tumor and targeting them with GARD-optimized doses, to improve FPR in high-grade STS.

METHODS

Phase 2 non-randomized single-arm clinical trial includes non-metastatic, resectable high-grade STS patients. Pre-treatment multiparametric MRIs (mpMRI) delineate three distinct intra-tumoral habitats based on apparent diffusion coefficient (ADC) and dynamic contrast enhanced (DCE) sequences. GARD estimates that simultaneous integrated boost (SIB) doses of 70 and 60 Gy in 25 fractions to the highest and intermediate radioresistant habitats, while the remaining volume receives standard 50 Gy, would lead to a > 3 fold FPR increase to 24%. Pre-treatment CT guided biopsies of each habitat along with clip placement will be performed for pathologic evaluation, future genomic studies, and response assessment. An mpMRI taken between weeks two and three of treatment will be used for biological plan adaptation to account for tumor response, in addition to an mpMRI after the completion of radiotherapy in addition to pathologic response, toxicity, radiomic response, disease control, and survival will be evaluated as secondary endpoints. Furthermore, liquid biopsy will be performed with mpMRI for future ancillary studies.

DISCUSSION

This is the first clinical trial to test a novel genomic-based RT dose optimization (GARD) and to utilize radiomic habitats to identify and target radioresistance regions, as a strategy to improve the outcome of RT-treated STS patients. Its success could usher in a new phase in radiation oncology, integrating genomic and radiomic insights into clinical practice and trial designs, and may reveal new radiomic and genomic biomarkers, refining personalized treatment strategies for STS.

TRIAL REGISTRATION

NCT05301283.

TRIAL STATUS

The trial started recruitment on March 17, 2022.

Magnetic Resonance Imaging Biomarkers of Bone and Soft Tissue Tumors

Magnetic resonance imaging (MRI) is essential in the management of musculoskeletal (MSK) tumors. This review delves into the diverse MRI modalities, focusing on anatomical, functional, and metabolic sequences that provide essential biomarkers for tumor detection, characterization, disease extent determination, and assessment of treatment response. MRI's multimodal capabilities offer a range of biomarkers that enhance MSK tumor evaluation, aiding in better patient management.

T2* Imaging Assessment of Neoadjuvant Radiation Therapy Combined With Pharmacological Ascorbate in Extremity Soft-Tissue Sarcomas: A Pilot Study

Background

Extremity soft-tissue sarcomas (STS) are commonly treated with neoadjuvant radiation therapy followed by surgical resection. However, the pathological near-complete response rate is low (9-25%). Noninvasive imaging assessment that predicts treatment response before and during treatment is desirable to optimize treatment regimens. This pilot study aimed to investigate the application of a quantitative MRI parameter, T2*, in assessing neoadjuvant radiation therapy combined with pharmacological ascorbate in extremity STS.

Methods

This prospective cohort study included seven patients diagnosed with extremity STS and scheduled to receive neoadjuvant radiation therapy combined with pharmacological ascorbate. T2* maps were obtained from each patient before treatment (baseline MRI), two weeks after initiating treatment (on-treatment MRI), and before surgery (pre-surgery MRI). The T2* values within the tumor region were transformed into z-scores with respect to the normal- appearing tissue region. The voxel-wise z-scores within the tumor region were thresholded to generate masks representing significantly high (z-score>1.96) and low z-score (z-score<-1.96) voxels. The means of the total z-scores and within each of the significantly high and low z-score mask were computed. Their correlations with percent necrosis from pathological examination were evaluated using Spearman's rank correlation coefficient r. A correlation was considered as moderate or strong when r is higher than 0.6 and 0.8, respectively. A correlation was considered as fair or weak when r is below 0.6.

Results

For the baseline and on-treatment MRIs, the means of the significantly high z-scores of the T2* measurements showed moderate correlations with percent necrosis (r = 0.68 and 0.6; p = 0.11 and 0.24). For the pre-surgery MRI, the means of the total and significantly high z-scores showed strong correlations with percent necrosis (r = 0.8 and 0.9; p = 0.13 and 0.08). Tumor volume and baseline MRI-based percent necrosis showed fair or weak correlations (r = 0.3-0.54; p = 0.24-0.68).

Conclusion

T2* measurements prior to treatment, two weeks after initiating treatment, and before surgery showed moderate to strong correlations with percent necrosis. These results support the potential for using T2* mapping to predict and assess response to neoadjuvant radiation therapy combined with pharmacological ascorbate in extremity STS. Level of Evidence: IV.

Non-invasive monitoring of neoadjuvant radiation therapy response in soft tissue sarcomas by multiparametric MRI and quantification of circulating tumor DNA-A study protocol

BACKGROUND

Wide resection remains the cornerstone of localized soft-tissue sarcomas (STS) treatment. Neoadjuvant radiation therapy (NRT) may decrease the risk of local recurrences; however, its effectiveness for different histological STS subtypes has not been systematically investigated. The proposed prospective study evaluates the NRT response in STS using liquid biopsies and the correlation of multiparametric magnetic resonance imaging (mpMRI) with histopathology and immunohistochemistry.

METHODS

Patients with localized high-grade STS, who qualify for NRT, are included in this study.

LIQUID BIOPSIES

Quantification of circulating tumor DNA (ctDNA) in patient blood samples is performed by targeted next-generation sequencing. Soft-tissue sarcoma subtype-specific panel sequencing in combination with patient-specific exome sequencing allows the detection of individual structural variants and point mutations. Circulating free DNA is isolated from peritherapeutically collected patient plasma samples and ctDNA quantified therein. Identification of breakpoints is carried out using FACTERA. Bioinformatic analysis is performed using samtools, picard, fgbio, and the MIRACUM Pipeline.

MPMRI

Combination of conventional MRI sequences with diffusion-weighted imaging, intravoxel-incoherent motion, and dynamic contrast enhancement. Multiparametric MRI is performed before, during, and after NRT. We aim to correlate mpMRI data with the resected specimen's macroscopical, histological, and immunohistochemical findings.

RESULTS

Preliminary data support the notion that quantification of ctDNA in combination with tumor mass characterization through co-registration of mpMRI and histopathology can predict NRT response of STS.

CLINICAL RELEVANCE

The methods presented in this prospective study are necessary to assess therapy response in heterogeneous tumors and lay the foundation of future patient- and tumor-specific therapy concepts. These methods can be applied to various tumor entities. Thus, the participation and support of a wider group of oncologic surgeons are needed to validate these findings on a larger patient cohort.

Imaging of pediatric extremity soft tissue tumors: A COG Diagnostic Imaging Committee/SPR Oncology Committee White Paper

Pediatric soft tissue tumors of the extremity include rhabdomyosarcoma and nonrhabdomyosarcoma neoplasms. This manuscript provides consensus-based imaging recommendations for imaging evaluation at diagnosis, during treatment, and following completion of therapy for patients with a soft tissue tumor of the extremity.

Virtual Biopsy in Soft Tissue Sarcoma. How Close Are We?

A shift in radiology to a data-driven specialty has been unlocked by synergistic developments in imaging biomarkers (IB) and computational science. This is advancing the capability to deliver "virtual biopsies" within oncology. The ability to non-invasively probe tumour biology both spatially and temporally would fulfil the potential of imaging to inform management of complex tumours; improving diagnostic accuracy, providing new insights into inter- and intra-tumoral heterogeneity and individualised treatment planning and monitoring. Soft tissue sarcomas (STS) are rare tumours of mesenchymal origin with over 150 histological subtypes and notorious heterogeneity. The combination of inter- and intra-tumoural heterogeneity and the rarity of the disease remain major barriers to effective treatments. We provide an overview of the process of successful IB development, the key imaging and computational advancements in STS including quantitative magnetic resonance imaging, radiomics and artificial intelligence, and the studies to date that have explored the potential biological surrogates to imaging metrics. We discuss the promising future directions of IBs in STS and illustrate how the routine clinical implementation of a virtual biopsy has the potential to revolutionise the management of this group of complex cancers and improve clinical outcomes.

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.

Descriptive analysis of MRI functional changes occurring during reduced dose radiotherapy for myxoid liposarcomas

OBJECTIVES

Myxoid liposarcomas (MLS) show enhanced response to radiotherapy due to their distinctive vascular pattern and therefore could be effectively treated with lower radiation doses. This is a descriptive study to explore the use of functional MRI to identify response in a uniform cohort of MLS patients treated with reduced dose radiotherapy.

METHODS

10 patients with MLS were imaged pre-, during, and post-radiotherapy receiving reduced dose radiotherapy and the response to treatment was histopathologically assessed post-radiotherapy. Apparent diffusion coefficient (ADC), T2* relaxation time, volume transfer constant (Ktrans), initial area under the gadolinium curve over 60 s (IAUGC60) and (Gd) were estimated for a central tumour volume.

RESULTS

All parameters showed large inter- and intrasubject variabilities. Pre-treatment (Gd), IAUGC60 and Ktrans were significantly different between responders and non-responders. Post-radiotherapy reductions from baseline were demonstrated for T2*, (Gd), IAUGC60 and Ktrans for responders. No statistically significant ADC differences were demonstrated between the two response groups. Significantly greater early tumour volume reductions were observed for responders.

CONCLUSIONS

MLS are heterogenous lesions, characterised by a slow gradual contrast-agent uptake. Pre-treatment vascular parameters, early changes to tumour volume, vascular parameters and T2* have potential in identifying response to treatment. The delayed (Gd) is a suitable descriptive parameter, relying simply on T1 measurements. Volume changes precede changes in MLS functionality and could be used to identify early response.

ADVANCES IN KNOWLEDGE

MLS are are characterised by slow gradual contrast-agent uptake. Measurement of the delayed contrast-agent uptake (Gd) is simple to implement and able to discriminate response.

Implementing a Machine Learning Strategy to Predict Pathologic Response in Patients With Soft Tissue Sarcomas Treated With Neoadjuvant Chemotherapy

PURPOSE

Neoadjuvant chemotherapy (NAC) has been increasingly used in patients with locally advanced high-risk soft tissue sarcomas in the past decade, but definition and prognostic impact of a good histologic response (GHR) are lacking. Our aim was to investigate which histologic feature from the post-NAC surgical specimen independently correlated with metastatic relapse-free survival (MFS) in combination with clinical, radiologic, and pathologic features using a machine learning approach.

METHODS

This retrospective study included 175 consecutive patients (median age: 59 years, 75 women) with resectable disease, treated with anthracycline-based NAC between 1989 and 2015 in our sarcoma reference center, and with quantitative histopathologic analysis of the surgical specimen. The outcome of interest was the MFS. A multimodel, multivariate survival analysis was used to define GHR. The added prognostic value of GHR was investigated through the comparisons with the standard model (including histologic grade, size, and depth) and SARCULATOR nomogram using concordance indices (c-index) and Monte-Carlo cross-validation.

RESULTS

Seventy-two patients (72 of 175, 41.1%) had a metastatic relapse. Stepwise Cox regression, random survival forests, and least absolute shrinkage and selection operator-penalized Cox regression all converged toward the same definition for GHR, ie, < 5% stainable tumor cells. The five-year MFS probability was 1 (95% CI, 1 to 1) in patients with GHR versus 0.73 (95% CI, 0.65 to 0.81) in patients without GHR (log-rank P = .0122). The final prognostic model incorporating the GHR was significantly better than the standard model and SARCULATOR (average c-index in testing sets = 0.72 [95% CI, 0.61 to 0.82] v 0.57 [95% CI, 0.44 to 0.70] and 0.54 [95% CI, 0.45 to 0.64], respectively; P = .0414 and .0091).

CONCLUSION

Histologic response to NAC improves the prediction of MFS in patients with soft tissue sarcoma and represents a possible end point in future studies exploring innovative regimens in the neoadjuvant setting.

Multisite Technical and Clinical Performance Evaluation of Quantitative Imaging Biomarkers from 3D FDG PET Segmentations of Head and Neck Cancer Images

Quantitative imaging biomarkers (QIBs) provide medical image-derived intensity, texture, shape, and size features that may help characterize cancerous tumors and predict clinical outcomes. Successful clinical translation of QIBs depends on the robustness of their measurements. Biomarkers derived from positron emission tomography images are prone to measurement errors owing to differences in image processing factors such as the tumor segmentation method used to define volumes of interest over which to calculate QIBs. We illustrate a new Bayesian statistical approach to characterize the robustness of QIBs to different processing factors. Study data consist of 22 QIBs measured on 47 head and neck tumors in 10 positron emission tomography/computed tomography scans segmented manually and with semiautomated methods used by 7 institutional members of the NCI Quantitative Imaging Network. QIB performance is estimated and compared across institutions with respect to measurement errors and power to recover statistical associations with clinical outcomes. Analysis findings summarize the performance impact of different segmentation methods used by Quantitative Imaging Network members. Robustness of some advanced biomarkers was found to be similar to conventional markers, such as maximum standardized uptake value. Such similarities support current pursuits to better characterize disease and predict outcomes by developing QIBs that use more imaging information and are robust to different processing factors. Nevertheless, to ensure reproducibility of QIB measurements and measures of association with clinical outcomes, errors owing to segmentation methods need to be reduced.

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.

Comparison of DCE-MRI of murine model cancers with a low dose and high dose of contrast agent

There are increasing concerns regarding intracellular accumulation of gadolinium (Gd) after multiple dynamic contrast enhanced (DCE) MRI scans. We investigated whether a low dose (LD) of Gd-based contrast agent is as effective as a high dose (HD) for quantitative analysis of DCE-MRI data, and evaluated the use of a split dose protocol to obtain new diagnostic parameters. Female C3H mice (n = 6) were injected with mammary carcinoma cells in the hind leg. MRI experiments were performed on 9.4 T scanner. DCE-MRI data were acquired with 1.5 s temporal resolution before and after a LD (0.04 mmol/kg), then again after 30 min followed by a HD (0.2 mmol/kg) bolus injection of Omniscan. The standard Tofts model was used to extract physiological parameters (K^trans and v_e) with the arterial input function derived from muscle reference tissue. In addition, an empirical mathematical model was used to characterize maximum contrast agent uptake (A), contrast agent uptake rate (α) and washout rate (β and γ). There were moderate to strong correlations (r = 0.69-0.97, p < 0001) for parameters K^trans, v_e, A, α and β from LD versus HD data. On average, tumor parameters obtained from LD data were significantly larger (p < 0.05) than those from HD data. The parameter ratios, K^trans, v_e, A and α calculated from the LD data divided by the HD data, were all significantly larger than 1.0 (p < 0.003) for tumor. T₂* changes following contrast agent injection affected parameters calculated from HD data, but this was not the case for LD data. The results suggest that quantitative analysis of LD data may be at least as effective for cancer characterization as quantitative analysis of HD data. In addition, the combination of parameters from two different doses may provide useful diagnostic information.

Quantitative Musculoskeletal Tumor Imaging

The role of quantitative magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) techniques continues to grow and evolve in the evaluation of musculoskeletal tumors. In this review we discuss the MRI quantitative techniques of volumetric measurement, chemical shift imaging, diffusion-weighted imaging, elastography, spectroscopy, and dynamic contrast enhancement. We also review quantitative PET techniques in the evaluation of musculoskeletal tumors, as well as virtual surgical planning and three-dimensional printing.

High-Grade Soft-Tissue Sarcomas: Can Optimizing Dynamic Contrast-Enhanced MRI Postprocessing Improve Prognostic Radiomics Models?

BACKGROUND

Heterogeneity on pretreatment dynamic contrast-enhanced (DCE)-MRI of sarcomas may be prognostic, but the best technique to capture this characteristic remains unknown.

PURPOSE

To investigate the best method to extract prognostic data from baseline DCE-MRI.

STUDY TYPE

Retrospective, single-center.

POPULATION

Fifty consecutive uniformly-treated adults with nonmetastatic high-grade sarcomas.

FIELD STRENGTH/SEQUENCE

1.5T; T₂ -weighted-imaging, fat-suppressed fast spoiled gradient echo DCE-MRI.

ASSESSMENT

Ninety-two radiomics features (RFs) were extracted at each DCE-MRI phase (11, from t = 0-88 sec). Relative changes in RFs (rRFs) since the acquisition baseline were calculated (11 × 92 rRFs). Curves of rRF as function of time postinjection were integrated (92 integrated-rRFs [irRFs]). K^trans and area under the time-intensity curve at 88-sec parametric maps were computed and 2 × 92 parametric-RFs (pRFs) were extracted. Five DCE-MRI-based radiomics models were built on: an RFs subset (32 sec, 64 sec, 88 sec); all rRFs; all irRFs; and all pRFs. Two models were elaborated as reference, on: conventional radiological features; and T₂ -WI RFs.

STATISTICAL TESTS

A common machine-learning approach was applied to radiomics models. Features with P < 0.05 at univariate analysis were entered in a LASSO-penalized Cox regression including bootstrapped 10-fold cross-validation. The resulting radiomics scores (RScores) were dichotomized per their median and entered in multivariate Cox models for predicting metastatic relapse-free survival. Models were compared with integrative area under the curve (AUC) and concordance index.

RESULTS

Only dichotomized RScores from models based on rRFs subset, all rRFS and irRFS correlated with prognostic (P = 0.0107-0.0377). The models including all rRFs and irRFs had the highest c-index (0.83), followed by the radiological model. The radiological model had the highest integrative AUC (0.87), followed by models including all rRFs and irRFs. The radiological and full rRFs models were significantly better than the T₂ -based radiomics model (P = 0.02).

DATA CONCLUSION

The initial DCE-MRI of STS contains prognostic information. It seems more relevant to make predictions on rRFs instead of pRFs. Evidence Level: 3 Technical Efficacy: 3 J. Magn. Reson. Imaging 2020;52:282-297.

Soft Tissue Sarcoma Stiffness and Perfusion Evaluation by MRE and DCE-MRI for Radiation Therapy Response Assessment: A Technical Feasibility Study

Soft tissue sarcomas are a rare and heterogeneous group of malignancies that present significant diagnostic and therapeutic challenges. Patient stratification based on tumor aggressiveness and early therapeutic response based on quantitative imaging may improve prediction of treatment response and the evaluation of new treatment strategies in clinical trials. The purpose of this pilot study was to determine the technical feasibility of magnetic resonance elastography (MRE) and dynamic contrast-enhanced (DCE) MRI for the evaluation of sarcoma stiffness and perfusion in 9 patients with histologically confirmed sarcoma. Additionally, we assessed the feasibility of utilizing MRE and DCE-MRI for the early evaluation of response to radiation therapy in 4 patients to determine the utility of further evaluation in a larger cohort study. Tumor size, stiffness, and perfusion parameters all decreased from baseline at the time of the pre-surgery or follow-up MRI, and results were compared to pathology or conventional imaging. MRE and DCE-MRI may be useful for the quantitative evaluation of tumor stiffness and perfusion, and therapy response assessment in soft tissue sarcomas.

MR Imaging of Pediatric Musculoskeletal Tumors:: Recent Advances and Clinical Applications

Pediatric musculoskeletal tumors comprise approximately 10% of childhood neoplasms, and MR imaging has been used as the imaging evaluation standard for these tumors. The role of MR imaging in these cases includes identification of tumor origin, tissue characterization, and definition of tumor extent and relationship to adjacent structures as well as therapeutic response in posttreatment surveillance. Technical advances have enabled quantitative evaluation of biochemical changes in tumors. This article reviews recent updates to MR imaging of pediatric musculoskeletal tumors, focusing on advanced MR imaging techniques and providing information on the relevant physics of these techniques, clinical applications, and pitfalls.

Dynamic contrast-enhanced MRI for advanced esophageal cancer response assessment after concurrent chemoradiotherapy

PURPOSE

We aimed to evaluate the treatment response of patients with esophageal cancer after concurrent chemoradiation therapy (CRT) using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

METHODS

This retrospective study included 59 patients with histologically confirmed esophageal squamous cell carcinoma. The patients underwent DCE-MRI before and 4 weeks after CRT. Patients with complete response were defined as the CR group; partial response, stable disease, and progressive disease patients were defined as the non-CR group. DCE-MRI parameters (Ktrans, Ve, and Kep) were measured and compared between pre- and post-CRT in the CR and non-CR groups, respectively. Pre-CRT and post-CRT parameters were used to calculate the absolute change and the ratio of change. DCE-MRI parameters were compared between the CR and non-CR groups. Receiver operating characteristic (ROC) curves were used to verify diagnostic performance.

RESULTS

Patients with higher T-stage esophageal cancer might present with poorer response. After CRT, the Ktrans and Kep values significantly decreased in the CR group, whereas only Kep value decreased in the non-CR group. The post-Ktrans and post-Kep values were observed to be significantly lower in the CR group than in the non-CR group. The absolute change and ratio of change of both Ktrans and Kep were higher in the CR group than in the non-CR group. Based on ROC analysis, the ratio of change in Ktrans was the best parameter to assess treatment response (AUC= 0.840).

CONCLUSION

DCE-MRI parameters are valuable in predicting and assessing concurrent CRT response for advanced esophageal cancer.

Clinicopathological analysis of epithelioid inflammatory myofibroblastic sarcoma

Inflammatory myofibroblastic tumor (IMT) is a distinctive neoplasm composed of myofibroblastic and fibroblastic spindle cells, accompanied by the inflammatory infiltration of plasma cells, lymphocytes and/or eosinophils. Epithelioid inflammatory myofibroblastic sarcoma (EIMS), which primarily consists of cells with a round or epithelioid morphology, is associated with a poor prognosis and rapid development of local recurrence, and has been recognized to be a variant of IMT. Diagnosis of EIMS is difficult owing to its close resemblance to malignant mesothelioma, anaplastic large cell lymphoma, gastrointestinal stromal tumor and other malignant diseases. In the present study, a case of this rare tumor was evaluated in a 26-year-old male who was admitted to hospital after experiencing abdominal pain for ~18 days and abdominal distention for 1 week. The patient's tumor was examined by imaging, gross examination, histology, immunohistochemistry and fluorescence in situ hybridization (FISH). The magnetic resonance imaging enhanced-scanning image revealed that the morphology of the tumor was irregular, and signal was medley consisting of high and low hybrid reinforcement. Tumors were located in the bladder and rectal pit, in the lower part of the lower abdomen, indicating the presence of malignancy and involvement of the small intestine and rectum. Enhanced-scanning imaging revealed notable inhomogeneous enhancement. Gross examination revealed that the tumor was solid and had a variegated appearance with alternating fleshy and mucoid areas in the cut surface. Microscopically, the tumors were dominated by sheets of epithelioid-to-round cells with a prominent inflammatory infiltrate. The majority of the stroma was myxoid. Immunohistochemically, the tumor cells exhibited diffuse strong staining for ALK receptor tyrosine kinase (hereafter ALK), vimentin, tumor protein P53, desmin, Wilms' tumor 1 and programmed death-ligand 1. FISH analysis also revealed the existence of ALK rearrangement. The expression of PD-L1 in EIMS indicates that the immune checkpoint blockade could represent a novel therapy for the treatment of EIMS.

Role of Imaging in Response Assessment and Individualised Treatment for Sarcomas

The first systematic response evaluation criteria were established by WHO, based on the tumor size changes shortly after the computed tomography (CT) technique became available to the daily practice. RECIST, a simplified version of WHO criteria, and its newer version, RECIST1.1 are the currently available international response evaluation criteria in solid tumors and remains based on tumor size changes. While the introduction of molecularly targeted drugs has significantly improved the survival in patient with sarcomas, the evaluation of tumor response has become more complicated. Increasing number of studies have reported the lack of shrinkage in responding tumors and raised concerns of significant underestimation of responses using RECIST. The first such observation was made on gastrointestinal stromal tumor (GIST) treated with imatinib. In GISTs responding to imatinib, the degree of contrast enhancement on CT typically decreases significantly compared with the baseline, and, regardless of whether tumors shrink, heterogeneous hyperattenuating tumors become homogeneous hypoattenuating tumors with a smaller enhancing solid component. In current oncology practice, CT is a widely accepted method of evaluating tumor response. CT images are relatively simple to acquire and can be reasonably reproduced with no significant technical obstacles. FDG-PET is highly sensitive and specific in identifying responding sarcomas. It has mostly been used as a problem solver and for those with marginally resectable GIST. More recently, the utility of whole body MRI is undergoing exploration. This article discusses the traditional size-based response evaluation criteria, and introduces new evidence based response evaluation based on changes in morphology in addition to changes in tumor size on CT images, and whole body imaging is introduced at the end.