Multiparametric Assessment of Treatment Response in High-Grade Soft-Tissue Sarcomas with Anatomic and Functional MR Imaging Sequences

The landscape of drug sensitivity and resistance in sarcoma

Sarcomas are rare malignancies with over 100 distinct histological subtypes. Their rarity and heterogeneity pose significant challenges to identifying effective therapies, and approved regimens show varied responses. Novel, personalized approaches to therapy are needed to improve patient outcomes. Patient-derived tumor organoids (PDTOs) model tumor behavior across an array of malignancies. We leverage PDTOs to characterize the landscape of drug resistance and sensitivity in sarcoma, collecting 194 specimens from 126 patients spanning 24 distinct sarcoma subtypes. Our high-throughput organoid screening pipeline tested single agents and combinations, with results available within a week from surgery. Drug sensitivity correlated with clinical features such as tumor subtype, treatment history, and disease trajectory. PDTO screening can facilitate optimal drug selection and mirror patient outcomes in sarcoma. We could identify at least one FDA-approved or NCCN-recommended effective regimen for 59% of the specimens, demonstrating the potential of our pipeline to provide actionable treatment information.

Perfusion-weighted imaging with dynamic contrast enhancement (PWI/DCE) morphologic, qualitative, semiquantitative, and radiomics features predicting undifferentiated pleomorphic sarcoma (UPS) treatment response

Undifferentiated pleomorphic sarcoma (UPS) is the largest subgroup of soft tissue sarcomas. This study determined the value of perfusion-weighted imaging with dynamic-contrast-enhancement (PWI/DCE) morphologic, qualitative, and semiquantitative features for predicting UPS pathology-assessed treatment effect (PATE). This retrospective study included 33 surgically excised extremity UPS patients with pre-surgical MRI. Volumetric tumor segmentation from PWI/DCE was obtained at Baseline (BL), Post-Chemotherapy (PC), and Post-Radiation Therapy (PRT). The surgical specimens' PATE separated cases into Responders (R) (≥ 90%, 16 patients), Partial-Responders (PR) (89 - 31%, 10 patients), and Non-Responders (NR) (≤ 30%, seven patients). Seven semiquantitative kinetic parameters and maps were extracted from time-intensity curves (TICs), and 107 radiomic features were derived. Statistical analyses compared R vs. PR/NR. At PRT, 79% of R displayed a "Capsular" morphology (P = 1.49 × 10-7), and 100% demonstrated a TIC-type II (P = 8.32 × 10-7). 80% of PR showed "Unipolar" morphology (P = 1.03 × 10-5), and 60% expressed a TIC-type V (P = 0.06). Semiquantitative wash-in rate (WiR) was able to separate R vs. PR/NR (P = 0.0078). The WiR radiomics displayed significant differences in the first_order_10 percentile (P = 0.0178) comparing R vs. PR/NR at PRT. The PWI/DCE TIC-type II curve, low WiR, and "Capsular" enhancement represent PRT patterns typically observed in successfully treated UPS and demonstrate potential for UPS treatment response assessment.

The role of imaging in extremity sarcoma surgery

The surgical management of extremity bone and soft tissue sarcomas has evolved significantly over the last 50 years. The introduction and refinement of high-resolution cross-sectional imaging has allowed accurate assessment of anatomy and tumor extent, and in the current era more than 90% of patients can successfully undergo limb-salvage surgery. Advances in imaging have also revolutionized the clinician's ability to assess treatment response, detect metastatic disease, and perform intraoperative surgical navigation. This review summarizes the broad and essential role radiology plays in caring for sarcoma patients from diagnosis to post-treatment surveillance. Present evidence-based imaging paradigms are highlighted along with key future directions.

Qualitative and quantitative MRI analysis of alveolar soft part sarcoma: correlation with histological grade and Ki-67 expression

OBJECTIVE

To investigate the correlation between MRI findings and histological features for preoperative prediction of histological grading and Ki-67 expression level in alveolar soft part sarcoma (ASPS).

METHODS

A retrospective analysis was conducted on 63 ASPS patients (Jan 2017-May 2023). All patients underwent 3.0-T MRI examinations, including conventional sequences, dynamic contrast-enhanced scans with time-intensity curve analysis, and diffusion-weighted imaging with apparent diffusion coefficient (ADC) measurements. Patients were divided into low-grade (histological Grade I) and high-grade (histological Grade II/III) groups based on pathology. Immunohistochemistry was used to assess Ki-67 expression levels in ASPS. Statistical analysis included chi-square tests, Wilcoxon rank-sum test, binary logistic regression analysis, Spearman correlation analysis, and receiver operating characteristic curve analysis of various observational data.

RESULTS

There were 29 low-grade and 34 high-grade patients (26 males and 37 females) and a wide age range (5-68 years). Distant metastasis, tumor enhancement characteristics, and ADC values were independent predictors of high-grade ASPS. High-grade ASPS had lower ADC values (p = 0.002), with an area under the curve (AUC), sensitivity, and specificity of 0.723, 79.4%, and 58.6%, respectively, for high-grade prediction. There was a negative correlation between ADC values and Ki-67 expression (r = -0.526; p < 0.001). When the cut-off value of ADC was 0.997 × 10-3 mm²/s, the AUC, sensitivity, and specificity for predicting high Ki-67 expression were 0.805, 65.6%, and 83.9%, respectively.

CONCLUSION

Qualitative and quantitative MRI parameters are valuable for predicting histological grading and Ki-67 expression levels in ASPS.

CRITICAL RELEVANCE STATEMENT

This study will help provide a more nuanced understanding of ASPS and guide personalized treatment strategies.

KEY POINTS

There is limited research on assessing ASPS prognosis through MRI. Metastasis, enhancement, and ADC correlated with histological grade; ADC related to Ki-67 expression. MRI provides clinicians with valuable information on ASPS grading and proliferation activity.

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.

Evaluation of the Prognostic Value of Pretherapeutic Magnetic Resonance Imaging in Predicting Soft Tissue Sarcoma Radiation Response: A Retrospective Study from a Large Institutional Sarcoma Imaging Database

Background: RT-induced hyalinization/fibrosis was recently evidenced as a significant independent predictor for complete response to neoadjuvant radiotherapy (RT) and survival in patients with soft tissue sarcoma (STS). Purpose: Non-invasive predictive markers of histologic response after neoadjuvant RT of STS are expected. Materials and Methods: From May 2010 to April 2017, patients with a diagnosis of STS who underwent neoadjuvant RT for limb STS were retrieved from a single center prospective clinical imaging database. Tumor Apparent Diffusion Coefficients (ADC) and areas under the time-intensity perfusion curve (AUC) were compared with the histologic necrosis ratio, fibrosis, and cellularity in post-surgical specimens. Results: We retrieved 29 patients. The median ADC value was 134.3 × 10-3 mm2/s. ADC values positively correlated with the post-treatment tumor necrosis ratio (p = 0.013). Median ADC values were lower in patients with less than 50% necrosis and higher in those with more than 50% (120.3 × 10-3 mm2/s and 202.0 × 10-3 mm2/s, respectively (p = 0.020). ADC values higher than 161 × 10-3 mm2/s presented a 95% sensitivity and a 55% specificity for the identification of tumors with more than 50% tumor necrosis ratio. Tumor-to-muscle AUC ratios were associated with histologic fibrosis (p = 0.036). Conclusions: ADC and perfusion AUC correlated, respectively, with radiation-induced tumor necrosis and fibrosis.

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.

Perfusion Imaging of the Musculoskeletal System

Perfusion imaging is the aspect of functional imaging, which is most applicable to the musculoskeletal system. In this review, the anatomy and physiology of bone perfusion is briefly outlined as are the methods of acquiring perfusion data on MR imaging. The current clinical indications of perfusion related to the assessment of soft tissue and bone tumors, synovitis, osteoarthritis, avascular necrosis, Keinbock's disease, diabetic foot, osteochondritis dissecans, and Paget's disease of bone are reviewed. Challenges and opportunities related to perfusion imaging of the musculoskeletal system are also briefly addressed.

Society of skeletal radiology position paper - recommendations for contrast use in musculoskeletal MRI: when is non-contrast imaging enough?

The following White Paper will discuss the appropriateness of gadolinium administration in MRI for musculoskeletal indications. Musculoskeletal radiologists should consider the potential risks involved and practice the judicious use of intravenous contrast, restricting administration to cases where there is demonstrable added value. Specific nuances of when contrast is or is not recommended are discussed in detail and listed in table format. Briefly, contrast is recommended for bone and soft tissue lesions. For infection, contrast is reserved for chronic or complex cases. In rheumatology, contrast is recommended for early detection but not for advanced arthritis. Contrast is not recommended for sports injuries, routine MRI neurography, implants/hardware, or spine imaging, but is helpful in complex and post-operative cases.

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.

Quantitative diffusion-weighted MRI response assessment in rhabdomyosarcoma: an international retrospective study on behalf of the European paediatric Soft tissue sarcoma Study Group Imaging Committee

OBJECTIVE

To investigate the feasibility of diffusion-weighted magnetic resonance imaging (DW-MRI) as a predictive imaging marker after neoadjuvant chemotherapy in patients with rhabdomyosarcoma.

MATERIAL AND METHODS

We performed a multicenter retrospective study including pediatric, adolescent and young adult patients with rhabdomyosarcoma, Intergroup Rhabdomyosarcoma Study group III/IV, treated according to the European paediatric Soft tissue sarcoma Study Group (EpSSG) RMS2005 or MTS2008 studies. DW-MRI was performed according to institutional protocols. We performed two-dimensional single-slice tumor delineation. Areas of necrosis or hemorrhage were delineated to be excluded in the primary analysis. Mean, median and 5th and 95th apparent diffusion coefficient (ADC) were extracted.

RESULTS

Of 134 included patients, 82 had measurable tumor at diagnosis and response and DW-MRI scans of adequate quality and were included in the analysis. Technical heterogeneity in scan acquisition protocols and scanners was observed. Mean ADC at diagnosis was 1.1 (95% confidence interval [CI]: 1.1-1.2) (all ADC expressed in * 10-3 mm2/s), versus 1.6 (1.5-1.6) at response assessment. The 5th percentile ADC was 0.8 (0.7-0.9) at diagnosis and 1.1 (1.0-1.2) at response. Absolute change in mean ADC after neoadjuvant chemotherapy was 0.4 (0.3-0.5). Exploratory analyses for association between ADC and clinical parameters showed a significant difference in mean ADC at diagnosis for alveolar versus embryonal histology. Landmark analysis at nine weeks after the date of diagnosis showed no significant association (hazard ratio 1.3 [0.6-3.2]) between the mean ADC change and event-free survival.

CONCLUSION

A significant change in the 5th percentile and the mean ADC after chemotherapy was observed. Strong heterogeneity was identified in DW-MRI acquisition protocols between centers and in individual patients.

The Prognostic Relevance of MRI Characteristics in Myxofibrosarcoma Patients Treated with Neoadjuvant Radiotherapy

To improve local control, neoadjuvant radiotherapy (nRT) followed by surgery is the standard of care in myxofibrosarcoma (MFS) because of its infiltrative growth pattern. Nevertheless, local recurrence rates are high. Data on prognostic factors for poor clinical outcomes are lacking. This retrospective study thus investigates the prognostic relevance of magnetic resonance imaging (MRI) characteristics before and after nRT in 40 MFS patients, as well as their association with disease-free survival (DFS) and overall survival (OS). A vascular pedicle, defined as extra-tumoral vessels at the tumor periphery, was observed in 12 patients (30.0%) pre-nRT and remained present post-nRT in all cases. Patients with a vascular pedicle had worse DFS (HR 5.85; 95% CI 1.56-21.90; p = 0.009) and OS (HR 9.58; 95% CI 1.91-48.00; p = 0.006). An infiltrative growth pattern, referred to as a tail sign, was observed in 22 patients (55.0%) pre-nRT and in 19 patients (47.5%) post-nRT, and was associated with worse DFS post-nRT (HR 6.99; 95% CI 1.39-35.35; p = 0.019). The percentage of tumor necrosis estimated by MRI was increased post-nRT, but was not associated with survival outcomes. The presence of a tail sign or vascular pedicle on MRI could support the identification of patients at risk for poor clinical outcomes after nRT.

Sarcoma Imaging Surveillance

Soft tissue sarcomas (STS) are a heterogeneous group of solid tumors. There are many histologic subtypes. The prognosis after treatment may be estimated by the analysis of the type of tumor, grade, depth, size at diagnosis, and age of the patient. These type of sarcomas most commonly metastasize to the lungs and may have a relatively high rate of local recurrence, depending on the histologic type and surgical margins. Patients with recurrence have a poorer prognosis. The surveillance of patients with STS is therefore extremely important. This review analyzes the role of MR imaging and US in detecting local recurrence.

Whole Body MRI with DWI in People with NF1 and Schwannomatosis: Are Qualitative and Quantitative Imaging Features of Peripheral Lesions Comparable to Localized MRI?

PURPOSE

To compare the qualitative and quantitative features of peripheral lesions on localized (L) and whole-body (WB) magnetic resonance imaging (MRI) in people with neurofibromatosis type 1 (NF1) and schwannomatosis.

MATERIALS AND METHODS

This is a retrospective, HIPAA compliant study with twenty-seven patients (14 women, 13 men; mean age (years): 38 (3-67)) who underwent both L-MRI and WB-MRI without interval treatment. WB-MRI and L-MRI were comprised of T1-weighted, fat suppressed (FS) T2-weighted or short tau inversion recovery (STIR), diffusion-weighted imaging (DWI) using b-values of 50, 400, and 800 s/mm2, apparent diffusion coefficient (ADC) mapping and pre- and post-contrast FST1 sequences. Two readers recorded qualitative (T1 and T2/STIR signal intensity and heterogeneity, contrast enhancement and heterogeneity, perilesional enhancement, presence of a target sign and perilesional edema) and quantitative (size, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), ADC) features of peripheral lesions on L-MRI and WB-MRI.Descriptive statistics, Wilcoxon signed-rank test and McNemar's test were used.

RESULTS

There were 31 peripheral lesions identified in 27 subjects, (mean size: 3.1 cm (range: 1-8.1 cm) on both L-MRI and WB-MRI).There were no differences in T1 signal and heterogeneity and T2/STIR signal and heterogeneity between WB-MRI and L-MRI ((p = 0.180, 0.083, 0.317 and 0.157 respectively). There were also no differences in contrast enhancement, heterogeneity and perilesional enhancement between WB-MRI and L-MRI (p = 1.000, 0.380 and 1.000 respectively). Presence of a target sign and perilesional edema did not differ between WB-MRI and L-MRI (p = 1.000 and 0.500 respectively). Craniocaudal (CC), mediolateral (ML) and anteroposterior (AP) size measurements on WB-MRI did not differ from CC, ML and AP size measurements on L-MRI (p = 0.597, 0.128 and 0.783 respectively). SNR on WB-DWI did not differ from SNR on L-DWI for b50, b400 and b800 images (p = 0.285, 0.166, and 0.974 respectively), and CNR on WB-DWI did not differ from CNR on L-DWI for b50, b400 and b800 images (p = 0.600, 0.124, and 0.787 respectively). There was no significant difference in minimum, mean and maximum ADC values between WB-DWI and L-DWI (p = 0.234, 0.481, and 0.441 respectively). Median minimum, mean and maximum ADC (×10(-3)mm(2)/s) differences between WB-DWI and L-DWI were 0.0 (range -1 to 0.7), 0.0 (range -0.5 to 0.6), and 0.1 (range -1.2 to 0.8) respectively. Relative ADC difference averages were 29.1% for minimum values, 10.1% for mean values, and 14.8% for maximum values.

CONCLUSION

WB-MRI yields qualitative and quantitative features for peripheral lesions, including DWI and ADC measurements, that are comparable to L-MRI scans. WB-DWI can be reliably used for the assessment of peripheral nerve sheath tumors, obviating the need for a repeat follow-up L-DWI acquisition.

Musculoskeletal Soft-tissue Masses

Evaluation of soft-tissue masses has become a common clinical practice indication for imaging with both ultrasound and MR imaging. We illustrate the ultrasonography and MR imaging appearances of soft-tissue masses based on the various categories, updates, and reclassifications of the 2020 World Health Organization classification.

Methodological considerations on segmenting rhabdomyosarcoma with diffusion-weighted imaging-What can we do better?

PURPOSE

Diffusion-weighted MRI is a promising technique to monitor response to treatment in pediatric rhabdomyosarcoma. However, its validation in clinical practice remains challenging. This study aims to investigate how the tumor segmentation strategy can affect the apparent diffusion coefficient (ADC) measured in pediatric rhabdomyosarcoma.

MATERIALS AND METHODS

A literature review was performed in PubMed using search terms relating to MRI and sarcomas to identify commonly applied segmentation strategies. Seventy-six articles were included, and their presented segmentation methods were evaluated. Commonly reported segmentation strategies were then evaluated on diffusion-weighted imaging of five pediatric rhabdomyosarcoma patients to assess their impact on ADC.

RESULTS

We found that studies applied different segmentation strategies to define the shape of the region of interest (ROI)(outline 60%, circular ROI 27%), to define the segmentation volume (2D 44%, multislice 9%, 3D 21%), and to define the segmentation area (excludes edge 7%, excludes other region 19%, specific area 27%, whole tumor 48%). In addition, details of the segmentation strategy are often unreported. When implementing and comparing these strategies on in-house data, we found that excluding necrotic, cystic, and hemorrhagic areas from segmentations resulted in on average 5.6% lower mean ADC. Additionally, the slice location used in 2D segmentation methods could affect ADC by as much as 66%.

CONCLUSION

Diffusion-weighted MRI studies in pediatric sarcoma currently employ a variety of segmentation methods. Our study shows that different segmentation strategies can result in vastly different ADC measurements, highlighting the importance to further investigate and standardize segmentation.

Characteristic of Apparent Diffusion Coefficient and Time Intensity Curve Analysis of Dynamic Contrast Enhanced MRI in Osteosarcoma Histopathologic Subtypes

Background: According to WHO criteria, osteosarcoma (OS) consists of various histopathological subtypes. Thus, contrast-enhanced MRI is a very useful modality in the diagnosis and evaluation of osteosarcoma. Magnetic resonance imaging with dynamic contrast enhancement (DCE-MRI) studies was used to determine the apparent diffusion coefficient (ADC) value and the slope of the time-intensity curve (TIC). This study aimed to determine the correlation between ADC and TIC analysis using %Slope and maximum enhancement (ME) of histopathological osteosarcoma subtypes. Methods: This was a retrospective study with observational analysis on OS patients. The obtained data were 43 samples. Moreover, the interpretation was conducted by placing three regions of interest (ROI) in determining ADC value. It was observed by two radiologist observers with more than 10 years of experience. In this case, as many as six obtained ROIs were averaged. The inter-observer agreement was evaluated by Kappa test. TIC curve was analyzed and slope value was obtained afterward. Through SPSS 21 software, the data was analyzed. Results: The mean of ADC values of OS was (1.031x10^-3±0.31mm²/s), where the highest value was found in chondroblastic subtype (1.470 x10^-3±0.31mm²/s). However, the mean of TIC %slope of OS was (45.3%/s), where the highest result was found in the osteoblastic subtype (70.8%/s) followed by small cell subtype (60.8%/s) and the mean of ME of OS was 100.55% with the highest values was in osteoblastic subtype 172.72% followed by chondroblastic subtype (144.92%). This study found a significant correlation between the mean of ADC value and the OS histopathologic results as well as the correlation between the mean of ADC value and ME. Conclusion: The various types of osteosarcoma have a characteristic of radiological appearances which may similar to some bone tumor entities. The analysis of ADC values and TIC curves using % slope and ME of osteosarcoma subtypes can improve the accuracy of diagnosis as well as the monitoring of the treatment response and the disease progression.

PET-CT in the Evaluation of Neoadjuvant/Adjuvant Treatment Response of Soft-tissue Sarcomas: A Comprehensive Review of the Literature

➢

In soft-tissue sarcomas (STSs), the use of positron emission tomography-computed tomography (PET-CT) through a standardized uptake value reduction rate correlates well with histopathological response to neoadjuvant treatment and survival.

➢

PET-CT has shown a better sensitivity to diagnose systemic involvement compared with magnetic resonance imaging and CT; therefore, it has an important role in detecting recurrent systemic disease. However, delaying the use of PET-CT scan, to differentiate tumor recurrence from benign fluorodeoxyglucose uptake changes after surgical treatment and radiotherapy, is essential.

➢

PET-CT limitations such as difficult differentiation between benign inflammatory and malignant processes, inefficient discrimination between benign soft-tissue tumors and STSs, and low sensitivity when evaluating small pulmonary metastases must be of special consideration.

Tumor cellularity beyond the visible in soft tissue sarcomas: Results of an ADC-based, single center, and preliminary radiomics study

Purpose

Soft tissue sarcomas represent approximately 1% of all malignancies, and diagnostic radiology plays a significant role in the overall management of this rare group of tumors. Recently, quantitative imaging and, in particular, radiomics demonstrated to provide significant novel information, for instance, in terms of prognosis and grading. The aim of this study was to evaluate the prognostic role of radiomic variables extracted from apparent diffusion coefficient (ADC) maps collected at diagnosis in patients with soft tissue sarcomas in terms of overall survival and metastatic spread as well as to assess the relationship between radiomics and the tumor grade.

Methods

Patients with histologically proven soft tissue sarcomas treated in our tertiary center from 2016 to 2019 who underwent an Magnetic Resonance (MR) scan at diagnosis including diffusion-weighted imaging were included in this retrospective institution review board–approved study. Each primary lesion was segmented using the b50 images; the volumetric region of interest was then applied on the ADC map. A total of 33 radiomic features were extracted, and highly correlating features were selected by factor analysis. In the case of feature/s showing statistically significant results, the diagnostic accuracy was computed. The Spearman correlation coefficient was used to evaluate the relationship between the tumor grade and radiomic features selected by factor analysis. All analyses were performed applying p&lt;0.05 as a significant level.

Results

A total of 36 patients matched the inclusion criteria (15 women; mean age 58.9 ± 15 years old). The most frequent histotype was myxofibrosarcoma (16.6%), and most of the patients were affected by high-grade lesions (77.7%). Seven patients had pulmonary metastases, and, altogether, eight were deceased. Only the feature Imc1 turned out to be a predictor of metastatic spread (p=0.045 after Bonferroni correction) with 76.7% accuracy. The value -0.16 showed 73.3% sensitivity and 71.4% specificity, and patients with metastases showed lower values (mean Imc1 of metastatic patients -0.31). None of the examined variables was a predictor of the overall outcome (p&gt;0.05, each). A moderate statistically significant correlation emerged only between Imc1 and the tumor grade (r=0.457, p=0.005).

Conclusions

In conclusion, the radiomic feature Imc1 acts as a predictor of metastatic spread in patients with soft tissue sarcomas and correlates with the tumor grade.

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.

What morphological MRI features enable differentiation of low-grade from high-grade soft tissue sarcoma?

Objective:

To assess the diagnostic performance of morphological MRI features separately and in combination for distinguishing low- from high-grade soft tissue sarcoma (STS).

Methods and materials:

We retrospectively analysed pre-treatment MRI examinations with T1, T2 with and without fat suppression (FS) and contrast-enhanced T1 obtained in 64 patients with STS categorized histologically as low (n = 21) versus high grade (n = 43). Two musculoskeletal radiologists blinded to histology evaluated MRI features. Diagnostic performance was calculated for each reader and for MRI features showing significant association with histology (p < 0.05). Logistic regression analysis was performed to develop a diagnostic model to identify high-grade STS.

Results:

Among all evaluated MRI features, only six features had adequate interobserver reproducibility (kappa>0.5). Multivariate logistic regression analysis revealed a significant association with tumour grade for lesion heterogeneity on FS images, intratumoural enhancement≥51% of tumour volume and peritumoural enhancement for both readers (p < 0.05). For both readers, the presence of each of the three features yielded odds ratios for high grade versus low grade from 4.4 to 9.1 (p < 0.05). The sum of the positive features for each reader independent of reader expertise yielded areas under the curve (AUCs) > 0.8. The presence of ≥2 positive features indicated a high risk for high-grade sarcoma, whereas ≤1 positive feature indicated a low-to-moderate risk

Conclusion:

A diagnostic MRI score based on tumour heterogeneity, intratumoural and peritumoural enhancement enables identification of lesions that are likely to be high-grade as opposed to low-grade STS.

Advances in knowledge:

Tumour heterogeneity in Fat Suppression sequence, intratumoural and peritumoural enhancement is identified as signs of high-grade sarcoma.

Update on MR Imaging of Soft Tissue Tumors of Head and Neck

This article reviews soft tissue tumors of the head and neck following the 2020 revision of WHO Classification of Soft Tissue and Bone Tumours. Common soft tissue tumors in the head and neck and tumors are discussed, along with newly added entities to the classification system. Salient clinical and imaging features that may allow for improved diagnostic accuracy or to narrow the imaging differential diagnosis are covered. Advanced imaging techniques are discussed, with a focus on diffusion-weighted and dynamic contrast imaging and their potential to help characterize soft tissue tumors and aid in distinguishing malignant from benign tumors.

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.

Standard diffusion-weighted, intravoxel incoherent motion, and dynamic contrast-enhanced MRI of musculoskeletal tumours: correlations with Ki67 proliferation status

AIM

To determine whether quantitative parameters derived from conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) correlate with the Ki67 proliferation status in musculoskeletal tumours.

MATERIALS AND METHODS

Twenty-eight patients with musculoskeletal tumours diagnosed via surgical specimen histological analysis who underwent standard DWI, IVIM, and DCE were reviewed retrospectively. The mean standard DWI (apparent diffusion coefficient [ADC]), IVIM (pure diffusion coefficient [D], pseudo-diffusion coefficient [D∗] and perfusion fraction [ƒ]), and DCE (volume transfer constant [K^trans], rate constant [K_ep], and extravascular extracellular volume fraction [V_e]) parameters were measured and correlated with the Ki67 index. The Ki67 value was categorised as high (>20%) or low (≤20%).

RESULTS

The ADC and D values correlated negatively with the Ki67 index (r=-0.711∼-0.699, p<0.001), whereas the K^trans and K_ep values correlated positively with the Ki67 index (r=0.389-0.434, p=0.021, 0.041). The ADC and D values were lower (p<0.001), whereas the K^trans and K_ep values were higher (p=0.011, 0.005) in musculoskeletal tumours with a high Ki67 status than in those in a low status. The ADC and D demonstrated the largest area under the receiver-operating characteristic curve (AUC = 0.953), which is statistically bigger than the AUC of K^trans and K_ep (0.784 and 0.802, respectively).

CONCLUSION

ADC, D, K^trans, and K_ep correlate with the Ki67 index. ADC and D are the strongest quantitative parameters for predicting Ki67 status.

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.

Prediction of soft tissue sarcoma response to radiotherapy using longitudinal diffusion MRI and a deep neural network with generative adversarial network-based data augmentation

PURPOSE

The goal of this study was to predict soft tissue sarcoma response to radiotherapy (RT) using longitudinal diffusion-weighted MRI (DWI). A novel deep-learning prediction framework along with generative adversarial network (GAN)-based data augmentation was investigated for the response prediction.

METHODS

Thirty soft tissue sarcoma patients who were treated with five-fraction hypofractionated radiation therapy (RT, 6Gy×5) underwent diffusion-weighted MRI three times throughout the RT course using an MR-guided radiotherapy system. Pathologic treatment effect (TE) scores, ranging from 0-100%, were obtained from the post-RT surgical specimen as a surrogate of patient treatment response. Patients were divided into three classes based on the TE score (TE ≤ 20%, 20% < TE < 90%, TE ≥ 90%). Apparent diffusion coefficient (ADC) maps of the tumor from the three time points were combined as 3-channel images. An auxiliary classifier generative adversarial network (ACGAN) was trained on 20 patients to augment the data size. A total of 15,000 synthetic images were generated for each class. A prediction model based on a previously described VGG-19 network was trained using the synthesized data, validated on five unseen validation patients, and tested on the remaining five test patients. The entire process was repeated seven times, each time shuffling the training, validation, and testing datasets such that each patient was tested at least once during the independent test stage. Prediction performance for slice-based prediction and patient-based prediction was evaluated.

RESULTS

The average training and validation accuracies were 86.5% ± 1.6% and 84.8% ± 1.8%, respectively, indicating that the generated samples were good representations of the original patient data. Among the seven rounds of testing, slice by slice prediction accuracy ranged from 81.6% to 86.8%. The overall accuracy of the independent test sets was 83.3%. For patient-based prediction, 80% was achieved in one round and 100% was achieved in the remaining six rounds. The mean accuracy was 97.1%.

CONCLUSION

This study demonstrated the potential to use deep learning to predict the pathologic treatment effect from longitudinal DWI. Accuracies of 83.3% and 97.1% were achieved on independent test sets for slice-based and patient-based prediction respectively.

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.

Feasibility of a multiparametric MRI protocol for imaging biomarkers associated with neoadjuvant radiotherapy for soft tissue sarcoma

Objective

Soft tissue sarcoma (STS) is a rare malignancy with a 5 year overall survival rate of 55%. Neoadjuvant radiotherapy is commonly used in preparation for surgery, but methods to assess early response are lacking despite pathological response at surgery being predictive of overall survival, local recurrence and distant metastasis. Multiparametric MR imaging (mpMRI) is used to assess response in a variety of tumours but lacks a robust, standardised method. The overall aim of this study was to develop a feasible imaging protocol to identify imaging biomarkers for further investigation.

Methods

15 patients with biopsy-confirmed STS suitable for pre-operative radiotherapy and radical surgery were imaged throughout treatment. The mpMRI protocol included anatomical, diffusion-weighted and dynamic contrast-enhanced imaging, giving estimates of apparent diffusion coefficient (ADC) and the area under the enhancement curve at 60 s (iAUC₆₀). Histological analysis of resected tumours included detection of CD31, Ki67, hypoxia inducible factor and calculation of a hypoxia score.

Results

There was a significant reduction in T1 at visit 2 and in ADC at visit 3. Significant associations were found between hypoxia and pre-treatment iAUC₆₀, pre-treatment ADC and mid-treatment iAUC₆₀. There was also statistically significant association between mid-treatment ADC and Ki67.

Conclusion

This work showed that mpMRI throughout treatment is feasible in patients with STS having neoadjuvant radiotherapy. The relationships between imaging parameters, tissue biomarkers and clinical outcomes warrant further investigation.

Advances in knowledge

mpMRI-based biomarkers have good correlation with STS tumour biology and are potentially of use for evaluation of radiotherapy response.

Multiparametric MRI with diffusion-weighted imaging in predicting response to chemotherapy in cases of osteosarcoma and Ewing's sarcoma

OBJECTIVE

To evaluate the multiparametric MRI in predicting chemotherapy response in pathologically proven cases of osteosarcoma and Ewing's sarcoma. Correlation between the tumor size changes and internal breakdown using RECIST 1.1, modified RECIST, quantitative apparent diffusion coefficient (ADC) and tumor volume as well as dynamic contrast-enhanced MRI (DCE-MRI).

METHODS

The study included 104 patients pathologically proved osteosarcoma (53) and Ewing`s sarcoma (51) underwent MRI examinations; before and after chemotherapy. All patients were assessed using the RECIST 1.1 criteria, m-RECIST, quantitative ADC, and tumor volume evaluation. 21 patients underwent DCE-MRI curve type with quantitative parameters. Correlation between the different evaluations was carried out. Results were correlated with the post-operative pathology in 42 patients who underwent surgery and for statistical evaluation, Those patients were classified into responders (≥90% necrosis) and non-responders (<90% necrosis).

RESULTS

The initial mean ADC of 104 patients of osteosarcoma and Ewing's sarcoma (0.90 ± 0.29) and (0.71 ± 0.16) respectively, differed significantly from that after treatment (1.62 ± 0.46) and (1.6 ± 0.39) respectively with (p<0.001).ADC variations (ADC%) in the non-progressive group were higher than those of the progressive group (128.3 ± 63.49 vs 36.34 ± 78.7) % with (p<0.001).ADC values and ADC variations were inversely correlated with morphologic changes, regardless of the effectiveness of chemotherapy expressed as changes in tumor size based on (RECIST 1.1, RECIST, and 3D volume). Linear regression analysis revealed a Pearson correlation coefficient of r=-0.427, -0.498 and -0.408, respectively with (p<0.001).An increase in the ADC value was not always associated with a reduction in tumor volume. The disease control rate (defined as the percentage of CR+PR+SD patients) was 89.4% and 93.9% according to RECIST 1.1 and m-RECIST respectively.42 out of the 104 patients had postsurgical histological evaluation as regards the chemotherapeutic response divided into two groups. ADC values showed a statistically significant difference between Group A and Group B being more evident with minimum ADC% (p<0.001).

CONCLUSION

Quantitative diffusion-weighted imaging with ADC mapping and ADC % after chemotherapy allows a detailed analysis of the treatment response in osteosarcoma and Ewing's sarcoma. The therapeutic response can be underestimated using RECIST 1.1, so the modified RECIST should be also considered.

ADVANCES IN KNOWLEDGE

Quantitative ADC especially ADC% provided an accurate non-invasive tool in the assessment of post-therapeutic cases of osteosarcoma and Ewing's sarcoma.

The Value of Quantitative Musculoskeletal Imaging

Musculoskeletal imaging is mainly based on the subjective and qualitative analysis of imaging examinations. However, integration of quantitative assessment of imaging data could increase the value of imaging in both research and clinical practice. Some imaging modalities, such as perfusion magnetic resonance imaging (MRI), diffusion MRI, or T2 mapping, are intrinsically quantitative. But conventional morphological imaging can also be analyzed through the quantification of various parameters. The quantitative data retrieved from imaging examinations can serve as biomarkers and be used to support diagnosis, determine patient prognosis, or monitor therapy.

We focus on the value, or clinical utility, of quantitative imaging in the musculoskeletal field. There is currently a trend to move from volume- to value-based payments. This review contains definitions and examines the role that quantitative imaging may play in the implementation of value-based health care. The influence of artificial intelligence on the value of quantitative musculoskeletal imaging is also discussed.

Advanced Imaging in Musculoskeletal Oncology: Moving Away From RECIST and Embracing Advanced Bone and Soft Tissue Tumor Imaging (ABASTI) - Part I - Tumor Response Criteria and Established Functional Imaging Techniques

According to the Revised Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, the majority of bone metastases are considered to be nonmeasurable disease. Traditional response criteria rely on physical measurements. New criteria would be valuable if they incorporated newly developed imaging features in order to provide a more comprehensive assessment of oncological status. Advanced magnetic resonance imaging (MRI) sequences such as diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) with dynamic contrast-enhanced (DCE) perfusion imaging are reviewed in the context of the initial and post-therapeutic assessment of musculoskeletal tumors. Particular attention is directed to the pseudoprogression phenomenon in which a successfully treated tumor enlarges from the pretherapeutic baseline, followed by regression without a change in therapy.

Treatment effect prediction for sarcoma patients treated with preoperative radiotherapy using radiomics features from longitudinal diffusion-weighted MRIs

The objective of this study was to explore radiomics features from longitudinal diffusion-weighted MRIs (DWIs) for pathologic treatment effect prediction in patients with localized soft tissue sarcoma (STS) undergoing hypofractionated preoperative radiotherapy (RT). Thirty patients with localized STS treated with preoperative hypofractionated RT were recruited to this longitudinal imaging study. DWIs were acquired at three time points using a 0.35 T MRI-guided radiotherapy system. Treatment effect score (TES) was obtained from the post-surgery pathology as a surrogate of treatment outcome. Patients were divided into two groups based on TES. Response prediction was first performed using a support vector machine (SVM) with only mean apparent diffusion coefficient (ADC) or delta ADC to serve as the benchmark. Radiomics features were then extracted from tumor ADC maps at each of the three time points. Logistic regression and SVM were constructed to predict the TES group using features selected by univariate analysis and sequential forward selection. Classification performance using SVM with features from different time points and with or without delta radiomics were evaluated. Prediction performance using only mean ADC or delta ADC was poor (area under the curve (AUC) < 0.7). For the radiomics study using features from all time points and corresponding delta radiomics, SVM significantly outperformed logistic regression (AUC of 0.91 ± 0.05 v.s. 0.85 ± 0.06). Prediction AUC values using single or multiple time points without delta radiomics were all below 0.74. Including delta radiomics of mid- or post-treatment relative to the baseline drastically boosted the prediction. In this work, an SVM model was built to predict the TES using radiomics features from longitudinal DWI. Based on this study, we found that use of mean ADC, delta ADC, or radiomics features alone was not sufficient for response prediction, and including delta radiomics features of mid- or post-treatment relative to the baseline can optimize the prediction of TES, a pathologic and clinical endpoint.

Evaluation of 18F-FDG PET and DWI Datasets for Predicting Therapy Response of Soft-Tissue Sarcomas Under Neoadjuvant Isolated Limb Perfusion

Our purpose was to evaluate and compare the clinical utility of simultaneously obtained quantitative ¹⁸F-FDG PET and diffusion-weighted MRI datasets for predicting the histopathologic response of soft-tissue sarcoma (STS) to neoadjuvant isolated limb perfusion (ILP). Methods: In total, 37 patients with a confirmed STS of the extremities underwent ¹⁸F-FDG PET/MRI before and after ILP with melphalan and tumor necrosis factor-α. For each patient, the maximum tumor size, metabolic activity (SUV), and diffusion restriction (apparent diffusion coefficient, ADC) were determined in pre- and posttherapeutic examinations, and percentage changes during treatment were calculated. Mann-Whitney U testing and receiver-operating-characteristic analysis were used to compare the results of the different quantitative parameters to predict the histopathologic response to therapy. Results from histopathologic analysis after tumor resection served as the reference standard, and patients were defined as responders or nonresponders based on the grading scale by Salzer-Kuntschik. Results: Histopathologic analysis categorized 22 (59%) patients as responders (grades I-III) and 15 (41%) as nonresponders (grades IV-VI). Under treatment, tumors in responders showed a mean reduction in size (-9.7%) and metabolic activity (SUV_peak, -51.9%; SUV_mean, -43.8%), as well as an increase of the ADC values (ADC_min, +29.4%; ADC_mean, +32.8%). The percentage changes in nonresponders were -6.2% in tumor size, -17.3% in SUV_peak, -13.9% in SUV_mean, +15.3% in ADC_min, and +14.6% in ADC_mean Changes in SUV and ADC_mean significantly differed between responders and nonresponders (<0.01), whereas differences in tumor size and ADC_min did not (>0.05). The corresponding AUCs were 0.63 for tumor size, 0.87 for SUV_peak, 0.82 for SUV_mean, 0.63 for ADC_min, 0.84 for ADC_mean, and 0.89 for ratio of ADC_mean to SUV_peak Conclusion: PET- and MRI-derived quantitative parameters (SUV and ADC_mean) and their combination performed well in predicting the histopathologic therapy response of STS to neoadjuvant ILP. Therefore, integrated PET/MRI could serve as a valuable tool for pretherapeutic assessment as well as monitoring of neoadjuvant treatment strategies of STS.

Computed Tomography-Based Differentiation of Benign and Malignant Craniofacial Lesions in Neurofibromatosis Type I Patients: A Machine Learning Approach

Background: Because neurofibromatosis type I (NF1) is a cancer predisposition disease, it is important to distinguish between benign and malignant lesions, especially in the craniofacial area. Purpose: The purpose of this study is to improve effectiveness in the diagnostic performance in discriminating malignant from benign craniofacial lesions based on computed tomography (CT) using a Keras-based machine-learning model. Methods: The Keras-based machine learning technique, a neural network package in the Python language, was used to train the diagnostic model on CT datasets. Fifty NF1 patients with benign craniofacial neurofibromas and six NF1 patients with malignant peripheral nerve sheath tumors (MPNSTs) were selected as the training set. Three validation cohorts were used: validation cohort 1 (random selection of 90% of the patients in the training cohort), validation cohort 2 (an independent cohort of 9 NF1 patients with benign craniofacial neurofibromas and 11 NF1 patients with MPNST), and validation cohort 3 (eight NF1 patients with MPNST, not restricted to the craniofacial area). Sensitivity and specificity were tested using validation cohorts 1 and 2, and generalizability was evaluated using validation cohort 3. Results: A total of 59 NF1 patients with benign neurofibroma and 23 NF1 patients with MPNST were included. A Keras-based machine-learning model was successfully established using the training cohort. The accuracy was 96.99 and 100% in validation cohorts 1 and 2, respectively, discriminating NF1-related benign and malignant craniofacial lesions. However, the accuracy of this model was significantly reduced to 51.72% in the identification of MPNSTs in different body regions. Conclusion: The Keras-based machine learning technique showed the potential of robust diagnostic performance in the differentiation of craniofacial MPNSTs and benign neurofibromas in NF1 patients using CT images. However, the model has limited generalizability when applied to other body areas. With more clinical data accumulating in the model, this system may support clinical doctors in the primary screening of true MPNSTs from benign lesions in NF1 patients.

Therapy Response Assessment of Pediatric Tumors with Whole-Body Diffusion-weighted MRI and FDG PET/MRI

Background Whole-body diffusion-weighted (DW) MRI can help detect cancer with high sensitivity. However, the assessment of therapy response often requires information about tumor metabolism, which is measured with fluorine 18 fluorodeoxyglucose (FDG) PET. Purpose To compare tumor therapy response with whole-body DW MRI and FDG PET/MRI in children and young adults. Materials and Methods In this prospective, nonrandomized multicenter study, 56 children and young adults (31 male and 25 female participants; mean age, 15 years ± 4 [standard deviation]; age range, 6-22 years) with lymphoma or sarcoma underwent 112 simultaneous whole-body DW MRI and FDG PET/MRI between June 2015 and December 2018 before and after induction chemotherapy (ClinicalTrials.gov identifier: NCT01542879). The authors measured minimum tumor apparent diffusion coefficients (ADCs) and maximum standardized uptake value (SUV) of up to six target lesions and assessed therapy response after induction chemotherapy according to the Lugano classification or PET Response Criteria in Solid Tumors. The authors evaluated agreements between whole-body DW MRI- and FDG PET/MRI-based response classifications with Krippendorff α statistics. Differences in minimum ADC and maximum SUV between responders and nonresponders and comparison of timing for discordant and concordant response assessments after induction chemotherapy were evaluated with the Wilcoxon test. Results Good agreement existed between treatment response assessments after induction chemotherapy with whole-body DW MRI and FDG PET/MRI (α = 0.88). Clinical response prediction according to maximum SUV (area under the receiver operating characteristic curve = 100%; 95% confidence interval [CI]: 99%, 100%) and minimum ADC (area under the receiver operating characteristic curve = 98%; 95% CI: 94%, 100%) were similar (P = .37). Sensitivity and specificity were 96% (54 of 56 participants; 95% CI: 86%, 99%) and 100% (56 of 56 participants; 95% CI: 54%, 100%), respectively, for DW MRI and 100% (56 of 56 participants; 95% CI: 93%, 100%) and 100% (56 of 56 participants; 95% CI: 54%, 100%) for FDG PET/MRI. In eight of 56 patients who underwent imaging after induction chemotherapy in the early posttreatment phase, chemotherapy-induced changes in tumor metabolism preceded changes in proton diffusion (P = .002). Conclusion Whole-body diffusion-weighted MRI showed significant agreement with fluorine 18 fluorodeoxyglucose PET/MRI for treatment response assessment in children and young adults. © RSNA, 2020 Online supplemental material is available for this article.

Multimodality imaging of adult rhabdomyosarcoma: the added value of hybrid imaging

Rhabdomyosarcoma (RMS) represents more than 50% of paediatric soft tissue tumours. Conversely, it is extremely rare among adults, where it shows peculiar biological and clinical features that are still poorly investigated. RMS patients should be referred to a Sarcoma Centre, where the contribution of experienced radiologists plays a relevant role in the diagnostic assessment of the disease, including precise localisation, staging, image-guided biopsy, response evaluation after treatment and follow-up. Besides CT and MRI, hybrid imaging including positron emission tomography (PET)/CT and PET/MRI are giving an increasing contribution to provide functional insights about tumour biology and to improve the diagnostic accuracy of the imaging work-up. This review paper provides a revision of the pathology, clinical and radiological features of adult RMS, with a particular focus on the growing role of hybrid PET-based imaging.

Diffusion-Weighted Imaging in Oncology: An Update

To date, diffusion weighted imaging (DWI) is included in routine magnetic resonance imaging (MRI) protocols for several cancers. The real additive role of DWI lies in the "functional" information obtained by probing the free diffusivity of water molecules into intra and inter-cellular spaces that in tumors mainly depend on cellularity. Although DWI has not gained much space in some oncologic scenarios, this non-invasive tool is routinely used in clinical practice and still remains a hot research topic: it has been tested in almost all cancers to differentiate malignant from benign lesions, to distinguish different malignant histotypes or tumor grades, to predict and/or assess treatment responses, and to identify residual or recurrent tumors in follow-up examinations. In this review, we provide an up-to-date overview on the application of DWI in oncology.

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.

MRI of Rhabdomyosarcoma and Other Soft-Tissue Sarcomas in Children

Soft-tissue sarcomas in children comprise a heterogeneous group of entities with variable manifestation depending on the age of the patient and the location of the tumor. MRI is the modality of choice for evaluating musculoskeletal soft-tissue tumors and plays a paramount role in both initial diagnosis and assessment of tumor response during and after treatment. Conventional MRI sequences, such as T1- and T2-weighted imaging, offer morphologic information, which is important for localizing the lesion and describing anatomic relationships but not accurate for determining its malignant or benign nature and may be limited in differentiating tumor response from therapy-related changes. Advanced multiparametric MRI offers further functional information that can help with these tasks by using different imaging sequences and biomarkers. The authors present the role of MRI in rhabdomyosarcoma and other soft-tissue sarcomas in children, emphasizing a multiparametric approach with focus on the utility and potential added value of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI in characterization and staging, determination of pretreatment extent, and evaluation of tumor response and recurrence after treatment. ^©RSNA, 2020.

Current status and recommendations for imaging in neurofibromatosis type 1, neurofibromatosis type 2, and schwannomatosis

Neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2), and schwannomatosis (SWN) are three clinically distinct tumor predisposition syndromes with a shared tendency to develop peripheral and central nervous system neoplasms. Disease expression and complications of NF1, NF2, and SWN are highly variable, necessitating a multidisciplinary approach to care in order to optimize outcomes. This review will discuss the imaging appearance of NF1, NF2, and SWN and highlight the important role that imaging plays in informing management decisions in people with tumors associated with these syndromes. Recent technological advances, including the role of both whole-body and localized imaging strategies, routine anatomic and advanced magnetic resonance (MR) imaging sequences such as diffusion-weighted imaging (DWI) with quantitative apparent diffusion coefficient (ADC) mapping, and metabolic imaging techniques (MR spectroscopy and positron emission testing) are discussed in the context of the diagnosis and management of people with NF1, NF2, and SWN based on the most up-to-date clinical imaging studies.

Targeting Refractory Sarcomas and Malignant Peripheral Nerve Sheath Tumors in a Phase I/II Study of Sirolimus in Combination with Ganetespib (SARC023)

Purpose

Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive soft tissue sarcomas. Combining Hsp90 inhibitors to enhance endoplasmic reticulum stress with mTOR inhibition results in dramatic MPNST shrinkage in a genetically engineered MPNST mouse model. Ganetespib is an injectable potent small molecule inhibitor of Hsp90. Sirolimus is an oral mTOR inhibitor. We sought to determine the safety, tolerability, and recommended dose of ganetespib and sirolimus in patients with refractory sarcomas and assess clinical benefits in patients with unresectable/refractory MPNSTs. Patients and Methods. In this multi-institutional, open-label, phase 1/2 study of ganetespib and sirolimus, patients ≥16 years with histologically confirmed refractory sarcoma (phase 1) or MPNST (phase 2) were eligible. A conventional 3 + 3 dose escalation design was used for phase 1. Pharmacokinetic and pharmacodynamic measures were evaluated. Primary objectives of phase 2 were to determine the clinical benefit rate (CBR) of this combination in MPNSTs. Patient-reported outcomes assessed pain.

Results

Twenty patients were enrolled (10 per phase). Toxicities were manageable; most frequent non-DLTs were diarrhea, elevated liver transaminases, and fatigue. The recommended dose of ganetespib was 200 mg/m² intravenously on days 1, 8, and 15 with sirolimus 4 mg orally once daily with day 1 loading dose of 12 mg. In phase 1, one patient with leiomyosarcoma achieved a sustained partial response. In phase 2, no responses were observed. The median number of cycles treated was 2 (1–4). Patients did not meet the criteria for clinical benefit as defined per protocol. Pain ratings decreased or were stable.

Conclusion

Despite promising preclinical rationale and tolerability of the combination therapy, no responses were observed, and the study did not meet parameters for further evaluation in MPNSTs. This trial was registered with (NCT02008877).

Diffusion-weighted MR imaging diagnostic merits in the post-therapeutic assessment of musculoskeletal soft tissue sarcoma

Background

The purpose of the study is assessing the diagnostic merits of diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping in evaluating tumor response to chemo-radiotherapy. The study included 36 patients with soft tissue sarcoma, who received chemo/radiotherapy. Tumor longest dimension according to response evaluation criteria in solid tumors 1.1 (RECIST 1.1), the longest dimension of the contrast-enhanced portion of the tumor according to modified response evaluation criteria in solid tumors: (mRECIST), the tumor volume (VOL) (cm3), and DWI with ADC values were recorded.

Results

ADC values in the non-progressive group were higher than those of the progressive group after neoadjuvant treatment (1.63 ± 0.42 vs. 1.24 ± 0.35) with (p < 0.005). ADC variations in the non-progressive group were higher than those of the progressive group (27.09 ± 48.09 vs. − 3.08 ± 23.5)% with (p < 0.05). ADC values after neoadjuvant treatment were negatively related to tumor volume variations (VOL%) after neoadjuvant treatment. ADC variations (ADC%) were inversely correlated with morphologic changes, regardless of the effectiveness of anticancer therapy expressed as changes in tumor size based on (RECIST, mRECIST, and three-dimensional volumetric assessment). An increase in the ADC value was not always associated with a reduction of tumor volume.

Conclusion

Quantitative DW imaging after neoadjuvant therapy provides added value in determining treatment response in soft tissue sarcomas. Therapeutic response to neoadjuvant therapy can be underestimated using RECIST 1.1; therefore, the mRECIST should also be considered.

Utility of Multi-Parametric Quantitative Magnetic Resonance Imaging for Characterization and Radiotherapy Response Assessment in Soft-Tissue Sarcomas and Correlation With Histopathology

Purpose: To evaluate repeatability of quantitative multi-parametric MRI in retroperitoneal sarcomas, assess parameter changes with radiotherapy, and correlate pre-operative values with histopathological findings in the surgical specimens. Materials and Methods: Thirty patients with retroperitoneal sarcoma were imaged at baseline, of whom 27 also underwent a second baseline examination for repeatability assessment. 14/30 patients were treated with pre-operative radiotherapy and were imaged again after completing radiotherapy (50.4 Gy in 28 daily fractions, over 5.5 weeks). The following parameter estimates were assessed in the whole tumor volume at baseline and following radiotherapy: apparent diffusion coefficient (ADC), parameters of the intra-voxel incoherent motion model of diffusion-weighted MRI (D, f, D*), transverse relaxation rate, fat fraction, and enhancing fraction after gadolinium-based contrast injection. Correlation was evaluated between pre-operative quantitative parameters and histopathological assessments of cellularity and fat fraction in post-surgical specimens (ClinicalTrials.gov, registration number NCT01902667). Results: Upper and lower 95% limits of agreement were 7.1 and -6.6%, respectively for median ADC at baseline. Median ADC increased significantly post-radiotherapy. Pre-operative ADC and D were negatively correlated with cellularity (r = -0.42, p = 0.01, 95% confidence interval (CI) -0.22 to -0.59 for ADC; r = -0.45, p = 0.005, 95% CI -0.25 to -0.62 for D), and fat fraction from Dixon MRI showed strong correlation with histopathological assessment of fat fraction (r = 0.79, p = 10-7, 95% CI 0.69-0.86). Conclusion: Fat fraction on MRI corresponded to fat content on histology and therefore contributes to lesion characterization. Measurement repeatability was excellent for ADC; this parameter increased significantly post-radiotherapy even in disease categorized as stable by size criteria, and corresponded to cellularity on histology. ADC can be utilized for characterizing and assessing response in heterogeneous retroperitoneal sarcomas.

T2 -based MRI Delta-radiomics improve response prediction in soft-tissue sarcomas treated by neoadjuvant chemotherapy

BACKGROUND

Standard of care for patients with high-grade soft-tissue sarcoma (STS) are being redefined since neoadjuvant chemotherapy (NAC) has demonstrated a positive effect on patients' outcome. Yet response evaluation in clinical trials still relies on RECIST criteria.

PURPOSE

To investigate the added value of a Delta-radiomics approach for early response prediction in patients with STS undergoing NAC.

STUDY TYPE

Retrospective.

POPULATION

Sixty-five adult patients with newly-diagnosed, locally-advanced, histologically proven high-grade STS of trunk and extremities. All were treated by anthracycline-based NAC followed by surgery and had available MRI at baseline and after two chemotherapy cycles.

FIELD STRENGTH/SEQUENCE

Pre- and postcontrast enhanced T₁ -weighted imaging (T₁ -WI), turbo spin echo T₂ -WI at 1.5 T.

ASSESSMENT

A threshold of <10% viable cells on surgical specimens defined good response (Good-HR). Two senior radiologists performed a semantic analysis of the MRI. After 3D manual segmentation of tumors at baseline and early evaluation, and standardization of voxel-sizes and intensities, absolute changes in 33 texture and shape features were calculated.

STATISTICAL TESTS

Classification models based on logistic regression, support vector machine, k-nearest neighbors, and random forests were elaborated using crossvalidation (training and validation) on 50 patients ("training cohort") and was validated on 15 other patients ("test cohort").

RESULTS

Sixteen patients were good-HR. Neither RECIST status (P = 0.112) nor semantic radiological variables were associated with response (range of P-values: 0.134-0.490) except an edema decrease (P = 0.003), although 14 shape and texture features were (range of P-values: 0.002-0.037). On the training cohort, the highest diagnostic performances were obtained with random forests built on three features: Δ_Histogram_Entropy, Δ_Elongation, Δ_Surrounding_Edema, which provided: area under the curve the receiver operating characteristic = 0.86, accuracy = 88.1%, sensitivity = 94.1%, and specificity = 66.3%. On the test cohort, this model provided an accuracy of 74.6% but 3/5 good-HR were systematically ill-classified.

DATA CONCLUSION

A T₂ -based Delta-radiomics approach might improve early response assessment in STS patients with a limited number of features.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:497-510.