Intensity Harmonization Techniques Influence Radiomics Features and Radiomics-based Predictions in Sarcoma Patients

International audienceIntensity harmonization techniques (IHT) are mandatory to homogenize multicentric MRIs before any quantitative analysis because signal intensities (SI) do not have standardized units. Radiomics combine quantification of tumors' radiological phenotype with machine-learning to improve predictive models, such as metastasticrelapse-free survival (MFS) for sarcoma patients. We post-processed the initial T2weighted-imaging of 70 sarcoma patients by using 5 IHTs and extracting 45 radiomics features (RFs), namely: classical standardization (IHTstd), standardization per adipose tissue SIs (IHTfat), histogram-matching with a patient histogra

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

CT and MRI radiomics of bone and soft-tissue sarcomas: a systematic review of reproducibility and validation strategies

Feature reproducibility and model validation are two main challenges of radiomics. This study aims to systematically review radiomic feature reproducibility and predictive model validation strategies in studies dealing with CT and MRI radiomics of bone and soft-tissue sarcomas. The ultimate goal is to promote achieving a consensus on these aspects in radiomic workflows and facilitate clinical transferability

Using Radiomics to improve the 2-year survival of Non-Small Cell Lung Cancer Patients

This thesis both exploits and further contributes enhancements to the utilization of radiomics (extracted quantitative features of radiological imaging data) for improving cancer survival prediction. Several machine learning methods were compared in this analysis, including but not limited to support vector machines, convolutional neural networks and logistic regression.A technique for analysing prognostic image characteristics, for non-small cell lung cancer based on the edge regions, as well as tissues immediately surrounding visible tumours is developed. Regions external to and neighbouring a tumour were shown to also have prognostic value. By using the additional texture features an increase in accuracy, of 3%, is shown over previous approaches for predicting two-year survival, which has been determined by examining the outside rind tissue including the tumour compared to the volume without the rind. This indicates that while the centre of the tumour is currently the main clinical target for radiotherapy treatment, the tissue immediately around the tumour is also clinically important for survival analysis. Further, it was found that improved prediction resulted up to some 6 pixels outside the tumour volume, a distance of approximately 5mm outside the original gross tumour volume (GTV), when applying a support vector machine, which achieved the highest accuracy of 71.18%. This research indicates the periphery of the tumour is highly predictive of survival. To our knowledge this is the first study that has concentrically expanded and analysed the NSCLC rind for radiomic analysis

Detecting and Evaluating Therapy Induced Changes in Radiomics Features Measured from Non-Small Cell Lung Cancer to Predict Patient Outcomes

The purpose of this study was to investigate whether radiomics features measured from weekly 4-dimensional computed tomography (4DCT) images of non-small cell lung cancers (NSCLC) change during treatment and if those changes are prognostic for patient outcomes or dependent on treatment modality. Radiomics features are quantitative metrics designed to evaluate tumor heterogeneity from routine medical imaging. Features that are prognostic for patient outcome could be used to monitor tumor response and identify high-risk patients for adaptive treatment. This would be especially valuable for NSCLC due to the high prevalence and mortality of this disease. A novel process was designed to select feature-specific image preprocessing and remove features that were not robust to differences in CT model or tumor volumes. These features were then measured from weekly 4DCT images. These features were evaluated to determine at which point in treatment they first begin changing if those changes were different for patients treated with protons versus photons. A subset of features demonstrated significant changes by the second or third week of treatment, however changes were never significantly different between patient groups. Delta-radiomics features were defined as relative net changes, linear regression slopes, and end of treatment feature values. Features were then evaluated in univariate and multivariate models for overall survival, distant metastases, and local-regional recurrence. In general, the delta-radiomics features were not more prognostic than models built using clinical factors or features at pre-treatment. However one shape descriptor measured at pre-treatment significantly improved model fit and performance for overall survival and distant metastases. Additionally for local-regional recurrence, the only significant covariate was texture strength measured at the end of treatment. A separate study characterized radiomics feature variability in cone-beam CT images to increased scatter, increased motion, and different scanners. Features were affected by all three parameters and specifically by motion amplitudes greater than 1 cm. This study resulted in strong evidence that a set of robust radiomics features change significantly during treatment. While these changes were not prognostic or dependent on treatment modality, future studies may benefit from the methodologies described here to explore delta-radiomics in alternative tumor sites or imaging modalities

Outcomes of MR-guided Stereotactic Body Radiotherapy (SBRT) or yttrium-90 Transarterial Radioembolization for Hepatocellular Carcinoma Treated at an Urban Liver Transplant Center

Background: There are overlapping indications for both stereotactic body radiotherapy (SBRT) and yttrium-90 (Y90) trans-arterial radioembolization as locoregional treatments for hepatocellular cancer, though most centers preferentially use one modality over the other. MR-guided radiation allows both effective on-table localization and integrated motion management as compared with many traditional linear accelerators, allowing SBRT to be done more easily. Y90 radioembolization has been a well-established modality to deliver highly conformal dose due to the localization of the microspheres to the vascular supply of a tumor. We looked at patient characteristics and treatment outcomes for patients receiving MR-guided SBRT or Y90 at an urban transplant center. Objectives: To compare patient characteristics and treatment outcomes of MR-guided SBRT with Y90 transarterial radioembolization in a liver transplant center. Methods: This retrospective single-institution study analyzed patients with HCC treated with SBRT or Y90 from August 2017 to September 2020. To select a patient population eligible for either treatment modality, any Y90 procedures for lesions \u3e 10 cm or for treatment volumes \u3e 1000 cc were omitted from the cohort. A total of 239 patients were included in the analysis, receiving a total of 98 courses of SBRT and 187 courses of Y90 treatment. Local control (LC), freedom from liver progression (FFLP), and overall survival (OS) rates were measured from treatment completion date to death date or last follow-up. All outcomes were censored at time of loss to follow-up; LC and FFLP were censored at time of liver transplant if applicable. Cox regression models were used for survival, with significant factors on the univariate analysis further analyzed with a multivariate model. Results: Median time to follow-up was 11 months (0-44 mo). The mean size of lesions treated with SBRT were smaller than those treated with Y90 (2.7 cm vs 4.3 cm, P\u3c0.01). The groups of patients differed in liver disease characteristics, with SBRT patients having fewer Child-Pugh A disease (62% vs 80%, P\u3c0.01), more having received locoregional treatments to the liver in the past (81% v 35%, P\u3c0.01), and more disease in previously treated liver (57% vs 25%, P\u3c0.01). Dose of radiation for SBRT was 45-50 Gy administered in 5 fractions; dose of Y90 radiation to tumor was prescribed to a median of 235.2 Gy (range 55.8-512.3 Gy). There was a higher rate of one year LC in the SBRT cohort (77% vs 57%, P\u3c0.01), while median FFLP (9 mo vs 8 mo, P=NS) and median OS were not significantly different (24 mo vs 21 mo, P=NS). Multivariate analysis revealed size of largest lesion (P\u3c0.01) was correlated with decreased local control; a 1 cm increase in tumor size was associated with a 25% increased risk of local failure. Subsequent transplant (P\u3c0.01) was the remaining significant factor. Treatment modality did not remain an independent predictor of LC. Predictors of OS in multivariate analysis included age (P=0.01), prior liver treatments (HR 2.86, P\u3c0.01), size of largest lesion (P\u3c0.01), Child-Pugh stage (P\u3c0.01), portal vein thrombosis (HR 1.6, P=0.04), and subsequent liver transplant (HR 0.08, P\u3c0.01). Conclusions: These findings support the effectiveness of both MR-guided SBRT and Y90 transarterial radioembolization in locoregional management of HCC at a single institution despite clear differences in the patient cohorts. Though survival outcomes were comparable, local control differences favored the cohort treated by SBRT, in large part due to differences in tumor size. This data supports further investigation in a randomized study between SBRT and Y90

The Influence of Dosimetric Parameters on Quality of Life for Early Stage Non-small Cell Lung Cancer Patients Treated with Stereotactic Body Radiation Therapy

Background: Lung stereotactic body radiotherapy (SBRT) has become a standard treatment option for early stage non-small cell lung cancer (NSCLC) patients who are medically inoperable. The influence of radiation dose/volume parameters on quality of life is not known. Our hypothesis is that clinically meaningful declines in quality of life over time will be associated with increased radiation lung dose/volume parameters. Objectives: To investigate clinical toxicity and quality of life (QOL) outcomes of stage I NSCLC patients after SBRT as a function of radiation dose/volume parameters. Methods: In this IRB-approved study, 55 stage I NSCLC patients who received SBRT (12 Gy x 4) and completed QOL forms were analyzed. Clinical symptoms and QOL were measured at baseline and at 3, 6, 12, 18, 24, and 36 months post-SBRT. Clinical toxicity was graded using the common terminology criteria for adverse effects (CTCAE v4.0). Quality of life was followed using the validated Functional Assessment of Cancer Therapy-Trial Outcome Index (FACT-TOI) instrument. Dosimetric parameters, including the mean lung radiation dose (MLD), and the volume of normal lung receiving \u3e 5, 10, 13 or 20 Gy (V5, V10, V13, and V20) were measured from the radiation treatment plan. Student\u27s t-test and Pearson correlation analyses were used to examine the relationships between radiation lung metrics and clinically meaningful changes in QOL and/or clinical toxicities. Kaplan-Meier method was used to estimate rates of local control (LC), disease free survival (DFS), and overall survival (OS). Results: With a median follow-up of 24 months, the 3 year LC, DFS, and OS were 93%, 65% and 84%, respectively, with 5.5% grade 3 toxicity and no grade 4 or 5 toxicities. Clinically meaningful declines in patient reported QOL (FACT-TOI, lung cancer subscale, physical well-being, and/or functional well-being) post-treatment significantly correlated with increased dosimetric parameters, such as V10, V13, and V20. Conclusions: While lung SBRT is associated with excellent LC and minimal clinical toxicity for early stage NSCLC, clinically meaningful declines in QOL significantly correlated with increasing lung dose/volume parameters. This suggests that further improvements in the techniques of lung SBRT have the potential to further enhance patients\u27 QOL following this treatment