MRI-derived radiomics to guide post-operative management of glioblastoma: Implication for personalized radiation treatment volume delineation.

Background: The glioblastoma's bad prognosis is primarily due to intra-tumor heterogeneity, demonstrated from several studies that collected molecular biology, cytogenetic data and more recently radiomic features for a better prognostic stratification. The GLIFA project (GLIoblastoma Feature Analysis) is a multicentric project planned to investigate the role of radiomic analysis in GB management, to verify if radiomic features in the tissue around the resection cavity may guide the radiation target volume delineation. Materials and methods: We retrospectively analyze from three centers radiomic features extracted from 90 patients with total or near total resection, who completed the standard adjuvant treatment and for whom we had post-operative images available for features extraction. The Manual segmentation was performed on post gadolinium T1w MRI sequence by 2 radiation oncologists and reviewed by a neuroradiologist, both with at least 10 years of experience. The Regions of interest (ROI) considered for the analysis were: the surgical cavity ± post-surgical residual mass (CTV_cavity); the CTV a margin of 1.5 cm added to CTV_cavity and the volume resulting from subtracting the CTV_cavity from the CTV was defined as CTV_Ring. Radiomic analysis and modeling were conducted in RStudio. Z-score normalization was applied to each radiomic feature. A radiomic model was generated using features extracted from the Ring to perform a binary classification and predict the PFS at 6 months. A 3-fold cross-validation repeated five times was implemented for internal validation of the model. Results: Two-hundred and seventy ROIs were contoured. The proposed radiomic model was given by the best fitting logistic regression model, and included the following 3 features: F_cm_merged.contrast, F_cm_merged.info.corr.2, F_rlm_merged.rlnu. A good agreement between model predicted probabilities and observed outcome probabilities was obtained (p-value of 0.49 by Hosmer and Lemeshow statistical test). The ROC curve of the model reported an AUC of 0.78 (95% CI: 0.68-0.88). Conclusion: This is the first hypothesis-generating study which applies a radiomic analysis focusing on healthy tissue ring around the surgical cavity on post-operative MRI. This study provides a preliminary model for a decision support tool for a customization of the radiation target volume in GB patients in order to achieve a margin reduction strategy.

When your MR linac is down: Can an automated pipeline bail you out of trouble?

PURPOSE: The unique treatment delivery technique provided by magnetic resonance guided radiotherapy (MRgRT) can represent a significant drawback when system fail occurs. This retrospective study proposes and evaluates a pipeline to completely automate the workflow necessary to shift a MRgRT treatment to a traditional radiotherapy linac. MATERIAL AND METHODS: Patients undergoing treatment during the last MRgRT system failure were retrospectively included in this study. The core of the proposed pipeline was based on a tool able to mimic the original MR linac dose distribution. The so obtained dose distribution (AUTO) has been compared with the distribution obtained in the conventional radiotherapy linac (MAN). Plan comparison has been performed in terms of time required to obtain the final dose distribution, DVH parameters, dosimetric indices and visual analogue scales scoring by radiation oncologists. RESULTS: AUTO plans generation has been obtained within 10 min for all the considered cases. All AUTO plans were found to be within clinical tolerance, showing a mean target coverage variation of 1.7% with a maximum value of 4.3% and a minimum of 0.6% when compared with MAN plans. The highest OARs mean variation has been found for rectum V60 (6.7%). Dosimetric indices showed no relevant differences, with smaller gradient measure in favour of AUTO plans. Visual analogue scales scoring has confirmed comparable plan quality for AUTO plans. CONCLUSION: The proposed workflow allows a fast and accurate generation of automatic treatment plans. AUTO plans can be considered equivalent to MAN ones, with limited clinical impact in the worst-case scenario.

On dose cube pixel spacing pre-processing for features extraction stability in dosiomic studies.

PURPOSE: Dosiomics allows to parameterize regions of interest (ROIs) and to produce quantitative dose features encoding the spatial and statistical distribution of radiotherapy dose. The stability of dosiomics features extraction on dose cube pixel spacing variation has been investigated in this study. MATERIAL AND METHODS: Based on 17 clinical delivered dose distributions (Pn), dataset has been generated considering all the possible combinations of four dose grid resolutions and two calculation algorithms. Each dose voxel cube has been post-processed considering 4 different dose cube pixel spacing values: 1x1x1, 2x2x2, 3x3x3 mm3 and the one equal to the planning CT. Dosiomics features extraction has been performed from four different ROIs. The stability of each extracted dosiomic feature has been analyzed in terms of coefficient of variation (CV) intraclass correlation coefficient (ICC). RESULTS: The highest CV mean values were observed for PTV ROI and for the grey level size zone matrix features family. On the other hand, the lowest CV mean values have been found for RING ROI for the grey level co-occurrence matrix features family. P3 showed the highest percentage of CV >1 (1.14%) followed by P15 (0.41%), P1 (0.29%) and P13 (0.19%). ICC analysis leads to identify features with an ICC >0.95 that could be considered stable to use in dosiomic studies when different dose cube pixel spacing are considered, especially the features in common among the seventeen plans. CONCLUSION: Considering the observed variability, dosiomic studies should always provide a report not only on grid resolution and algorithm dose calculation, but also on dose cube pixel spacing.

VMAT-like plans for magnetic resonance guided radiotherapy: Addressing unmet needs.

PURPOSE: VMAT delivery technique is currently not applicable to Magnetic Resonance-guided radiotherapy (MRgRT) hybrid systems. Aim of this study is to evaluate an innovative VMAT-like (VML) delivery technique. MATERIAL AND METHODS: First, planning and dosimetric evaluation of the MRgRT VML treatment have been performed on 10 different disease sites and the results have been compared with the corresponding IMRT plans. Then, in the second phase, 10 of the most dosimetrically challenging locally advanced pancreas treatment plans have been retrospectively re-planned using the VML approach to explore the potentiality of this new delivery technique. Finally, VML robustness was evaluated and compared with the IMRT plans, considering a lateral positioning error of ± 5 mm. RESULTS: In phase one, all VML plans were within constraint for all OARs. When PTV coverage is considered, in the 50% of the cases VML PTV coverage is equal or higher than in IMRT plan. In the remaining 50%, the highest target under coverage difference in comparison with IMRT plan is -1.71%. The mean and maximum treatment time differences (VML-IMRT) is 0.2 min and 3.1 min respectively. In phase two, the treatment time variation (VML-IMRT), shows a mean, maximum and minimum variations of 1.3, 4.6 and -0.6 min respectively. All VML plans have a better target coverage if compared with IMRT plans, keeping in any case the OARs constraints within tolerance. VML doesn't increase plan robustness. CONCLUSION: VMAT-like treatment approach appeared to be an efficient planning solution and it was decided to clinically implement it in daily practice, especially in the frame of hypo fractionated treatments.

Dosimetric accuracy of dual isocenter irradiation in low magnetic field resonance guided radiotherapy system for extended abdominal tumours.

PURPOSE: Due to limited field size of Magnetic Resonance Linear Accelerators (MR-Linac), some treatments could require a dual-isocenter planning approach to achieve a complete target coverage and thus exploit the benefits of the online adaptation. This study evaluates the dosimetric accuracy of the dual-isocenter intensity modulated radiation therapy (IMRT) delivery technique for MR-Linac. MATERIAL AND METHODS: Dual-isocenter multi leaf collimator (MLC) and couch accuracy tests have been performed to evaluate the delivery accuracy of the system. A mono-isocenter plan delivered in clinical practice has then been retrospectively re-planned with dual-isocenter technique. The dual-isocenter plan has been re-calculated and delivered on a 3-dimensional (3D) ArcCHECK phantom and 2-dimensional (2D) films to assess its dosimetric accuracy in terms of gamma analysis. Clinical and planning target volume (CTV and PTV respectively) coverage robustness was then investigated after the introduction of ± 2 mm and ± 5 mm positioning errors by shifting the couch. RESULTS: MLC and couch accuracy tests confirmed the system accuracy in delivering a dual-isocenter irradiation. 2D/3D gamma analysis results occurred always to be above 95% if considered a gamma criteria 1%/2 mm and 1%/1 mm respectively for the 2D and 3D analysis. The mean variations for CTV D98% and PTV V95% were 0.2% and 1.1% respectively when positioning error was introduced separately in each direction, while the maximum observed variations were 0.9% (CTV) and 3.7% (PTV). CONCLUSION: The dosimetric accuracy of dual-isocenter irradiation has been verified for MR-Linac, achieving accurate and robust treatment strategy and improving dose conformality also in presence of targets whose extension exceeds the nominal maximum field size.

Stability of dosomics features extraction on grid resolution and algorithm for radiotherapy dose calculation.

PURPOSE: Dosomics is a novel texture analysis method to parameterize regions of interest and to produce dose features that encode the spatial and statistical distribution of radiotherapy dose at higher resolution than organ-level dose-volume histograms. This study investigates the stability of dosomics features extraction, as their variation due to changes of grid resolution and algorithm dose calculation. MATERIAL AND METHODS: Dataset has been generated considering all the possible combinations of four grid resolutions and two algorithms dose calculation of 18 clinical delivered dose distributions, leading to a 144 3D dose distributions dataset. Dosomics features extraction has been performed with an in-house developed software. A total number of 214 dosomics features has been extracted from four different region of interest: PTV, the two closest OARs and a RING structure. Reproducibility and stability of each extracted dosomic feature (Rfe, Sfe), have been analyzed in terms of intraclass correlation coefficient (ICC) and coefficient of variation. RESULTS: Dosomics features extraction was found reproducible (ICC > 0.99). Dosomic features, across the combination of grid resolutions and algorithms dose calculation, are more stable in the RING for all the considered feature's families. Sfe is higher in OARs, in particular for GLSZM features' families. Highest Sfe have been found in the PTV, in particular in the GLCM features' family. CONCLUSION: Stability and reproducibility of dosomics features have been evaluated for a representative clinical dose distribution case mix. These results suggest that, in terms of stability, dosomic studies should always perform a reporting of grid resolution and algorithm dose calculation.

Contrast-enhanced ultrasonography (CEUS) vs. MRI of the small bowel in the evaluation of Crohn's disease activity.

PURPOSE: The presence of disease activity in Crohn's disease (CD) is one of the main parameters used to establish whether optimal therapy should be drug therapy or surgery. However, a major problem in monitoring CD is the common mismatch between the patient's symptoms and imaging objective signs of disease activity. Bowel ultrasonography (US) has emerged as a low-cost, noninvasive technique in the diagnosis and follow-up of patients with CD. Accordingly, the use of contrast-enhanced US (CEUS) has made possible an evaluation of the vascular enhancement pattern, similar to the use of magnetic resonance imaging (MRI). The aim of our study was to evaluate the role of CEUS in comparison with small-bowel MRI for assessing Crohn's disease activity. MATERIALS AND METHODS: We prospectively enrolled 30 consecutive patients with known CD. Clinical and laboratory data were compared with imaging findings obtained from MRI and CEUS of the small bowel. MRI was performed with a 1.5-T system using phased-array coils and biphasic orally administered contrast agent prior to and after gadolinium chelate administration. We performed US with a 7.5-MHz linear-array probe and a second-generation contrast agent. The parameters analysed in both techniques were the following: lesion length, wall thickness, layered wall appearance, comb sign, fibroadipose proliferation, presence of enlarged lymph nodes and stenosis. We classified parietal enhancement curves into two types in relation to the contrast pattern obtained with the time-intensity curves at MRI and CEUS: (1) quick washin, quick washout, (2) slow washin, plateau with a slow washout. RESULTS: Comparison between Crohn's disease activity index (CDAI) and MRI showed a low correlation, with an rho=0.398; correlation between CDAI-laboratory data and CEUS activity was low, with rho=0.354; correlation between MRI activity and CEUS activity was good, with rho = 0.791; high correlation was found between CEUS and MRI of the small bowel when assessing wall-thickness, lymph nodes and comb sign; good correlation was fund when assessing layered wall appearance, disease extension and fibroadipose proliferation. At MRI, time-intensity curves for 12/30 patients were active, compared with for 14/30 patients at CEUS; therefore there was a poor correlation between curve on CEUS and curve on MRI (r=0.167; p=0.36). CONCLUSIONS: The use of CEUS can be recommended if there is a discrepancy between MRI and clinical/laboratory parameters. MRI of the small bowel remains the most accurate method for evaluating disease activity.