Magnetic resonance (MR) image guidance may facilitate safe ultrahypofractionated radiation dose escalation for inoperable pancreatic ductal adenocarcinoma. We conducted a prospective study evaluating ...the safety of 5-fraction Stereotactic MR-guided on-table Adaptive Radiation Therapy (SMART) for locally advanced (LAPC) and borderline resectable pancreatic cancer (BRPC).
Patients with LAPC or BRPC were eligible for this multi-institutional, single-arm, phase 2 trial after ≥3 months of systemic therapy without evidence of distant progression. Fifty gray in 5 fractions was prescribed on a 0.35T MR-guided radiation delivery system. The primary endpoint was acute grade ≥3 gastrointestinal (GI) toxicity definitely attributed to SMART.
One hundred thirty-six patients (LAPC 56.6%, BRPC 43.4%) were enrolled between January 2019 and January 2022. Mean age was 65.7 (36-85) years. Head of pancreas lesions were most common (66.9%). Induction chemotherapy mostly consisted of (modified)FOLFIRINOX (65.4%) or gemcitabine/nab-paclitaxel (16.9%). Mean CA19-9 after induction chemotherapy and before SMART was 71.7 U/mL (0-468). On-table adaptive replanning was performed for 93.1% of all delivered fractions. Median follow-up from diagnosis and SMART was 16.4 and 8.8 months, respectively. The incidence of acute grade ≥3 GI toxicity possibly or probably attributed to SMART was 8.8%, including 2 postoperative deaths that were possibly related to SMART in patients who had surgery. There was no acute grade ≥3 GI toxicity definitely related to SMART. One-year overall survival from SMART was 65.0%.
The primary endpoint of this study was met with no acute grade ≥3 GI toxicity definitely attributed to ablative 5-fraction SMART. Although it is unclear whether SMART contributed to postoperative toxicity, we recommend caution when pursuing surgery, especially with vascular resection after SMART. Additional follow-up is ongoing to evaluate late toxicity, quality of life, and long-term efficacy.
Traumatic brain injury (TBI) is a worldwide problem that results in death or disability for millions of people every year. Progressive neurological complications and long-term impairment can ...significantly disrupt quality of life. We demonstrated the feasibility of multiple magnetic resonance imaging (MRI) modalities to investigate and predict aberrant changes and progressive atrophy of gray and white matter tissue at several acute and chronic time points after moderate and severe parasagittal fluid percussion TBI. T2-weighted imaging, diffusion tensor imaging (DTI), and perfusion weighted imaging (PWI) were performed. Adult Sprague-Dawley rats were imaged sequentially on days 3, 14, and 1, 4, 6, 8, and 12 months following surgery. TBI caused dynamic white and gray matter alterations with significant differences in DTI values and injury-induced alterations in cerebral blood flow (CBF) as measured by PWI. Regional abnormalities after TBI were observed in T2-weighted images that showed hyperintense cortical lesions and significant cerebral atrophy in these hyperintense areas 1 year after TBI. Temporal DTI values indicated significant injury-induced changes in anisotropy in major white matter tracts, the corpus callosum and external capsule, and in gray matter, the hippocampus and cortex, at both early and chronic time points. These alterations were primarily injury-severity dependent with severe TBI exhibiting a greater degree of change relative to uninjured controls. PWI evaluating CBF revealed sustained global reductions in the cortex and in the hippocampus at most time points in an injury-independent manner. We next sought to investigate prognostic correlations across MRI metrics, timepoints, and cerebral pathology, and found that diffusion abnormalities and reductions in CBF significantly correlated with specific vulnerable structures at multiple time points, as well as with the degree of cerebral atrophy observed 1 year after TBI. This study further supports using DTI and PWI as a means of prognostic imaging for progressive structural changes after TBI and emphasizes the progressive nature of TBI damage.
We have created two neuron-specific mouse models of mitochondrial electron transport chain deficiencies involving defects in complex III (CIII) or complex IV (CIV). These conditional knockouts (cKOs) ...were created by ablation of the genes coding for the Rieske iron-sulfur protein (RISP) and COX10, respectively. RISP is one of the catalytic subunits of CIII and COX10 is an assembly factor indispensable for the maturation of Cox1, one of the catalytic subunits of CIV. Although the rates of gene deletion, protein loss and complex dysfunction were similar, the RISP cKO survived 3.5 months of age, whereas the COX10 cKO survived for 10-12 months. The RISP cKO had a sudden death, with minimal behavioral changes. In contrast, the COX10 cKO showed a distinctive behavioral phenotype with onset at 4 months of age followed by a slower but progressive neurodegeneration. Curiously, the piriform and somatosensory cortices were more vulnerable to the CIII defect whereas cingulate cortex and to a less extent piriform cortex were affected preferentially by the CIV defect. In addition, the CIII model showed severe and early reactive oxygen species damage, a feature not observed until very late in the pathology of the CIV model. These findings illustrate how specific respiratory chain defects have distinct molecular mechanisms, leading to distinct pathologies, akin to the clinical heterogeneity observed in patients with mitochondrial diseases.
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•MRI provides superior visualization of abdominal anatomy compared to CBCT.•MRgRT plan adaptation mitigates organ motion and provides superior dosimetry.•Several patients had ...meaningful reductions in OAR violations with online adaptation.•Not all liver SBRT patients materially benefit from online adaptation.•Higher plan quality may permit safe dose escalation without compromising quality.
Online Adaptive Radiotherapy (ART) with daily MR-imaging has the potential to improve dosimetric accuracy by accounting for inter-fractional anatomical changes. This study provides an assessment for the feasibility and potential benefits of online adaptive MRI-Guided Stereotactic Body Radiotherapy (SBRT) for treatment of liver cancer.
Ten patients with liver cancer treated with MR-Guided SBRT were included. Prescription doses ranged between 27 and 50 Gy in 3–5 fx. All SBRT fractions employed daily MR-guided setup while utilizing cine-MR gating. Organs-at-risk (OARs) included duodenum, bowel, stomach, kidneys and spinal cord. Daily MRIs and contours were utilized to create each adapted plan. Adapted plans used the beam-parameters and optimization-objectives from the initial plan. Planning target volume (PTV) coverage and OAR constraints were used to compare non-adaptive and adaptive plans.
PTV coverage for non-adapted treatment plans was below the prescribed coverage for 32/47 fractions (68%), with 11 fractions failing by more than 10%. All 47 adapted fractions met prescribed coverage. OAR constraint violations were also compared for several organs. The duodenum exceeded tolerance for 5/23 non-adapted and 0/23 for adapted fractions. The bowel exceeded tolerance for 5/34 non-adaptive and 1/34 adaptive fractions. The stomach exceeded tolerance for 4/19 non-adapted and 1/19 for adaptive fractions. Accumulated dose volume histograms were also generated for each patient.
Online adaptive MR-Guided SBRT of liver cancer using daily re-optimization resulted in better target conformality, coverage and OAR sparing compared with non-adaptive SBRT. Daily adaptive planning may allow for PTV dose escalation without compromising OAR sparing.
Extracting longitudinal image quantitative data, known as delta-radiomics, has the potential to capture changes in a patient's anatomy throughout the course of radiation treatment for prostate ...cancer. Some of the major challenges of delta-radiomics studies are contouring the structures for individual fractions and accruing patients' data in an efficient manner. The manual contouring process is often time consuming and would limit the efficiency of accruing larger sample sizes for future studies. The problem is amplified because the contours are often made by highly trained radiation oncologists with limited time to dedicate to research studies of this nature. This work compares the use of automated prostate contours generated using a deformable image-based algorithm to make predictive models of genitourinary and changes in total international prostate symptom score in comparison to manually contours for a cohort of fifty patients. Area under the curve of manual and automated models were compared using the Delong test. This study demonstrated that the delta-radiomics models were similar for both automated and manual delta-radiomics models.
Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in ...RT, MRI possesses excellent soft‐tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision‐making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.
This study provides a quantitative assessment of the accuracy of a commercially available deformable image registration (DIR) algorithm to automatically generate prostate contours and additionally ...investigates the robustness of radiomic features to differing contours. Twenty-eight prostate cancer patients enrolled on an institutional review board (IRB) approved protocol were selected. Planning CTs (pCTs) were deformably registered to daily cone-beam CTs (CBCTs) to generate prostate contours (auto contours). The prostate contours were also manually drawn by a physician. Quantitative assessment of deformed versus manually drawn prostate contours on daily CBCT images was performed using Dice similarity coefficient (DSC), mean distance-to-agreement (MDA), difference in center-of-mass position (ΔCM) and difference in volume (ΔVol). Radiomic features from 6 classes were extracted from each contour. Lin's concordance correlation coefficient (CCC) and mean absolute percent difference in radiomic feature-derived data (mean |%Δ|RF) between auto and manual contours were calculated. The mean (± SD) DSC, MDA, ΔCM and ΔVol between the auto and manual prostate contours were 0.90 ± 0.04, 1.81 ± 0.47 mm, 2.17 ± 1.26 mm and 5.1 ± 4.1% respectively. Of the 1,010 fractions under consideration, 94.8% of DIRs were within TG-132 recommended tolerance. 30 radiomic features had a CCC > 0.90 and 21 had a mean |%∆|RF < 5%. Auto-propagation of prostate contours resulted in nearly 95% of DIRs within tolerance recommendations of TG-132, leading to the majority of features being regarded as acceptably robust. The use of auto contours for radiomic feature analysis is promising but must be done with caution.
For prostate cancer (PCa) patients treated with definitive radiotherapy (RT), acute and late RT-related genitourinary (GU) toxicities adversely impact disease-specific quality of life. Early warning ...of potential RT toxicities can prompt interventions that may prevent or mitigate future adverse events. During intensity modulated RT (IMRT) of PCa, daily cone-beam computed tomography (CBCT) images are used to improve treatment accuracy through image guidance. This work investigated the performance of CBCT-based delta-radiomic features (DRF) models to predict acute and sub-acute International Prostate Symptom Scores (IPSS) and Common Terminology Criteria for Adverse Events (CTCAE) version 5 GU toxicity grades for 50 PCa patients treated with definitive RT. Delta-radiomics models were built using logistic regression, random forest for feature selection, and a 1000 iteration bootstrapping leave one analysis for cross validation. To our knowledge, no prior studies of PCa have used DRF models based on daily CBCT images. AUC of 0.83 for IPSS and greater than 0.7 for CTCAE grades were achieved as early as week 1 of treatment. DRF extracted from CBCT images showed promise for the development of models predictive of RT outcomes. Future studies will include using artificial intelligence and machine learning to expand CBCT sample sizes available for radiomics analysis.
Purpose
Radiomic features of cone‐beam CT (CBCT) images have potential as biomarkers to predict treatment response and prognosis for patients of prostate cancer. Previous studies of radiomic feature ...analysis for prostate cancer were assessed in a variety of imaging modalities, including MRI, PET, and CT, but usually limited to a pretreatment setting. However, CBCT images may provide an opportunity to capture early morphological changes to the tumor during treatment that could lead to timely treatment adaptation. This work investigated the quality of CBCT‐based radiomic features and their relationship with reconstruction methods applied to the CBCT projections and the preprocessing methods used in feature extraction. Moreover, CBCT features were correlated with planning CT (pCT) features to further assess the viability of CBCT radiomic features.
Methods
The quality of 42 CBCT‐based radiomic features was assessed according to their repeatability and reproducibility. Repeatability was quantified by correlating radiomic features between 20 CBCT scans that also had repeated scans within 15 minutes. Reproducibility was quantified by correlating radiomic features between the planning CT (pCT) and the first fraction CBCT for 20 patients. Concordance correlation coefficients (CCC) of radiomic features were used to estimate the repeatability and reproducibility of radiomic features. The same patient dataset was assessed using different reconstruction methods applied to the CBCT projections. CBCT images were generated using 18 reconstruction methods using iterative (iCBCT) and standard (sCBCT) reconstructions, three convolution filters, and five noise suppression filters. Eighteen preprocessing settings were also considered.
Results
Overall, CBCT radiomic features were more repeatable than reproducible. Five radiomic features are repeatable in > 97% of the reconstruction and preprocessing methods, and come from the gray‐level size zone matrix (GLSZM), neighborhood gray‐tone difference matrix (NGTDM), and gray‐level‐run length matrix (GLRLM) radiomic feature classes. These radiomic features were reproducible in > 9.8% of the reconstruction and preprocessing methods. Noise suppression and convolution filter smoothing increased radiomic features repeatability, but decreased reproducibility. The top‐repeatable iCBCT method (iCBCT‐Sharp‐VeryHigh) is more repeatable than the top‐repeatable sCBCT method (sCBCT‐Smooth) in 64% of the radiomic features.
Conclusion
Methods for reconstruction and preprocessing that improve CBCT radiomic feature repeatability often decrease reproducibility. The best approach may be to use methods that strike a balance repeatability and reproducibility such as iCBCT‐Sharp‐VeryLow‐1‐Lloyd‐256 that has 17 repeatable and eight reproducible radiomic features. Previous radiomic studies that only used pCT radiomic features have generated prognostic models of prostate cancer outcome. Since our study indicates that CBCT radiomic features correlated well with a subset of pCT radiomic features, one may expect CBCT radiomics to also generate prognostic models for prostate cancer.
To develop a prostate tumor habitat risk scoring (HRS) system based on multiparametric magnetic resonance imaging (mpMRI) referenced to prostatectomy Gleason score (GS) for automatic delineation of ...gross tumor volumes. A workflow for integration of HRS into radiation therapy boost volume dose escalation was developed in the framework of a phase 2 randomized clinical trial (BLaStM).
An automated quantitative mpMRI-based 10-point pixel-by-pixel method was optimized to prostatectomy GSs and volumes using referenced dynamic contrast-enhanced and apparent diffusion coefficient sequences. The HRS contours were migrated to the planning computed tomography scan for boost volume generation.
There were 51 regions of interest in 12 patients who underwent radical prostatectomy (26 with GS ≥7 and 25 with GS 6). The resultant heat maps showed inter- and intratumoral heterogeneity. The HRS6 level was significantly associated with radical prostatectomy regions of interest (slope 1.09, r = 0.767; P < .0001). For predicting the likelihood of cancer, GS ≥7 and GS ≥8 HRS6 area under the curve was 0.718, 0.802, and 0.897, respectively. HRS was superior to the Prostate Imaging, Reporting and Diagnosis System 4/5 classification, wherein the area under the curve was 0.62, 0.64, and 0.617, respectively (difference with HR6, P < .0001). HRS maps were created for the first 37 assessable patients on the BLaStM trial. There were an average of 1.38 habitat boost volumes per patient at a total boost volume average of 3.6 cm
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An automated quantitative mpMRI-based method was developed to objectively guide dose escalation to high-risk habitat volumes based on prostatectomy GS.
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