Artificial Intelligence-Based Organ Delineation for Radiation Treatment Planning of Prostate Cancer on Computed Tomography.

Purpose: Meticulous manual delineations of the prostate and the surrounding organs at risk are necessary for prostate cancer radiation therapy to avoid side effects to the latter. This process is time consuming and hampered by inter- and intraobserver variability, all of which could be alleviated by artificial intelligence (AI). This study aimed to evaluate the performance of AI compared with manual organ delineations on computed tomography (CT) scans for radiation treatment planning. Methods and Materials: Manual delineations of the prostate, urinary bladder, and rectum of 1530 patients with prostate cancer who received curative radiation therapy from 2006 to 2018 were included. Approximately 50% of those CT scans were used as a training set, 25% as a validation set, and 25% as a test set. Patients with hip prostheses were excluded because of metal artifacts. After training and fine-tuning with the validation set, automated delineations of the prostate and organs at risk were obtained for the test set. Sørensen-Dice similarity coefficient, mean surface distance, and Hausdorff distance were used to evaluate the agreement between the manual and automated delineations. Results: The median Sørensen-Dice similarity coefficient between the manual and AI delineations was 0.82, 0.95, and 0.88 for the prostate, urinary bladder, and rectum, respectively. The median mean surface distance and Hausdorff distance were 1.7 and 9.2 mm for the prostate, 0.7 and 6.7 mm for the urinary bladder, and 1.1 and 13.5 mm for the rectum, respectively. Conclusions: Automated CT-based organ delineation for prostate cancer radiation treatment planning is feasible and shows good agreement with manually performed contouring.

Impact of delineation errors on the estimated organ at risk dose and of dose errors on the normal tissue complication probability model.

BACKGROUND: Normal tissue complication probability (NTCP) models are often based on doses retrieved from delineated volumes. For retrospective dose-response studies focusing on organs that have not been delineated historically, automatic segmentation might be considered. However, automatic segmentation risks generating considerable delineation errors and knowledge regarding how these errors impact the estimated organ dose is important. Furthermore, organ-at-risk (OAR) dose uncertainties cannot be eliminated and might affect the resulting NTCP model. Therefore, it is also of interest to study how OAR dose errors impact the NTCP modeling results. PURPOSE: To investigate how random delineation errors of the proximal bronchial tree, heart, and esophagus impact the estimated OAR dose, and to investigate how random errors in the doses used for dose-response modeling affect the estimated NTCPs. METHODS: We investigated the impact of random delineation errors on the estimated OAR dose using the treatment plans of 39 patients treated with conventionally fractionated radiation therapy of non-small-cell lung cancer. Study-specific reference structures were defined by manually contouring the proximal bronchial tree, heart and esophagus. For each patient and organ, 120 reshaped structures were created by introducing random shifts and margins to the entire reference structure. The mean and near-maximum dose to the reference and reshaped structures were compared. In a separate investigation, the impact of random dose errors on the NTCP model was studied performing dose-response modeling with study sets containing treatment outcomes and OAR doses with and without introduced errors. Universal patient populations with defined population risks, dose-response relationships and distributions of OAR doses were used as ground truth. From such a universal population, we randomly sampled data sets consisting of OAR dose and treatment outcome into reference populations. Study sets of different sizes were created by repeatedly introducing errors to the OAR doses of each reference population. The NTCP models generated with dose errors were compared to the reference NTCP model of the corresponding reference population. RESULTS: A total of 14 040 reshaped structures with random delineation errors were created. The delineation errors resulted in systematic mean dose errors of less than 1% of the prescribed dose (PD). Mean dose differences above 15% of PD and near-maximum doses differences above 25% of PD were observed for 211 and 457 reshaped structures, respectively. Introducing random errors to OAR doses used for dose-response modeling resulted in systematic underestimations of the median NTCP. For all investigated scenarios, the median differences in NTCP were within 0.1 percentage points (p.p.) when comparing different study sizes. CONCLUSIONS: Introducing random delineation errors to the proximal bronchial tree, heart and esophagus resulted in mean dose and near-maximum dose differences above 15% and 25% of PD, respectively. We did not observe an association between the dose level and the magnitude of the dose errors. For the scenarios investigated in this study, introducing random errors to OAR doses used for dose-response modeling resulted in systematic underestimations of the median NTCP for reference risks higher than the universal population risk. The median NTCP underestimation was similar for different study sizes, all within 0.1 p.p.

A Primer on Dose-Response Data Modeling in Radiation Therapy.

An overview of common approaches used to assess a dose response for radiation therapy-associated endpoints is presented, using lung toxicity data sets analyzed as a part of the High Dose per Fraction, Hypofractionated Treatment Effects in the Clinic effort as an example. Each component presented (eg, data-driven analysis, dose-response analysis, and calculating uncertainties on model prediction) is addressed using established approaches. Specifically, the maximum likelihood method was used to calculate best parameter values of the commonly used logistic model, the profile-likelihood to calculate confidence intervals on model parameters, and the likelihood ratio to determine whether the observed data fit is statistically significant. The bootstrap method was used to calculate confidence intervals for model predictions. Correlated behavior of model parameters and implication for interpreting dose response are discussed.

Intrafractional relationship changes between an external breathing signal and fiducial marker positions in pancreatic cancer patients.

BACKGROUND AND PURPOSE: The purpose of this study of pancreatic cancer patients treated with respiratory-guided stereotactic body radiotherapy (SBRT) on a standard linac was to investigate (a) the intrafractional relationship change (IRC) between a breathing signal and the tumor position, (b) the impact of IRC on the delivered dose, and (c) potential IRC predictors. MATERIALS AND METHODS: We retrospectively investigated 10 pancreatic cancer patients with 2-4 implanted fiducial markers in the tumor treated with SBRT. Fluoroscopic images were acquired before and after treatment delivery simultaneously with the abdominal breathing motion. We quantified the IRC as the change in fiducial location for a given breathing amplitude in the left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions from before to after treatment delivery. The treatment plans were re-calculated after changing the isocenter coordinates according to the IRCs. Four treatment- or patient-related factors were investigated as potential predictors for IRC using linear models. RESULTS: The average (±1 SD) absolute IRCs in the LR, AP, and SI directions were 1.2 ± 1.2 mm, 0.7 ± 0.7 mm, and 1.1 ± 0.8 mm, respectively. The average 3D IRC was 2.0 ± 1.3 mm (range: 0.4-5.3 mm) for a median treatment delivery time of 8.5 min (range: 5.7-19.9 min; n = 31 fractions). The dose coverage of the internal target volume (ITV) decreased by more than 3% points in three of 31 fractions. In those cases, the 3D IRC had been larger than 4.3 mm. The 3D IRC was found to correlate with changes in the minimum breathing amplitude during treatment delivery. CONCLUSION: On average, 2 mm of treatment delivery accuracy was lost due to IRC. Periodical intrafractional imaging is needed to safely deliver respiratory-guided SBRT.

Analysis of early respiratory-related mortality after radiation therapy of non-small-cell lung cancer: feasibility of automatic data extraction for dose-response studies.

Purpose: To examine the feasibility of automatic data extraction from clinical radiation therapy (RT) databases at four hospitals to investigate the impact of mean lung dose (MLD) and age on the risk of early respiratory-related death and early overall death for patients treated with RT for non-small-cell lung cancer (NSCLC).Material and methods: We included adult patients with NSCLC receiving curatively intended RT between 2002 and 2017 at four hospitals. A script was developed to automatically extract RT-related data. The cause of death for patients deceased within 180 days of the start of RT was retrospectively assessed. Using logistic regression, the risks of respiratory-related death and of overall death within 90 and 180 days were investigated using MLD and age as variables.Results: Altogether, 1785 patients were included in the analysis of early overall mortality and 1655 of early respiratory-related mortality. The respiratory-related mortalities within 90 and 180 days were 0.9% (15/1655) and 3.6% (60/1655). The overall mortalities within 90 and 180 days were 2.5% (45/1785) and 10.6% (190/1785). Higher MLD and older age were associated with an increased risk of respiratory-related death within 180 days and overall death within 90 and 180 days (all p<.05). For example, the risk of respiratory-related death within 180 days and their 95% confidence interval for patients aged 65 and 75 years with MLDs of 20 Gy was according to our logistic model 3.8% (2.6-5.0%) and 7.7% (5.5-10%), respectively.Conclusions: Automatic data extraction was successfully used to pool data from four hospitals. MLD and age were associated with the risk of respiratory-related death within 180 days of the start of RT and with overall death within 90 and 180 days. A model quantifying the risk of respiratory-related death within 180 days was formulated.

Effects of long term storage on secondary metabolite profiles of cannabis resin.

The structural identification and the monitoring of the relative concentrations of a wide range of major (3) and minor secondary (16) metabolites used as marker substances for profiling of cannabis resin using GC-FID at the Swedish National Forensic Centre (NFC) has facilitated the mapping of their chemical and physical behaviors over a period of 48months whilst stored under different conditions (exposure to light, exposure to air, temperature). In all cases the behavior of this group of sesquiterpenes, sesquiterpenoids, cannabinoids and waxes could be directly related to their chemical lability/functionality. In particular, the identification of homologue triads for both Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) together with a group of seemingly chemically inert substances (for example, cannabicyclol(CBL) and the waxes (n-alkanes)) has created new tools for the establishment of common origins between samples of cannabis resins aged under different conditions. Since sampling of the resin blocks in NFC's method for profiling of cannabis resin is made below the surface, the effects of light incursion were found to be negligible. The effects of exposure to air (and indirectly temperature) were found to be more significant, not unexpectedly as many of the observed transformations were based on oxidation or rearrangement processes.

An in vitro study for the dosimetric and radiobiological validation of respiratory gating in conventional and hypofractionated radiotherapy of the lung: effect of dose, dose rate, and breathing pattern.

Stereotactic body radiotherapy (SBRT) of the lung has become a standard of care for early-stage inoperable non-small cell lung cancer (NSCLC). A common strategy to manage respiratory motion is gating, which inevitably results in an increase in treatment time, especially in irregularly-breathing patients. Flattening-filter free (FFF) beams allow for delivery of the treatment at a higher dose rate, therefore counteracting the lengthened treatment time due to frequent interruption of the beam during gated radiotherapy. In this study, we perform our in vitro evaluation of the dosimetric and radiobiological effect of gated lung SBRT with simultaneous integrated boost (SIB) using both flattened and FFF beams. A moving thorax-shaped phantom with inserts and applicators was used for simulation, planning, gated treatment delivery measurements and in vitro tests. The effects of gating window, dose rate, and breathing pattern were evaluated. Planned doses represented a typical conventional fractionation, 200 cGy per fraction with SIB to 240 cGy, flattened beam only, and SBRT, 800 cGy with SIB to 900 cGy, flattened and FFF beams. Ideal, as well as regular and irregular patient-specific breathing patterns with and without gating were used. A survival assay for lung adenocarcinoma A549 cell line was performed. Delivered dose was within 6% for locations planned to receive 200 and 800 cGy and within 4% for SIB locations. Time between first beam-on and last beam-off varied from approximately 1.5 min for conventional fractionation, 200/240 cGy, to 10.5 min for gated SBRT, 800/900 cGy doses, flattened beam and irregular breathing motion pattern. With FFF beams dose delivery time was shorter by a factor of 2-3, depending on the gating window and breathing pattern. We have found that, for the most part, survival depended on dose and not on dose rate, gating window, or breathing regularity.

Image-based Data Mining to Probe Dosimetric Correlates of Radiation-induced Trismus.

PURPOSE: To identify imaged regions in which dose is associated with radiation-induced trismus after head and neck cancer radiation therapy (HNRT) using a novel image-based data mining (IBDM) framework. METHODS AND MATERIALS: A cohort of 86 HNRT patients were analyzed for region identification. Trismus was characterized as a continuous variable by the maximum incisor-to-incisor opening distance (MID) at 6 months after radiation therapy. Patient anatomies and dose distributions were spatially normalized to a common frame of reference using deformable image registration. IBDM was used to identify clusters of voxels associated with MID (P ≤ .05 based on permutation testing). The result was externally tested on a cohort of 35 patients with head and neck cancer. Internally, we also performed a dose-volume histogram-based analysis by comparing the magnitude of the correlation between MID and the mean dose for the IBDM-identified cluster in comparison with 5 delineated masticatory structures. RESULTS: A single cluster was identified with the IBDM approach (P < .01), partially overlapping with the ipsilateral masseter. The dose-volume histogram-based analysis confirmed that the IBDM cluster had the strongest association with MID, followed by the ipsilateral masseter and the ipsilateral medial pterygoid (Spearman's rank correlation coefficients: Rs = -0.36, -0.35, -0.32; P = .001, .001, .002, respectively). External validation confirmed an association between mean dose to the IBDM cluster and MID (Rs = -0.45; P = .007). CONCLUSIONS: IBDM bypasses the common assumption that dose patterns within structures are unimportant. Our novel IBDM approach for continuous outcome variables successfully identified a cluster of voxels that are highly associated with trismus, overlapping partially with the ipsilateral masseter. Tests on an external validation cohort showed an even stronger correlation with trismus. These results support use of the region in HNRT treatment planning to potentially reduce trismus.

Clinical feasibility and positional stability of an implanted wired transmitter in a novel electromagnetic positioning system for prostate cancer radiotherapy.

PURPOSE: Three aspects of the RayPilot real-time tracking system were investigated: (1) feasibility of the transmitter with respect to implantation and explantation procedures, (2) user and patients' experiences and (3) quantification of the transmitter positional stability in relation to fiducial markers. METHODS AND MATERIALS: Ten prostate cancer patients scheduled for radiotherapy received transmitter implantation in the prostate, concomitantly with fiducial markers. Transmitter and marker positions were assessed in 3D by orthogonal kV-imaging at daily treatment setup in eight patients. RESULTS: The transmitter was successfully implanted in all patients. Patients reported mild to moderate discomfort and impact on daily activities due to the implant but overall subjective tolerability was good. One patient had spontaneous explantation of the transmitter after four fractions. One patient had transmitter 3D shifts >9 mm, but also inter-marker shifts >6 mm. The mean inter-marker shift in the remaining patients was <1 mm. In four patients, maximum transmitter 3D shifts were 5-7 mm (mean >2 mm). In three patients, mean transmitter 3D shifts were <2 mm. CONCLUSIONS: Implantation and explantation of the transmitter is generally feasible and safe. Patient tolerability is good overall. However, due to interfractional transmitter positional instability in this cohort, use of the system for real-time tracking should be combined with other daily setup techniques.

Automatic patient positioning and gating window settings in respiratory-gated stereotactic body radiation therapy for pancreatic cancer using fluoroscopic imaging.

Before treatment delivery of respiratory-gated radiation therapy (RT) in patients with implanted fiducials, both the patient position and the gating window thresholds must be set. In linac-based RT, this is currently done manually and setup accuracy will therefore be dependent on the skill of the user. In this study, we present an automatic method for finding the patient position and the gating window thresholds. Our method uses sequentially acquired anterior-posterior (AP) and lateral fluoroscopic imaging with simultaneous breathing amplitude monitoring and intends to reach 100% gating accuracy while keeping the duty cycle as high as possible. We retrospectively compared clinically used setups to the automatic setups by our method in five pancreatic cancer patients treated with hypofractionated RT. In 15 investigated fractions, the average (±standard deviation) differences between the clinical and automatic setups were -0.4 ± 0.8 mm, -1.0 ± 1.1 mm, and 1.8 ± 1.3 mm in the left-right (LR), the AP, and the superior-inferior (SI) direction, respectively. For the clinical setups, typical interfractional setup variations were 1-2 mm in the LR and AP directions, and 2-3 mm in the SI direction. Using the automatic method, the duty cycle could be improved in six fractions, in four fractions the duty cycle had to be lowered to improve gating accuracy, and in five fractions both duty cycle and gating accuracy could be improved. Our automatic method has the potential to increase accuracy and decrease user dependence of setup for patients with implanted fiducials treated with respiratory-gated RT. After fluoroscopic image acquisition, the calculated patient shifts and gating window thresholds are calculated in 1-2 s. The method gives the user the possibility to evaluate the effect of different patient positions and gating window thresholds on gating accuracy and duty cycle. If deemed necessary, it can be used at any time during treatment delivery.

Analyses of regional radiosensitivity of white matter structures along tract axes using novel white matter segmentation and diffusion imaging biomarkers.

BACKGROUND AND PURPOSE: Brain radiotherapy (RT) can cause white matter damage and downstream neurocognitive decline. We developed a computational neuroimaging tool to regionally partition individual white matter tracts, then analyze regional changes in diffusion metrics of white matter damage following brain RT. MATERIALS AND METHODS: RT dose, diffusion metrics and white matter tract structures were extracted and mapped to a reference brain for 49 patients who received brain RT, and underwent diffusion tensor imaging pre- and 9-12 months post-RT. Based on their elongation, 23 of 48 white matter tracts were selected. The Tract-Crawler software was developed in MATLAB to create cross-sectional slice planes normal to a tract's computed medial axis. We then performed slice- and voxel-wise analysis of radiosensitivity, defined as percent change in mean diffusivity (MD) and fractional anisotropy (FA) as a function of dose relative to baseline. RESULTS: Distinct patterns of FA/MD radiosensitivity were seen for specific tracts, including the corticospinal tract, medial lemniscus, and inferior cerebellar peduncle, in particular at terminal ends. These patterns persisted for corresponding tracts in left and right hemispheres. Local sensitivities were as high as 40%/Gy (e.g., voxel-wise: -39 ±â€¯31%/Gy in right corticospinal tract FA, -45 ±â€¯25%/Gy in right inferior cerebellar peduncle FA), p < 0.05. CONCLUSIONS: Tract-Crawler, a novel tool to visualize and analyze cuts of white matter structures normal to medial axes, was used to demonstrate that particular white matter tracts exhibit significant regional variations in radiosensitivity based on diffusion biomarkers.

A case-control study using motion-inclusive spatial dose-volume metrics to account for genito-urinary toxicity following high-precision radiotherapy for prostate cancer.

BACKGROUND AND PURPOSE: The risk of genitourinary (GU) toxicity is dose-limiting in radiotherapy (RT) for prostate cancer. This study investigated whether motion-inclusive spatial dose/volume metrics explain the GU toxicity manifesting after high-precision RT for prostate cancer. MATERIAL AND METHODS: A matched case-control was performed within a cohort of 258 prostate cancer patients treated with daily cone-beam CT (CBCT)-guided RT (prescription doses of 77.4-81.0 Gy). Twenty-seven patients (10.5%) presented late RTOG GU ≥ Grade 2 toxicity and those without symptoms of toxicity prior treatment (N = 7) were selected as cases. Each case was matched with three controls based on pre-treatment GU symptoms, age, Gleason score, follow-up time, and hormone therapy. Thirteen CBCTs per patient were rigidly registered to the planning CT using the recorded treatment shifts, and the bladder was manually contoured on each CBCT. Planned and actually delivered dose/volume metrics (the latter averaged across the CBCTs) were extracted from the bladder and its subsectors, and compared between cases and controls (two-way ANOVA test). RESULTS: There were no significant differences between planned and delivered dose/volume metrics; also, there were no significant differences between cases and controls at any dose level, neither for planned nor delivered doses. The cases tended to have larger bladder volumes during treatment than controls (221 ±â€¯71 cm3 vs 166 ±â€¯73 cm3; p = 0.09). CONCLUSIONS: High-precision RT for prostate cancer eliminates differences between planned and delivered dose distributions. Neither planned nor delivered bladder dose/volume metrics were associated to the remaining low risk of developing GU toxicity after high-precision radiotherapy for prostate cancer.

Spatial rectal dose/volume metrics predict patient-reported gastro-intestinal symptoms after radiotherapy for prostate cancer.

BACKGROUND: Gastro-intestinal (GI) toxicity after radiotherapy (RT) for prostate cancer reduces patient's quality of life. In this study, we explored associations between spatial rectal dose/volume metrics and patient-reported GI symptoms after RT for localized prostate cancer, and compared these with those of dose-surface/volume histogram (DSH/DVH) metrics. MATERIAL AND METHODS: Dose distributions and six GI symptoms (defecation urgency/emptying difficulties/fecal leakage, ≥Grade 2, median follow-up: 3.6 y) were extracted for 200 patients treated with image-guided RT in 2005-2007. Three hundred and nine metrics assessed from 2D rectal dose maps or DSHs/DVHs were subject to 50-times iterated five-fold cross-validated univariate and multivariate logistic regression analysis (UVA, MVA). Performance of the most frequently selected MVA models was evaluated by the area under the receiving-operating characteristics curve (AUC). RESULTS: The AUC increased for dose-map compared to DSH/DVH-based models (mean SD: 0.64 ± 0.03 vs. 0.61 ± 0.01), and significant relations were found for six versus four symptoms. Defecation urgency and faecal leakage were explained by high doses at the central/upper and central areas, respectively; while emptying difficulties were explained by longitudinal extensions of intermediate doses. CONCLUSIONS: Predictability of patient-reported GI toxicity increased using spatial metrics compared to DSH/DVH metrics. Novel associations were particularly identified for emptying difficulties using both approaches in which intermediate doses were emphasized.

A novel 3D-printed phantom insert for 4D PET/CT imaging and simultaneous integrated boost radiotherapy.

PURPOSE: To construct a 3D-printed phantom insert designed to mimic the variable PET tracer uptake seen in lung tumor volumes and a matching dosimetric insert to be used in simultaneous integrated boost (SIB) phantom studies, and to evaluate the design through end-to-end tests. METHODS: A set of phantom inserts was designed and manufactured for a realistic representation of gated radiotherapy steps from 4D PET/CT scanning to dose delivery. A cylindrical phantom (φ80 × 120 mm) holds inserts for PET/CT scanning. The novel 3D printed insert dedicated to 4D PET/CT mimics high PET tracer uptake in the core and low uptake in the periphery. This insert is a variable density porous cylinder (φ44.5 × 70.0 mm), ABS-P430 thermoplastic, 3D printed by fused deposition modeling an inner (φ11 × 42 mm) cylindrical void. The square pores (1.8 × 1.8 mm2 each) fill 50% of outer volume, resulting in a 2:1 PET tracer concentration ratio in the void volume with respect to porous volume. A matching cylindrical phantom insert is dedicated to validate gated radiotherapy. It contains eight peripheral holes and one central hole, matching the location of the porous part and the void part of the 3D printed insert, respectively. These holes accommodate adaptors for Farmer-type ion chamber and cells vials. End-to-end tests were designed for imaging, planning, and dose measurements. RESULTS: End-to-end test were performed from 4D PET/CT scanning to transferring data to the planning system, target volume delineation, and dose measurements. 4D PET/CT scans were acquired of the phantom at different respiratory motion patterns and gating windows. A measured 2:1 18F-FDG concentration ratio between inner void and outer porous volume matched the 3D printed design. Measured dose in the dosimetric insert agreed well with planned dose on the imaging insert, within 3% for the static phantom and within 5% for most breathing patterns. CONCLUSIONS: The novel 3D printed phantom insert mimics variable PET tracer uptake typical of tumors. Obtained 4D PET/CT scans are suitable for segmentation and treatment planning and delivery in SIB gated treatments. Our experiments demonstrate the feasibility of this set of phantom inserts serving as end-to-end quality-assurance phantoms of SIB radiotherapy.

Associations between volume changes and spatial dose metrics for the urinary bladder during local versus pelvic irradiation for prostate cancer.

BACKGROUND: Inter-fractional variation in urinary bladder volumes during the course of radiotherapy (RT) for prostate cancer causes deviations between planned and delivered doses. This study compared planned versus daily cone-beam CT (CBCT)-based spatial bladder dose distributions, for prostate cancer patients receiving local prostate treatment (local treatment) versus prostate including pelvic lymph node irradiation (pelvic treatment). MATERIAL AND METHODS: Twenty-seven patients (N = 15 local treatment; N = 12 pelvic treatment) were treated using daily image-guided RT (1.8 Gy@43-45 fx), adhering to a full bladder/empty rectum protocol. For each patient, 9-10 CBCTs were registered to the planning CT, using the clinically applied translations. The urinary bladder was manually segmented on each CBCT, 3 mm inner shells were generated, and semi and quadrant sectors were created using axial/coronal cuts. Planned and delivered DVH metrics were compared across patients and between the two groups of treatment (t-test, p < .05; Holm-Bonferroni correction). Associations between bladder volume variations and the dose-volume histograms (DVH) of the bladder and its sectors were evaluated (Spearman's rank correlation coefficient, rs). RESULTS: Bladder volumes varied considerably during RT (coefficient of variation: 16-58%). The population-averaged planned and delivered DVH metrics were not significantly different at any dose level. Larger treatment bladder volumes resulted in increased absolute volume of the posterior/inferior bladder sector receiving intermediate-high doses, in both groups. The superior bladder sector received less dose with larger bladder volumes for local treatments (rs ± SD: -0.47 ± 0.32), but larger doses for pelvic treatments (rs ± SD: 0.74 ± 0.24). CONCLUSIONS: Substantial bladder volume changes during the treatment course occurred even though patients were treated under a full bladder/daily image-guided protocol. Larger bladder volumes resulted in less bladder wall spared at the posterior-inferior sector, regardless the treatment received. Contrary, larger bladder volumes meant larger delivered doses to the superior bladder sector for pelvic RT but smaller doses for local treatments.

Multi-component diffusion characterization of radiation-induced white matter damage.

PURPOSE: We used multi-b-value diffusion models to characterize microstructural white matter changes after brain radiation into fast and slow components, in order to better understand the pathophysiology of radiation-induced tissue damage. METHODS: Fourteen patients were included in this retrospective analysis with imaging prior to, and at 1, 4-5, and 9-10 months after radiotherapy (RT). Diffusion signal decay within brain white matter was fit to a biexponential model to separate changes within the slow and fast components. Linear mixed-effects models were used to obtain estimates of the effect of radiation dose and time on the model parameters. RESULTS: We found an increase of 0.11 × 10-4 and 0.14 × 10-4 mm2 /s in the fast diffusion coefficient per unit dose-time (Gy-month) in the longitudinal and transverse directions, respectively. By contrast, the longitudinal slow diffusion coefficient decreased independently of dose, by 0.18 × 10-4 , 0.16 × 10-4 , and 0.098 × 10-4 mm2 /s at 1, 4, and 9 months post-RT, respectively. CONCLUSIONS: Radiation-induced white matter changes in the first year following RT are driven by dose-dependent increases in the fast component and dose-independent decreases in the slow component.

Dose-dependent white matter damage after brain radiotherapy.

BACKGROUND AND PURPOSE: Brain radiotherapy is limited in part by damage to white matter, contributing to neurocognitive decline. We utilized diffusion tensor imaging (DTI) with multiple b-values (diffusion weightings) to model the dose-dependency and time course of radiation effects on white matter. MATERIALS AND METHODS: Fifteen patients with high-grade gliomas treated with radiotherapy and chemotherapy underwent MRI with DTI prior to radiotherapy, and after months 1, 4-6, and 9-11. Diffusion tensors were calculated using three weightings (high, standard, and low b-values) and maps of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ∥), and radial diffusivity (λ⊥) were generated. The region of interest was all white matter. RESULTS: MD, λ∥, and λ⊥ increased significantly with time and dose, with corresponding decrease in FA. Greater changes were seen at lower b-values, except for FA. Time-dose interactions were highly significant at 4-6months and beyond (p<.001), and the difference in dose response between high and low b-values reached statistical significance at 9-11months for MD, λ∥, and λ⊥ (p<.001, p<.001, p=.005 respectively) as well as at 4-6months for λ∥ (p=.04). CONCLUSIONS: We detected dose-dependent changes across all doses, even <10Gy. Greater changes were observed at low b-values, suggesting prominent extracellular changes possibly due to vascular permeability and neuroinflammation.

A Factor Analysis Approach for Clustering Patient Reported Outcomes.

BACKGROUND: In the field of radiation oncology, the use of extensive patient reported outcomes is increasingly common to measure adverse side effects after radiotherapy in cancer patients. Factor analysis has the potential to identify an optimal number of latent factors (i.e., symptom groups). However, the ultimate goal of treatment response modeling is to understand the relationship between treatment variables such as radiation dose and symptom groups resulting from FA. Hence, it is crucial to identify clinically more relevant symptom groups and improved response variables from those symptom groups for a quantitative analysis. OBJECTIVES: The goal of this study is to design a computational method for finding clinically relevant symptom groups from PROs and to test associations between symptom groups and radiation dose. METHODS: We propose a novel approach where exploratory factor analysis is followed by confirmatory factor analysis to determine the relevant number of symptom groups. We also propose to use a combination of symptoms in a symptom group identified as a new response variable in linear regression analysis to investigate the relationship between the symptom group and dose-volume variables. RESULTS: We analyzed patient-reported gastrointestinal symptom profiles from 3 datasets in prostate cancer patients treated with radiotherapy. The final structural model of each dataset was validated using the other two datasets and compared to four other existing FA methods. Our systematic EFA-CFA approach provided clinically more relevant solutions than other methods, resulting in new clinically relevant outcome variables that enabled a quantitative analysis. As a result, statistically significant correlations were found between some dose-volume variables to relevant anatomic structures and symptom groups identified by FA. CONCLUSIONS: Our proposed method can aid in the process of understanding PROs and provide a basis for improving our understanding of radiation-induced side effects.