Dosimetric impact of bone marrow sparing for robustly optimized IMPT for locally advanced cervical cancer.

BACKGROUND AND PURPOSE: To investigate the trade-off between bone marrow sparing (BMS) and dose to organs at risk (OARs) for intensity modulated proton therapy (IMPT) for women with locally advanced cervical cancer (LACC). MATERIALS AND METHODS: Twenty LACC patients were retrospectively included. IMPT plans were created for each patient using automated treatment planning. These plans progressively reduced bone marrow mean doses by steps of 1 GyRBE, while constraining target coverage and conformality. The relation between bone marrow dose and bladder, small bowel, rectum, and sigmoid doses was evaluated. RESULTS: A total of 140 IMPT plans were created. Plans without BMS had an average [range] bone marrow mean dose of 17.3 [14.7-21.6] GyRBE , which reduced to 12.0 [10.0-14.0] GyRBE with maximum BMS. The mean OAR dose [range] increased modestly for 1 GyRBE BMS: 0.2 [0.0 - 0.6] GyRBE for bladder, 0.3 [-0.2 - 0.7] GyRBE for rectum, 0.4 [0.1 - 0.8] GyRBE for small bowel, and 0.2 [-0.2 - 0.4] GyRBE for sigmoid. Moreover, for maximum BMS, mean OAR doses [range] escalated by 3.3 [0.1 - 6.7] GyRBE for bladder, 5.8 [1.8 - 12.4] GyRBE for rectum, 3.9 [1.6 - 5.9] GyRBE for small bowel, and 2.7 [0.6 - 5.9] GyRBE for sigmoid. CONCLUSION: Achieving 1 GyRBE BMS for IMPT is feasible for LACC patients with limited dosimetric impact on other OARs. While further bone marrow dose reduction is possible for some patients, it may increase OAR doses substantially for others. Hence, we recommend a personalized approach when introducing BMS into clinical IMPT treatment planning to carefully assess individual patient benefits and risks.

Ex vivo radiation sensitivity assessment for individual head and neck cancer patients using deep learning-based automated nuclei and DNA damage foci detection.

Introduction: Tumor biopsy tissue response to ex vivo irradiation is potentially an interesting biomarker for in vivo tumor response, therefore, for treatment personalization. Tumor response ex vivo can be characterized by DNA damage response, expressed by the large-scale presence of DNA damage foci in tumor nuclei. Currently, characterizing tumor nuclei and DNA damage foci is a manual process that takes hours per patient and is subjective to inter-observer variability, which is not feasible in for clinical decision making. Therefore, our goal was to develop a method to automatically segment nuclei and DNA damage foci in tumor tissue samples treated with radiation ex vivo to characterize the DNA damage response, as potential biomarker for in vivo radio-sensitivity. Methods: Oral cavity tumor tissue of 21 patients was irradiated ex vivo (5 or 0 Gy), fixated 2 h post-radiation, and used to develop our method for automated nuclei and 53BP1 foci segmentation. The segmentation model used both deep learning and conventional image-analysis techniques. The training (22 %), validation (22 %), and test set (56 %) consisted of thousands of manually segmented nuclei and foci. The segmentations and number of foci per nucleus in the test set were compared to their ground truths. Results: The automatic nuclei and foci segmentations were highly accurate (Dice = 0.901 and Dice = 0.749, respectively). An excellent correlation (R2 = 0.802) was observed for the foci per nucleus that outperformed reported inter-observation variation. The analysis took âˆ¼ 8 s per image. Conclusion: This model can replace manual foci analysis for ex vivo irradiation of head-and-neck squamous cell carcinoma tissue, reduces the image-analysis time from hours to minutes, avoids the problem of inter-observer variability, enables assessment of multiple images or conditions, and provides additional information about the foci size. Thereby, it allows for reliable and rapid ex vivo radio-sensitivity assessment, as potential biomarker for response in vivo and treatment personalization.

Target Volume Coverage and Organ at Risk Doses for Left-sided Whole-breast Irradiation With or Without Internal Mammary Chain Irradiation: A Comparison Between Three Techniques Representing the Past and the Present.

AIMS: The 15-year results of the EORTC 229922-10925 phase III trial showed a significant reduction in breast cancer mortality and breast cancer recurrences after internal mammary chain (IMC) and medio-supraclavicular irradiation. Unexpectedly, cardiac death was not increased, and the incidence of cardiac events did not differ between left- and right-sided cases, although target volume coverages and organ at risk doses were unknown. Therefore, a planning study was carried out comparing the past and the present, to eventually enable, thereafter, an increased therapeutic ratio of IMC irradiation. MATERIALS AND METHODS: A planning study was carried out on target volume coverage and organ at risk doses for whole-breast irradiation (WBI) ± IMC comparing the results between two-dimensional radiotherapy (free-breathing), hybrid intensity-modulated radiotherapy (IMRT; breath-hold) and robust intensity-modulated proton therapy (IMPT; free-breathing) for 10 left-sided breast cancer cases. Two-dimensional radiotherapy consisted of two tangential wedged photon breast fields and mixed electron/photon beams for the IMC. Hybrid IMRT included two tangential photon breast fields (70%) complemented with IMRT (30%). IMPT plans were created using multi-field robust optimisation (5 mm set-up and 3% range uncertainties) with two (WBI) or three (WBI + IMC) beams. RESULTS: Target volume dose objectives were met for hybrid IMRT and IMPT. For two-dimensional radiotherapy, target coverage was 97% and 83% for breast and IMC, respectively. The mean heart dose for WBI only was <2 Gy for all techniques. For WBI + IMC, heart doses (mean heart dose, mean left anterior descending region, volume of the heart receiving 5 Gy (V5) were significantly higher for two-dimensional radiotherapy when compared with contemporary techniques. The V5 left anterior descending region reduced from 100% (two-dimensional radiotherapy) to 70% and 20% for hybrid IMRT and IMPT, respectively. CONCLUSION: Contemporary radiotherapy techniques result in improved target volume coverage and significantly decreased heart doses for WBI + IMC radiotherapy. Hence, nowadays an increased therapeutic ratio of elective IMC irradiation may be anticipated.

What is the optimal number of library plans in ART for locally advanced cervical cancer?

PURPOSE: Library-of-plans ART is used to manage daily anatomy changes in locally advanced cervical cancer. In our institute, the library contains 2 VMAT plans for patients with large cervix-uterus motion. Increasing this number could be beneficial for tissue sparing, but is burdensome while the dosimetric gain is yet unclear. This study's aim is to determine the optimal number of plans at an individual patient level. MATERIAL AND METHODS: Data of 14 treated patients were analyzed. Plan libraries were created containing 1-4 VMAT plans. Pre-treatment extent of uterus motion was defined by the 99th percentile of the Hausdorff distance (HD99). For dosimetric evaluations, OARs were contoured in daily CBCT scans, plan selection was simulated, and the V45Gy and V40Gy parameters were recorded. RESULTS: Moderate to strong correlations were found between HD99 and the volume of spared OARs. All patients benefitted from adding a 2nd plan, as is the clinical practice. For patients with a HD99 between 30 and 50mm, a 3-plan library reduced the composite V40Gy with 11-21ml compared to a 2-plan library. CONCLUSION: Patients with large uterus motion (HD99>30mm) would benefit from an extension of the plan library to 3. HD99 is an easy-to-implement criteria to select those patients pre-treatment.

Dynamics of patient reported quality of life and symptoms in the acute phase of online adaptive external beam radiation therapy for locally advanced cervical cancer.

OBJECTIVE: For locally advanced cervical cancer patients, treated with External Beam Radiotherapy (EBRT), Quality of Life (QoL) questionnaires arefrequently used to evaluate treatment-related symptoms and functioning scales. Currently, it is unknown how those evolve during the radiation treatment course. In this prospective study we report on weekly-captured patient-reported QoL and symptoms during image-guided adaptive radiotherapy (IGART) of cervical cancer patients. MATERIAL AND METHODS: Between January 2012 and September 2016, all locally advanced cervical cancer patients treated with IGART and brachytherapy with or without chemotherapy or hyperthermia, were eligible. QoL was assessed at baseline; weekly during the first five weeks of treatment; 1week, 1 and 3months after treatment, using the EORTC QLQ-C30 and the QLQ-CX24 questionnaires. Comparisons were made with an age-matched norm population. RESULTS: Among the 138 (70%) responders, most symptoms showed a moderate-to-large increase, reaching a maximum at the end of treatment, or first week after treatment with return to baseline value at 3months after treatment. While most symptoms gradually increased during the first five weeks, diarrhea and bowel cramps already markedly increased within the first three weeks to reach a plateau at the 5th week of treatment. Global health and functioning were temporarily decreased and returned to a plateau at baseline level 3months after treatment, except for cognitive functioning. CONCLUSION: A profound impact on QoL was observed during the radiation treatment course, temporarily affecting functioning. The maximum impaired was reached at the end of EBRT.

Validation of deformable image registration algorithms on CT images of ex vivo porcine bladders with fiducial markers.

PURPOSE: The spatial accuracy of deformable image registration (DIR) is important in the implementation of image guided adaptive radiotherapy techniques for cancer in the pelvic region. Validation of algorithms is best performed on phantoms with fiducial markers undergoing controlled large deformations. Excised porcine bladders, exhibiting similar filling and voiding behavior as human bladders, provide such an environment. The aim of this study was to determine the spatial accuracy of different DIR algorithms on CT images of ex vivo porcine bladders with radiopaque fiducial markers applied to the outer surface, for a range of bladder volumes, using various accuracy metrics. METHODS: Five excised porcine bladders with a grid of 30-40 radiopaque fiducial markers attached to the outer wall were suspended inside a water-filled phantom. The bladder was filled with a controlled amount of water with added contrast medium for a range of filling volumes (100-400 ml in steps of 50 ml) using a luer lock syringe, and CT scans were acquired at each filling volume. DIR was performed for each data set, with the 100 ml bladder as the reference image. Six intensity-based algorithms (optical flow or demons-based) implemented in theMATLAB platform DIRART, a b-spline algorithm implemented in the commercial software package VelocityAI, and a structure-based algorithm (Symmetric Thin Plate Spline Robust Point Matching) were validated, using adequate parameter settings according to values previously published. The resulting deformation vector field from each registration was applied to the contoured bladder structures and to the marker coordinates for spatial error calculation. The quality of the algorithms was assessed by comparing the different error metrics across the different algorithms, and by comparing the effect of deformation magnitude (bladder volume difference) per algorithm, using the Independent Samples Kruskal-Wallis test. RESULTS: The authors found good structure accuracy without dependency on bladder volume difference for all but one algorithm, and with the best result for the structure-based algorithm. Spatial accuracy as assessed from marker errors was disappointing for all algorithms, especially for large volume differences, implying that the deformations described by the registration did not represent anatomically correct deformations. The structure-based algorithm performed the best in terms of marker error for the large volume difference (100-400 ml). In general, for the small volume difference (100-150 ml) the algorithms performed relatively similarly. The structure-based algorithm exhibited the best balance in performance between small and large volume differences, and among the intensity-based algorithms, the algorithm implemented in VelocityAI exhibited the best balance. CONCLUSIONS: Validation of multiple DIR algorithms on a novel physiological bladder phantom revealed that the structure accuracy was good for most algorithms, but that the spatial accuracy as assessed from markers was low for all algorithms, especially for large deformations. Hence, many of the available algorithms exhibit sufficient accuracy for contour propagation purposes, but possibly not for accurate dose accumulation.

Generic method for automatic bladder segmentation on cone beam CT using a patient-specific bladder shape model.

PURPOSE: The aim of this study is to develop and validate a generic method for automatic bladder segmentation on cone beam computed tomography (CBCT), independent of gender and treatment position (prone or supine), using only pretreatment imaging data. METHODS: Data of 20 patients, treated for tumors in the pelvic region with the entire bladder visible on CT and CBCT, were divided into four equally sized groups based on gender and treatment position. The full and empty bladder contour, that can be acquired with pretreatment CT imaging, were used to generate a patient-specific bladder shape model. This model was used to guide the segmentation process on CBCT. To obtain the bladder segmentation, the reference bladder contour was deformed iteratively by maximizing the cross-correlation between directional grey value gradients over the reference and CBCT bladder edge. To overcome incorrect segmentations caused by CBCT image artifacts, automatic adaptations were implemented. Moreover, locally incorrect segmentations could be adapted manually. After each adapted segmentation, the bladder shape model was expanded and new shape patterns were calculated for following segmentations. All available CBCTs were used to validate the segmentation algorithm. The bladder segmentations were validated by comparison with the manual delineations and the segmentation performance was quantified using the Dice similarity coefficient (DSC), surface distance error (SDE) and SD of contour-to-contour distances. Also, bladder volumes obtained by manual delineations and segmentations were compared using a Bland-Altman error analysis. RESULTS: The mean DSC, mean SDE, and mean SD of contour-to-contour distances between segmentations and manual delineations were 0.87, 0.27 cm and 0.22 cm (female, prone), 0.85, 0.28 cm and 0.22 cm (female, supine), 0.89, 0.21 cm and 0.17 cm (male, supine) and 0.88, 0.23 cm and 0.17 cm (male, prone), respectively. Manual local adaptations improved the segmentation results significantly (p < 0.01) based on DSC (6.72%) and SD of contour-to-contour distances (0.08 cm) and decreased the 95% confidence intervals of the bladder volume differences. Moreover, expanding the shape model improved the segmentation results significantly (p < 0.01) based on DSC and SD of contour-to-contour distances. CONCLUSIONS: This patient-specific shape model based automatic bladder segmentation method on CBCT is accurate and generic. Our segmentation method only needs two pretreatment imaging data sets as prior knowledge, is independent of patient gender and patient treatment position and has the possibility to manually adapt the segmentation locally.

Improved efficiency of multi-criteria IMPT treatment planning using iterative resampling of randomly placed pencil beams.

This study investigates whether 'pencil beam resampling', i.e. iterative selection and weight optimization of randomly placed pencil beams (PBs), reduces optimization time and improves plan quality for multi-criteria optimization in intensity-modulated proton therapy, compared with traditional modes in which PBs are distributed over a regular grid. Resampling consisted of repeatedly performing: (1) random selection of candidate PBs from a very fine grid, (2) inverse multi-criteria optimization, and (3) exclusion of low-weight PBs. The newly selected candidate PBs were added to the PBs in the existing solution, causing the solution to improve with each iteration. Resampling and traditional regular grid planning were implemented into our in-house developed multi-criteria treatment planning system 'Erasmus iCycle'. The system optimizes objectives successively according to their priorities as defined in the so-called 'wish-list'. For five head-and-neck cancer patients and two PB widths (3 and 6 mm sigma at 230 MeV), treatment plans were generated using: (1) resampling, (2) anisotropic regular grids and (3) isotropic regular grids, while using varying sample sizes (resampling) or grid spacings (regular grid). We assessed differences in optimization time (for comparable plan quality) and in plan quality parameters (for comparable optimization time). Resampling reduced optimization time by a factor of 2.8 and 5.6 on average (7.8 and 17.0 at maximum) compared with the use of anisotropic and isotropic grids, respectively. Doses to organs-at-risk were generally reduced when using resampling, with median dose reductions ranging from 0.0 to 3.0 Gy (maximum: 14.3 Gy, relative: 0%-42%) compared with anisotropic grids and from -0.3 to 2.6 Gy (maximum: 11.4 Gy, relative: -4%-19%) compared with isotropic grids. Resampling was especially effective when using thin PBs (3 mm sigma). Resampling plans contained on average fewer PBs, energy layers and protons than anisotropic grid plans and more energy layers and protons than isotropic grid plans. In conclusion, resampling resulted in improved plan quality and in considerable optimization time reduction compared with traditional regular grid planning.

Control over structure-specific flexibility improves anatomical accuracy for point-based deformable registration in bladder cancer radiotherapy.

PURPOSE: Future developments in image guided adaptive radiotherapy (IGART) for bladder cancer require accurate deformable image registration techniques for the precise assessment of tumor and bladder motion and deformation that occur as a result of large bladder volume changes during the course of radiotherapy treatment. The aim was to employ an extended version of a point-based deformable registration algorithm that allows control over tissue-specific flexibility in combination with the authors' unique patient dataset, in order to overcome two major challenges of bladder cancer registration, i.e., the difficulty in accounting for the difference in flexibility between the bladder wall and tumor and the lack of visible anatomical landmarks for validation. METHODS: The registration algorithm used in the current study is an extension of the symmetric-thin plate splines-robust point matching (S-TPS-RPM) algorithm, a symmetric feature-based registration method. The S-TPS-RPM algorithm has been previously extended to allow control over the degree of flexibility of different structures via a weight parameter. The extended weighted S-TPS-RPM algorithm was tested and validated on CT data (planning- and four to five repeat-CTs) of five urinary bladder cancer patients who received lipiodol injections before radiotherapy. The performance of the weighted S-TPS-RPM method, applied to bladder and tumor structures simultaneously, was compared with a previous version of the S-TPS-RPM algorithm applied to bladder wall structure alone and with a simultaneous nonweighted S-TPS-RPM registration of the bladder and tumor structures. Performance was assessed in terms of anatomical and geometric accuracy. The anatomical accuracy was calculated as the residual distance error (RDE) of the lipiodol markers and the geometric accuracy was determined by the surface distance, surface coverage, and inverse consistency errors. Optimal parameter values for the flexibility and bladder weight parameters were determined for the weighted S-TPS-RPM. RESULTS: The weighted S-TPS-RPM registration algorithm with optimal parameters significantly improved the anatomical accuracy as compared to S-TPS-RPM registration of the bladder alone and reduced the range of the anatomical errors by half as compared with the simultaneous nonweighted S-TPS-RPM registration of the bladder and tumor structures. The weighted algorithm reduced the RDE range of lipiodol markers from 0.9-14 mm after rigid bone match to 0.9-4.0 mm, compared to a range of 1.1-9.1 mm with S-TPS-RPM of bladder alone and 0.9-9.4 mm for simultaneous nonweighted registration. All registration methods resulted in good geometric accuracy on the bladder; average error values were all below 1.2 mm. CONCLUSIONS: The weighted S-TPS-RPM registration algorithm with additional weight parameter allowed indirect control over structure-specific flexibility in multistructure registrations of bladder and bladder tumor, enabling anatomically coherent registrations. The availability of an anatomically validated deformable registration method opens up the horizon for improvements in IGART for bladder cancer.

Individualized nonadaptive and online-adaptive intensity-modulated radiotherapy treatment strategies for cervical cancer patients based on pretreatment acquired variable bladder filling computed tomography scans.

PURPOSE: To design and evaluate individualized nonadaptive and online-adaptive strategies based on a pretreatment established motion model for the highly deformable target volume in cervical cancer patients. METHODS AND MATERIALS: For 14 patients, nine to ten variable bladder filling computed tomography (CT) scans were acquired at pretreatment and after 40 Gy. Individualized model-based internal target volumes (mbITVs) accounting for the cervix and uterus motion due to bladder volume changes were generated by using a motion-model constructed from two pretreatment CT scans (full and empty bladder). Two individualized strategies were designed: a nonadaptive strategy, using an mbITV accounting for the full-range of bladder volume changes throughout the treatment; and an online-adaptive strategy, using mbITVs of bladder volume subranges to construct a library of plans. The latter adapts the treatment online by selecting the plan-of-the-day from the library based on the measured bladder volume. The individualized strategies were evaluated by the seven to eight CT scans not used for mbITVs construction, and compared with a population-based approach. Geometric uniform margins around planning cervix-uterus and mbITVs were determined to ensure adequate coverage. For each strategy, the percentage of the cervix-uterus, bladder, and rectum volumes inside the planning target volume (PTV), and the clinical target volume (CTV)-to-PTV volume (volume difference between PTV and CTV) were calculated. RESULTS: The margin for the population-based approach was 38 mm and for the individualized strategies was 7 to 10 mm. Compared with the population-based approach, the individualized nonadaptive strategy decreased the CTV-to-PTV volume by 48% ± 6% and the percentage of bladder and rectum inside the PTV by 5% to 45% and 26% to 74% (p < 0.001), respectively. Replacing the individualized nonadaptive strategy by an online-adaptive, two-plan library further decreased the percentage of bladder and rectum inside the PTV (0% to 10% and -1% to 9%; p < 0.004) and the CTV-to-PTV volume (4-96 ml). CONCLUSIONS: Compared with population-based margins, an individualized PTV results in better organ-at-risk sparing. Online-adaptive radiotherapy further improves organ-at-risk sparing.

A population-based model to describe geometrical uncertainties in radiotherapy: applied to prostate cases.

Local motions and deformations of organs between treatment fractions introduce geometrical uncertainties into radiotherapy. These uncertainties are generally taken into account in the treatment planning by enlarging the radiation target by a margin around the clinical target volume. However, a practical method to fully include these uncertainties is still lacking. This paper proposes a model based on the principal component analysis to describe the patient-specific local probability distributions of voxel motions so that the average values and variances of the dose distribution can be calculated and fully used later in inverse treatment planning. As usually only a very limited number of data for new patients is available; in this paper the analysis is extended to use population data. A basic assumption (which is justified retrospectively in this paper) is that general movements and deformations of a specific organ are similar despite variations in the shapes of the organ over the population. A proof of principle of the method for deformations of the prostate and the seminal vesicles is presented.

Dose-wall histograms and normalized dose-surface histograms for the rectum: a new method to analyze the dose distribution over the rectum in conformal radiotherapy.

PURPOSE: To develop an accurate method to generate a dose-volume histogram (DVH) of the rectum wall, solely based on the outer contours of the rectum wall. METHODS AND MATERIALS: A mathematical model for the rectum wall is developed, incorporating the stretching of the rectum wall due to variable rectal filling and neighboring structures. The model is based on the assumption that the amount of intersected rectum wall tissue normal to the central axis of the rectum is constant. The main objective of the model is to determine the thickness of the rectum wall in each wall element. Two approaches are described, each yielding a DVH of the rectum wall, based only on the delineated outer contours of the rectum. In the first approach, the model is used to create a set of inner contours out of the axial outer contours. Both sets of contours are used to derive a dose-wall histogram (DWH) of the rectum. In the second approach, the model is used to generate a normalized 2D sampling space, which is subsequently binned into a normalized dose-surface histogram (NDSH). The model is verified using 20 sets of CT data (5 patients x 4 scans) in which both outer and inner contours of the rectum are carefully delineated. The DWHs and NDSHs are compared with DVHs of the rectum wall, which require contouring of the outer and inner surfaces of the rectum wall, and with DVHs of the total rectum (including rectal filling). The variation between DWHs, NDSHs, and DVHs is investigated using normal tissue complication probability (NTCP) calculations. RESULTS: The local wall thickness of the rectum as outlined on CT data was in conformity with the described rectum model. The amount of rectum wall tissue per unit length rectum varied considerably between patients (27%, 1 SD). In all analyzed patients, the DWHs and NDSHs corresponded well to the DVHs of the rectum wall. Much more discrepancies were observed between the DVHs of the total rectum and the DVHs of the rectum wall. CONCLUSION: The applied methods yield accurate dose distributions of the rectum wall, without delineating the inner surface of the rectum. This reduces both the workload and variations due to inaccurate delineation of the rectum wall. The DWH and NDSH are effective tools to evaluate 3D dose distributions of the rectum wall and to estimate the complication probability of the rectum in high-dose conformal radiotherapy.