Treatment simulations with a statistical deformable motion model to evaluate margins for multiple targets in radiotherapy for high-risk prostate cancer

DiffuseRT: predicting likely anatomical deformations of patients undergoing radiotherapy

Objective. Predicting potential deformations of patients can improve radiotherapy treatment planning. Here, we introduce new deep-learning models that predict likely anatomical changes during radiotherapy for head and neck cancer patients.Approach. Denoising diffusion probabilistic models (DDPMs) were developed to generate fraction-specific anatomical changes based on a reference cone-beam CT (CBCT), the fraction number and the dose distribution delivered. Three distinct DDPMs were developed: (1) theimage modelwas trained to directly generate likely future CBCTs, (2) the deformable vector field (DVF) model was trained to generate DVFs that deform a reference CBCT and (3) thehybrid modelwas trained similarly to the DVF model, but without relying on an external deformable registration algorithm. The models were trained on 9 patients with longitudinal CBCT images (224 CBCTs) and evaluated on 5 patients (152 CBCTs).Results. The generated images mainly exhibited random positioning shifts and small anatomical changes for early fractions. For later fractions, all models predicted weight losses in accordance with the training data. The distributions of volume and position changes of the body, esophagus, and parotids generated with the image and hybrid models were more similar to the ground truth distribution than the DVF model, evident from the lower Wasserstein distance achieved with the image (0.33) and hybrid model (0.30) compared to the DVF model (0.36). Generating several images for the same fraction did not yield the expected variability since the ground truth anatomical changes were only in 76% of the fractions within the 95% bounds predicted with the best model. Using the generated images for robust optimization of simplified proton therapy plans improved the worst-case clinical target volume V95 with 7% compared to optimizing with 3 mm set-up robustness while maintaining a similar integral dose.Significance. The newly developed DDPMs generate distributions similar to the real anatomical changes and have the potential to be used for robust anatomical optimization.

Reduction of PTV margins for elective pelvic lymph nodes in online adaptive radiotherapy of prostate cancer patients

BACKGROUND

Cone beam CT (CBCT) based online adaptive radiotherapy (oART) is a new development in radiotherapy. With oART, the requirements for planning target volume (PTV) margins differ from standard therapy because motion occurs during a session. In this study, we aim to evaluate a margin reduction for locally advanced prostate patients treated with oART.

MATERIAL AND METHODS

Intrafraction motion of the elective pelvic lymph nodes was evaluated by two radiation therapists (RTTs) for 150 fractions from 10 prostate patients treated with oART. PTV margins of 3, 4 and 5 mm where added to these lymph nodes for all patients. The seven first patients were treated with 5 mm PTV margin, while the last three patients were treated with 4 mm margin. After treatment, the RTTs reviewed the verification CBCTs and evaluated whether the various PTV margins would have covered the adapted clinical target volume, scoring each fraction as approved, inconclusive or rejected. Couch shifts corresponding to the rigid prostate match between the CBCTs were analyzed with respect to the RTT evaluation.

RESULTS

The RTTs approved a 4 mm margin in 95% of the fractions, while 2% of the fractions were rejected. For a 3 mm margin, 57% of the fractions were approved, while 5% were rejected. The scoring from the two RTTs was consistent; e.g., for 3 mm, one RTT approved 58% of the fractions, while the other approved 55%. If the couch was moved less than 2 mm in any direction, 70% of the fractions were approved for a 3 mm margin, compared to 32% for shifts greater than 2 mm.

CONCLUSION

It is safe to reduce the PTV margin from 5 to 4 mm for the elective pelvic lymph nodes for prostate patients treated with oART. Further margin reductions can be motivated for patients presenting little intrafraction motion.

Probabilistic evaluation of plan quality for time-dependent anatomical deformations in head and neck cancer patients

PURPOSE

In addition to patient set-up uncertainties, anatomical deformations, e.g., weight loss, lead to time-dependent differences between the planned and delivered dose in a radiotherapy course that currently cannot easily be predicted. The aim of this study was to create time-varying prediction models to describe both the average and residual anatomical deformations.

METHODS

Weekly population-based principal component analysis models were generated from on-treatment cone-beam CT scans (CBCTs) of 30 head and neck cancer patients, with additional data of 35 patients used as a validation cohort. We simulated treatment courses accounting for a) anatomical deformations, b) set-up uncertainties and c) a combination of both. The dosimetric effects of the simulated deformations were compared to a direct dose accumulation based on deformable registration of the CBCT data.

RESULTS

Set-up uncertainties were seen to have a larger effect on the organ at risk (OAR) doses than anatomical deformations for all OARs except the larynx and the primary CTV. Distributions from simulation results were in good agreement with those of the accumulated dose.

CONCLUSIONS

We present a novel method of modelling time-varying organ deformations in head and neck cancer. The effect on the OAR doses from these deformations are smaller than the effect of set-up uncertainties for most OARs. These models can, for instance, be used to predict which patients could benefit from adaptive radiotherapy, prior to commencing treatment.

A probabilistic deep learning model of inter-fraction anatomical variations in radiotherapy

Objective. In radiotherapy, the internal movement of organs between treatment sessions causes errors in the final radiation dose delivery. To assess the need for adaptation, motion models can be used to simulate dominant motion patterns and assess anatomical robustness before delivery. Traditionally, such models are based on principal component analysis (PCA) and are either patient-specific (requiring several scans per patient) or population-based, applying the same set of deformations to all patients. We present a hybrid approach which, based on population data, allows to predict patient-specific inter-fraction variations for an individual patient.Approach. We propose a deep learning probabilistic framework that generates deformation vector fields warping a patient's planning computed tomography (CT) into possible patient-specific anatomies. This daily anatomy model (DAM) uses few random variables capturing groups of correlated movements. Given a new planning CT, DAM estimates the joint distribution over the variables, with each sample from the distribution corresponding to a different deformation. We train our model using dataset of 312 CT pairs with prostate, bladder, and rectum delineations from 38 prostate cancer patients. For 2 additional patients (22 CTs), we compute the contour overlap between real and generated images, and compare the sampled and 'ground truth' distributions of volume and center of mass changes.Results. With a DICE score of 0.86 ± 0.05 and a distance between prostate contours of 1.09 ± 0.93 mm, DAM matches and improves upon previously published PCA-based models, using as few as 8 latent variables. The overlap between distributions further indicates that DAM's sampled movements match the range and frequency of clinically observed daily changes on repeat CTs.Significance. Conditioned only on planning CT values and organ contours of a new patient without any pre-processing, DAM can accurately deformations seen during following treatment sessions, enabling anatomically robust treatment planning and robustness evaluation against inter-fraction anatomical changes.

An organ deformation model using Bayesian inference to combine population and patient-specific data

Objective.Organ deformation models have the potential to improve delivery and reduce toxicity of radiotherapy, but existing data-driven motion models are based on either patient-specific or population data. We propose to combine population and patient-specific data using a Bayesian framework. Our goal is to accurately predict individual motion patterns while using fewer scans than previous models.Approach.We have derived and evaluated two Bayesian deformation models. The models were applied retrospectively to the rectal wall from a cohort of prostate cancer patients. These patients had repeat CT scans evenly acquired throughout radiotherapy. Each model was used to create coverage probability matrices (CPMs). The spatial correlations between these estimated CPMs and the ground truth, derived from independent scans of the same patient, were calculated.Main results.Spatial correlation with ground truth were significantly higher for the Bayesian deformation models than both patient-specific and population-derived models with 1, 2 or 3 patient-specific scans as input. Statistical motion simulations indicate that this result will also hold for more than 3 scans.Significance.The improvement over previous models means that fewer scans per patient are needed to achieve accurate deformation predictions. The models have applications in robust radiotherapy planning and evaluation, among others.

An updated approach for deriving PTV margins using image guidance and deformable dose accumulation

Objective. To demonstrate an updated approach for deriving planning target volume (PTV) margins for a patient population treated with volumetric image-guided radiotherapy. Approach. The approach uses a semi-automated workflow within commercial radiotherapy applications that combines dose accumulation with the bidirectional local distance (BLD) metric. The patient cohort is divided into derivation and validation datasets. For each patient in the derivation dataset, a treatment plan is generated with a 0 mm PTV margin (the idealized treatment scenario without the influence of the standard margin). Deformable image registration enabled dose accumulation of these zero-margin plans. PTV margins are derived by using the BLD to calculate the geometric extent of underdosed regions of the clinical target volume (CTV). The PTV margin is validated by ensuring the specified CTV coverage criterion is met when the margin is applied to the validation dataset. Main results. The methodology was applied to two cohorts: 40 oropharyngeal cancer patients and 50 early-stage breast cancer patients. Ten patients from each cohort were used for validation. PTV margins derived for the oropharyngeal and early-stage breast cancer patient cohorts were 3 and 5 mm, respectively, and ensure that 95% of the prescription dose is delivered to 98% of the CTV for 90% of patients. Dose accumulation showed that the CTV coverage criterion was achieved for at least 90% of patients when the margins were applied. Significance. This methodology can be used to derive appropriate PTV margins for realistic treatment scenarios and any disease site, which will improve our understanding of patient outcomes.

Evaluating principal component analysis models for representing anatomical changes in head and neck radiotherapy

Background and purpose

Anatomical changes during radiotherapy pose a challenge to robustness of plans. Principal component analysis (PCA) is commonly used to model such changes. We propose a toolbox to evaluate how closely a given PCA model can represent actual deformations seen in the patient and highlight regions where the model struggles to capture these changes.

Materials and methods

We propose to calculate a residual error map from the difference between an actual displacement vector field (DVF) and the closest DVF that the PCA model can produce. This was done by taking the inner product of the DVF with the PCA components from the model. As a global measure of error, the 90th percentile of the residual errors (Mres90) across the whole scan was used. As proof of principle, we demonstrated this approach on both patient-specific cases and a population-based PCA in head and neck (H&N) cancer patients. These models were created using deformation data from deformable registrations between the planning computed tomography and cone-beam computed tomography (CBCTs), and were evaluated against DVFs from registrations of CBCTs not used to create the model.

Results

For our example cases, the oropharyngeal and the nasal cavity regions showed the largest local residual error, indicating the PCA models struggle to predict deformations seen in these regions. Mres90 ranged from 0.4 mm to 6.3 mm across the different models.

Conclusions

A method to quantitatively evaluate how well PCA models represent observed anatomical changes was proposed. We demonstrated our approach on H&N PCA models, but it can be applied to other sites.

Intrafractional motion models based on principal components in Magnetic Resonance guided prostate radiotherapy

Background and purpose

Devices that combine an MR-scanner with a Linac for radiotherapy, referred to as MR-Linac systems, introduce the possibility to acquire high resolution images prior and during treatment. Hence, there is a possibility to acquire individualised learning sets for motion models for each fraction and the construction of intrafractional motion models. We investigated the feasibility for a principal component analysis (PCA) based, intrafractional motion model of the male pelvic region.

Materials and methods

4D-scans of nine healthy male volunteers were utilized, FOV covering the entire pelvic region including prostate, bladder and rectum with manual segmentation of each organ at each time frame. Deformable image registration with an optical flow algorithm was performed for each subject with the first time frame as reference. PCA was performed on a subset of the resulting displacement vector fields to construct individualised motion models evaluated on the remaining fields.

Results

The registration algorithm produced accurate registration result, in general DICE overlap >0.95 across all time frames. Cumulative variance of the eigen values from the PCA showed that 50% or more of the motion is explained in the first component for all subjects. However, the size and direction for the components differed between subjects. Adding more than two components did not improve the accuracy significantly and the model was able to explain motion down to about 1 mm.

Conclusions

An individualised intrafractional male pelvic motion model is feasible. Geometric accuracy was about 1 mm based on 1–2 principal components.

Impact of prostate focused alignment on planned pelvic lymph node dose

Purpose

Prostate patients with positive lymph node margins receive an initial course of 45 Gy to the planning target volume (PTV) comprised of prostate, seminal vesicles, and lymph nodes with a 1‐cm margin. The prostate is localized via implanted fiducial markers before each fraction is delivered using portal‐imaging. However, the pelvic lymph nodes are affixed to the bony anatomy and are not mobile in concert with the prostate. The aim of this study was to determine whether a significant difference in pelvic lymph node coverage exists between planned and delivered external beam therapy treatments for these patients.

Methods

The recorded prostate motions were gathered for 19 patients; conjointly the pelvic lymph node motions were determined by manual registration of the bony anatomy in the kV‐images. The difference between the prostate and the bony anatomy coordinates was input into Eclipse as field shifts to represent the deviation in planned vs delivered pelvic lymph node coverage.

Results

Structure volume at V(100) was recorded for each patient for two structures: summed pelvic lymph nodes (LN CTV) and pelvic lymph nodes +1 cm margin (LN PTV) to express their contribution to the PTV. For the LN PTV, the average difference between the planned coverage and calculated delivered coverage was 3.5%, with a paired t‐test value of P = 0.005. Based upon bony anatomy registration, 26% of patients received less than 95% dose coverage using V(100) criteria for LN PTV. Dose value differences between the two plans at minimum were 6.96 ± 6.23 Gy, at mean were 0.54 ± 0.40 Gy, and at maximum were 0.10 ± 0.29 Gy. For the LN CTV, the average difference between the planned coverage and calculated delivered coverage was 1%, with a paired t‐test value of P = 0.53.

Conclusions

The results indicate a significant difference exists between the planned coverage and calculated delivered coverage for the LN PTV. There was no significant difference found for the LN CTV. We conclude that lymph node motion must be considered with the prostate motion when aligning patients before each fraction.

Anatomically robust proton therapy using multiple planning computed tomography scans for locally advanced prostate cancer

BACKGROUND

Proton therapy (PT) is sensitive towards anatomical changes that may occur during a treatment course. The aim of this study was to investigate if anatomically robust PT (ARPT) plans incorporating patient-specific target motion improved target coverage while still sparing normal tissues, when applied on locally advanced prostate cancer patients where pelvic irradiation is indicated.

MATERIAL AND METHODS

A planning computed tomography (CT) scan used for dose calculation and two additional CTs (acquired on different days) were used to make patient-specific targets for the ARPT plans on the eight included patients. The plans were compared to a conventional robust PT plan and a volumetric modulated arc therapy (VMAT) photon plan, which were derived from the planning CT (pCT). Worst-case robust optimisation was used for all proton plans with a setup uncertainty of 5 mm and a range uncertainty of 3.5%. Target coverage (V95% and D95%) and normal tissue doses (V5-75 Gy) were evaluated on 6-8 rCTs per patient.

RESULTS

The ARPT plans improved the prostate target coverage for the most challenging patient compared to conventional robust PT plans (20% point increase for V95% and 31 Gy increase for D95%). Across the whole cohort the estimated mean value for V95% was 97% for the ARPT plans and 95% for the conventional robust PT plans. The ARPT plans had a slight, statistically insignificant increase in normal tissue doses compared to the conventional robust proton plans. Compared to VMAT, the ARPT plans significantly reduced the normal tissue doses in the low-to-intermediate dose range.

CONCLUSIONS

While both proton plans reduced the low-to-intermediate normal tissue doses compared to VMAT, ARPT plans improved the target coverage for the most challenging patient without significantly increasing the normal tissue doses compared to conventional robust PT plans.

Spatial and dosimetric evaluation of residual distortions of prostate and seminal vesicle bed after image-guided definitive and postoperative radiotherapy of prostate cancer with endorectal balloon

Purpose

To quantify daily residual deviations from the planned geometry after image‐guided prostate radiotherapy with endorectal balloon and to evaluate their effect on the delivered dose distribution.

Methods

Daily kV‐CBCT imaging was used for online setup‐correction in six degrees of freedom (6‐dof) for 24 patients receiving definitive (12 RT_def patients) or postoperative (12 RT_postop patients) radiotherapy with endorectal balloon (overall 739 CBCTs). Residual deviations were evaluated using several spatial and dosimetric variables, including: (a) posterior Hausdorff distance HD^post (=maximum distance between planned and daily CTV contour), (b) point P_worst with largest HD^post over all fractions, (c) equivalent uniform dose using a cell survival model (EUD_SF) and the generalized EUD concept (gEUD_a with parameter a = −7 and a = −20). EUD values were determined for planned (EUDSFplan), daily (EUDSFind), and delivered dose distributions (EUDSFaccum) for plans with 6 mm (=clinical plans) and 2 mm CTV‐to‐PTV margin. Time series analyses of interfractional spatial and dosimetric deviations were conducted.

Results

Large HD^post values ≥ 12.5 mm (≥15 mm) were observed in 20/739 (5/739) fractions distributed across 7 (3) patients. Points P_worst were predominantly located at the posterior CTV boundary in the seminal vesicle region (16/24 patients, 6/7 patients with HD^post ≥ 12.5 mm). Time series analyses revealed a stationary white noise characteristic of HD^post and relative dose at P_worst. The EUD_SF difference between planned and accumulated dose distributions was < 5.4% for all 6‐mm plans. Evaluating 2‐mm plans, EUD_SF deteriorated by < 10% (<5%) in 75% (58.5%) of the patients. EUDSFaccum was well described by the median value of the EUDSFind distribution. PTV margin calculation at P_worst yielded 8.8 mm.

Conclusions

Accumulated dose distributions in prostate radiotherapy with endorectal balloon are forgiving of considerable residual distortions after 6‐dof patient setup if they are observed in a minority of fractions and the median value of EUDSFind determined per fraction stays within 95% of prescribed dose. Common PTV margin calculations are overly conservative because after online correction of translational and rotational errors only residual deformations need to be included. These results provide guidelines regarding online navigation, margin optimization, and treatment adaptation strategies.

Evaluation of an a priori scatter correction algorithm for cone-beam computed tomography based range and dose calculations in proton therapy

BACKGROUND AND PURPOSE

Scatter correction of cone-beam computed tomography (CBCT) projections may enable accurate online dose-delivery estimations in photon and proton-based radiotherapy. This study aimed to evaluate the impact of scatter correction in CBCT-based proton range/dose calculations, in scans acquired in both proton and photon gantries.

MATERIAL AND METHODS

CBCT projections of a Catphan and an Alderson phantom were acquired on both a proton and a photon gantry. The scatter corrected CBCTs (corrCBCTs) and the clinical reconstructions (stdCBCTs) were compared against CTs rigidly registered to the CBCTs (rigidCTs). The CBCTs of the Catphan phantom were segmented by materials for CT number analysis. Water equivalent path length (WEPL) maps were calculated through the Alderson phantom while proton plans optimized on the rigidCT and recalculated on all CBCTs were compared in a gamma analysis.

RESULTS

In medium and high-density materials, the corrCBCT CT numbers were much closer to those of the rigidCT than the stdCBCTs. E.g. in the 50% bone segmentations the differences were reduced from above 300 HU (with stdCBCT) to around 60-70 HU (with corrCBCT). Differences in WEPL from the rigidCT were typically well below 5 mm for the corrCBCTs, compared to well above 10 mm for the stdCBCTs with the largest deviations in the head and thorax regions. Gamma pass rates (2%/2mm) when comparing CBCT-based dose re-calculations to rigidCT calculations were improved from around 80% (with stdCBCT) to mostly above 90% (with corrCBCT).

CONCLUSION

Scatter correction leads to substantial artefact reductions, improving accuracy of CBCT-based proton range/dose calculations.

Evaluation of an Open Source Registration Package for Automatic Contour Propagation in Online Adaptive Intensity-Modulated Proton Therapy of Prostate Cancer

Objective: Our goal was to investigate the performance of an open source deformable image registration package, elastix, for fast and robust contour propagation in the context of online-adaptive intensity-modulated proton therapy (IMPT) for prostate cancer.

Methods: A planning and 7–10 repeat CT scans were available of 18 prostate cancer patients. Automatic contour propagation of repeat CT scans was performed using elastix and compared with manual delineations in terms of geometric accuracy and runtime. Dosimetric accuracy was quantified by generating IMPT plans using the propagated contours expanded with a 2 mm (prostate) and 3.5 mm margin (seminal vesicles and lymph nodes) and calculating dosimetric coverage based on the manual delineation. A coverage of V_95% ≥ 98% (at least 98% of the target volumes receive at least 95% of the prescribed dose) was considered clinically acceptable.

Results: Contour propagation runtime varied between 3 and 30 s for different registration settings. For the fastest setting, 83 in 93 (89.2%), 73 in 93 (78.5%), and 91 in 93 (97.9%) registrations yielded clinically acceptable dosimetric coverage of the prostate, seminal vesicles, and lymph nodes, respectively. For the prostate, seminal vesicles, and lymph nodes the Dice Similarity Coefficient (DSC) was 0.87 ± 0.05, 0.63 ± 0.18, and 0.89 ± 0.03 and the mean surface distance (MSD) was 1.4 ± 0.5 mm, 2.0 ± 1.2 mm, and 1.5 ± 0.4 mm, respectively.

Conclusion: With a dosimetric success rate of 78.5–97.9%, this software may facilitate online adaptive IMPT of prostate cancer using a fast, free and open implementation.

Robustness of elective lymph node target coverage with shrinking Planning Target Volume margins in external beam radiotherapy of locally advanced cervical cancer

BACKGROUND AND PURPOSE

Image-Guidance decreases set-up uncertainties, which may allow for Planning Target Volume (PTV) margins reduction. This study evaluates the robustness of the elective lymph node target coverage to translational and rotational set-up errors in combination with shrinking PTV margins and determines the gain for the Organs At Risk (OARs).

MATERIAL AND METHODS

Ten cervix cancer patients who underwent external beam radiotherapy with 45 Gy/25Fx were analysed. Daily Image-Guidance was based on bony registration of Cone Beam CT (CBCT) to planning CT (pCT) and daily couch correction (translation and yaw). On each pCT, four Volumetric Modulated Arc Therapy dose-plans were generated with PTV margins of 0, 3, 5 and 8 mm. The elective clinical target volume (CTV-E) was propagated from daily CBCTs to the pCT to evaluate daily CTV-E dose. Additional systematic translational isocenter shifts of 2 mm were simulated. D98% (dose received by 98% of the volume of interest) and D99.9% were extracted from each CTV-E for all dose-plans and scenarios. Total dose was accumulated by Dose-Volume Histogram addition. The dosimetric impact of PTV margin reduction on the OARs was evaluated through V30Gy (volume included within the 30 Gy isodose), V40Gy and body V43Gy.

RESULTS

When decreasing the PTV margin from 5 to 0 mm, bowel V30Gy was decreased by 13% (from 247 cm3 to 214 cm3), body V43Gy by 19% (from 1462 cm3 to 1188 cm3) and PTV by 39% (from 1416 to 870 cm3). The dosimetric impact of combined systematic shifts and residual rotations on the elective target with a 0 mm PTV margin was a decrease of D98% (mean ± SD) from 44.1 Gy ± 0.4 Gy to 43.7 Gy ± 0.8 Gy and a minimum of 42.4 Gy.

CONCLUSION

PTV margin reduction from 5 to 0 mm induced significant OARs dosimetric gains while elective target coverage remained robust to positioning uncertainties.

Prospective Study to Quantify Expansion Volumes Around the Involved Pelvic Lymph Nodes to Plan Simultaneous Integrated Boost in Patients With Cervical Cancer Undergoing Pelvic Intensity Modulated Radiation Therapy

PURPOSE

This study aimed to calculate the expansion margins around enlarged pelvic lymph nodes to encompass internal motion and setup errors during intensity modulated radiation therapy with simultaneous integrated boost for cervical cancer.

METHODS AND MATERIALS

Four-dimensional computed tomography scans were obtained for 19 patients with cervical cancer, and 32 fluorodeoxyglucose-avid pelvic lymph nodes were delineated in different respiratory phases to calculate respiratory displacement. Setup variations during daily treatments were estimated from on-board imaging. Descriptive statistics were used to quantify the expansion margins using Mc Kenzie and Van Herk formulas separately. An analysis of variance was used to analyze the volumetric impact of the margins.

RESULTS

Based on the McKenzie formula, an internal margin (internal target volume) of 3 mm and setup margin (planning target volume) of 5 mm was required to adequately encompass respiratory and setup uncertainties, respectively. Although the use of the Van Herk formula necessitated a single 6 mm expansion margin for all uncertainties, which resulted in a significant reduction in boost volume, inherent limitations in our methodology might pose a higher risk of target miss with such smaller margins.

CONCLUSIONS

An isotropic expansion margin of 3 mm for the internal target volume and 5 mm for the planning target volume is necessary for enlarged pelvic lymph nodes while planning intensity modulated radiation therapy with simultaneous integrated boost for cervical cancer.

Inter-fraction movements of the prostate and pelvic lymph nodes during IGRT

Objectivities

The aim of this study was to evaluate inter-fraction movements of lymph node regions that are commonly included in the pelvic clinical target volume (CTV) for high-risk prostate cancer patients. We also aimed to evaluate if the movements affect the planning target volumes.

Methods

Ten prostate cancer patients were included. The patients underwent six MRI scans, from treatment planning to near end of treatment. The CTV movements were analyzed with deformable registration technique with the CTV divided into sections. The validity of the deformable registration was assessed by comparing the results for individual lymph nodes that were possible to identify in all scans.

Results

Using repetitive MRI, measurements showed that areas inside the CTV (lymph nodes) in some extreme cases were as mobile as the prostate and not fixed to the bones. The lymph node volumes closest to the prostate did not tend to follow the prostate motion. The more cranial lymph node volumes moved less, but still independently, and they were not necessarily fixed to the pelvic bones. In 95% of the cases, the lymph node motion in the R-L direction was 2–4 mm, in the A-P direction 2–7 mm, and in the C-C direction 2–5 mm depending on the CTV section.

Conclusion

Lymph nodes and prostate were most mobile in the A-P direction, followed by the C-C and R-L directions. This movement should be taken into account when deciding the margins for the planning target volumes (PTV).

Electronic supplementary material

The online version of this article (10.1007/s13566-018-0366-3) contains supplementary material, which is available to authorized users.

Petersen P, Vogelius IR, Aznar MC. A modeling study of functional magnetic resonance imaging to individualize target definition of seminal vesicles for external beam radiotherapy

BACKGROUND

Pre-treatment magnetic resonance imaging (MRI) can give patient-specific evaluation of suspected pathologically involved volumes in the seminal vesicles (SV) in prostate cancer patients. By targeting this suspicious volume we hypothesize that radiotherapy is more efficient without introducing more toxicity. In this study we evaluate the concept of using MRI-defined target volumes in terms of tumor control probability (TCP) and rectal normal tissue complication probability (NTCP).

MATERIAL AND METHODS

Twenty-one high-risk prostate cancer patients were included. Pre-treatment CT images, T2 weighted (T2w) MRI and two multi-parametric MRI were acquired. Overlap between a suspicious volume in the SV observed on T2w images and a suspicious volume observed on either multi-parametric MRI was assumed to reflect a true malignant region (named 'MRI positive'). In addition the entire SV on the CT-scan was delineated. Three treatment plans of 2 Gy ×39 fractions were generated per patient: one covering the MRI positive volume in SV and prostate with margin of 11 mm to the MRI positive in the SV and two plans covering prostate and SV using 11 and 7 mm SV margin, respectively. All plans were prescribed the same PTV mean dose. Rectal NTCP grade ≥2 was evaluated with the Lyman-Kutcher-Burman model and TCP was estimated by a logistic model using the combined MRI positive volume in SV and prostate as region-of-interest.

RESULTS

Fourteen of twenty-one patients were classified as MRI positive, six of which had suspicious volumes in all three MRI modalities. On average TCP for the plan covering prostate and the MRI positive volume was 3% higher (up to 11%) than the two other plans which was statistically significant. The increased TCP was obtained without increasing rectal NTCP grade ≥2.

CONCLUSIONS

Using functional MRI for individualized target delineation in the SV may improve the treatment outcome in radiotherapy of prostate cancer without increasing the rectal toxicity.

Population model of bladder motion and deformation based on dominant eigenmodes and mixed-effects models in prostate cancer radiotherapy

In radiotherapy for prostate cancer irradiation of neighboring organs at risk may lead to undesirable side-effects. Given this setting, the bladder presents the largest inter-fraction shape variations hampering the computation of the actual delivered dose vs. planned dose. This paper proposes a population model, based on longitudinal data, able to estimate the probability of bladder presence during treatment, using only the planning computed tomography (CT) scan as input information. As in previously-proposed principal component analysis (PCA) population-based models, we have used the data to obtain the dominant eigenmodes that describe bladder geometric variations between fractions. However, we have used a longitudinal analysis along each mode in order to properly characterize patient's variance from the total population variance. We have proposed is a mixed-effects (ME) model in order to separate intra- and inter-patient variability, in an effort to control confounding cohort effects. Other than using PCA, bladder shapes are represented by using spherical harmonics (SPHARM) that additionally enables data compression without information lost. Based on training data from repeated CT scans, the ME model was thus implemented following dimensionality reduction by means of SPHARM and PCA. We have evaluated the model in a leave-one-out cross validation framework on the training data but also using independent data. Probability maps (PMs) were thus generated with several draws from the learnt model as predicted regions where the bladder will likely move and deform. These PMs were compared with the actual regions using metrics based on mutual information distance and misestimated voxels. The prediction was also compared with two previous population PCA-based models. The proposed model was able to reduce the uncertainties in the estimation of the probable region of bladder motion and deformation. This model can thus be used for tailoring radiotherapy treatments.

Adaptive radiotherapy strategies for pelvic tumors - a systematic review of clinical implementations

Introdution: Variation in shape, position and treatment response of both tumor and organs at risk are major challenges for accurate dose delivery in radiotherapy. Adaptive radiotherapy (ART) has been proposed to customize the treatment to these motion/response patterns of the individual patients, but increases workload and thereby challenges clinical implementation. This paper reviews strategies and workflows for clinical and in silico implemented ART for prostate, bladder, gynecological (gyne) and ano-rectal cancers.

MATERIAL AND METHODS

Initial identification of papers was based on searches in PubMed. For each tumor site, the identified papers were screened independently by two researches for selection of studies describing all processes of an ART workflow: treatment monitoring and evaluation, decision and execution of adaptations. Both brachytherapy and external beam studies were eligible for review.

RESULTS

The review consisted of 43 clinical studies and 51 in silico studies. For prostate, 1219 patients were treated with offline re-planning, mainly to adapt prostate motion relative to bony anatomy. For gyne 1155 patients were treated with online brachytherapy re-planning while 25 ano-rectal cancer patients were treated with offline re-planning, all to account for tumor regression detected by magnetic resonance imaging (MRI)/computed tomography (CT). For bladder and gyne, 161 and 64 patients, respectively, were treated with library-based online plan selection to account for target volume and shape variations. The studies reported sparing of rectum (prostate and bladder cancer), bladder (ano-rectal cancer) and bowel cavity (gyne and bladder cancer) as compared to non-ART.

CONCLUSION

Implementations of ART were dominated by offline re-planning and online brachytherapy re-planning strategies, although recently online plan selection workflows have increased with the availability of cone-beam CT. Advantageous dosimetric and outcome patterns using ART was documented by the studies of this review. Despite this, clinical implementations were scarce due to challenges in target/organ re-contouring and suboptimal patient selection in the ART workflows.

Target margins in radiotherapy of prostate cancer

We reviewed the literature on the use of margins in radiotherapy of patients with prostate cancer, focusing on different options for image guidance (IG) and technical issues. The search in PubMed database was limited to include studies that involved external beam radiotherapy of the intact prostate. Post-prostatectomy studies, brachytherapy and particle therapy were excluded. Each article was characterized according to the IG strategy used: positioning on external marks using room lasers, bone anatomy and soft tissue match, usage of fiducial markers, electromagnetic tracking and adapted delivery. A lack of uniformity in margin selection among institutions was evident from the review. In general, introduction of pre- and in-treatment IG was associated with smaller planning target volume (PTV) margins, but there was a lack of definitive experimental/clinical studies providing robust information on selection of exact PTV values. In addition, there is a lack of comparative research regarding the cost-benefit ratio of the different strategies: insertion of fiducial markers or electromagnetic transponders facilitates prostate gland localization but at a price of invasive procedure; frequent pre-treatment imaging increases patient in-room time, dose and labour; online plan adaptation should improve radiation delivery accuracy but requires fast and precise computation. Finally, optimal protocols for quality assurance procedures need to be established.

A method for evaluation of proton plan robustness towards inter-fractional motion applied to pelvic lymph node irradiation

BACKGROUND

The benefit of proton therapy may be jeopardized by dose deterioration caused by water equivalent path length (WEPL) variations. In this study we introduced a method to evaluate robustness of proton therapy with respect to inter-fractional motion and applied it to irradiation of the pelvic lymph nodes (LNs) from different beam angles. Patient- versus population-specific patterns in dose deterioration were explored.

MATERIAL AND METHODS

Patient data sets consisting of a planning computed tomography (pCT) as well as multiple repeat CT (rCT) scans for three patients were used, with target volumes and organs at risk (ORs) outlined in all scans. Single beam spot scanning proton plans were optimized for the left and right LN targets separately, across all possible beam angle configurations (5° angle intervals). Isotropic margins of 0, 3, 5 and 7 mm from the clinical target volume (CTV) to the planning target volume (PTV) were investigated. The optimized fluence maps for the pCT for each beam were applied onto all rCTs and the dose distributions were re-calculated. WEPL variation for each beam angle was computed by averaging over beams eye view WEPL distributions.

RESULTS

Similarity in deterioration patterns were found for the investigated patients, with beam angles delivering less dose to rectum, bladder and overall normal tissue identified around 40° and around 150°-160° for the left LNs, and corresponding angles for the right LNs. These angles were also associated with low values of WEPL variation.

CONCLUSION

We have established and explored a method to quantify the robustness towards inter-fractional motion of single beam proton plans treating the pelvic LNs from different beam configurations and with different CTV to PTV margins. For the patients investigated we were able to identify beam orientations that were robust to dose deterioration in the target and ORs.

Normal tissue sparing in a phase II trial on daily adaptive plan selection in radiotherapy for urinary bladder cancer

Background: Patients with urinary bladder cancer often display large changes in the shape and size of their bladder target during a course of radiotherapy (RT), making adaptive RT (ART) appealing for this tumour site. We are conducting a clinical phase II trial of daily plan selection-based ART for bladder cancer and here report dose-volume data from the first 20 patients treated in the trial.

MATERIAL AND METHODS

All patients received 60 Gy in 30 fractions to the bladder; in 13 of the patients the pelvic lymph nodes were simultaneously treated to 48 Gy. Daily patient set-up was by use of cone beam computed tomography (CBCT) guidance. The first 5 fractions were delivered with large, population-based (non-adaptive) margins. The bladder contours from the CBCTs acquired in the first 4 fractions were used to create a patient-specific library of three plans, corresponding to a small, medium and large size bladder. From fraction 6, daily online plan selection was performed, where the smallest plan covering the bladder was selected prior to each treatment delivery. A total of 600 treatment fractions in the 20 patients were evaluated.

RESULTS

Small, medium and large size plans were used almost equally often, with an average of 10, 9 and 11 fractions, respectively. The median volume ratio of the course-averaged PTV (PTV-ART) relative to the non-adaptive PTV was 0.70 (range: 0.46-0.89). A linear regression analysis showed a 183 cm(3) (CI 143-223 cm(3)) reduction in PTV-ART compared to the non-adaptive PTV (R(2) = 0.94).

CONCLUSION

Daily adaptive plan selection in RT of bladder cancer results in a considerable normal tissue sparing, of a magnitude that we expect will translate into a clinically significant reduction of the treatment-related morbidity.