Therapeutic applications of radioactive sources: from image-guided brachytherapy to radio-guided surgical resection.

It is well known nowadays that radioactivity can destroy the living cells it interacts with. It is therefore unsurprising that radioactive sources, such as iodine-125, were historically developed for treatment purposes within radiation oncology with the goal of damaging malignant cells. However, since then, new techniques have been invented that make creative use of the same radioactivity properties of these sources for medical applications. Here, we review two distinct kinds of therapeutic uses of radioactive sources with applications to prostate, cervical, and breast cancer: brachytherapy and radioactive seed localization. In brachytherapy (BT), the radioactive sources are used for internal radiation treatment. Current approaches make use of real-time image guidance, for instance by means of magnetic resonance imaging, ultrasound, computed tomography, and sometimes positron emission tomography, depending on clinical availability and cancer type. Such image-guided BT for prostate and cervical cancer presents a promising alternative and/or addition to external beam radiation treatments or surgical resections. Radioactive sources can also be used for radio-guided tumor localization during surgery, for which the example of iodine-125 seed use in breast cancer is given. Radioactive seed localization (RSL) is increasingly popular as an alternative tumor localization technique during breast cancer surgery. Advantages of applying RSL include added flexibility in the clinical scheduling logistics, an increase in tumor localization accuracy, and higher patient satisfaction; safety measures do however have to be employed. We exemply the implementation of RSL in a clinic through our experiences at the Netherlands Cancer Institute.

Achieving Highly Scalable Evolutionary Real-Valued Optimization by Exploiting Partial Evaluations.

It is known that to achieve efficient scalability of an Evolutionary Algorithm (EA), dependencies (also known as linkage) must be properly taken into account during variation. In a Gray-Box Optimization (GBO) setting, exploiting prior knowledge regarding these dependencies can greatly benefit optimization. We specifically consider the setting where partial evaluations are possible, meaning that the partial modification of a solution can be efficiently evaluated. Such problems are potentially very difficult, for example, non-separable, multimodal, and multiobjective. The Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) can effectively exploit partial evaluations, leading to a substantial improvement in performance and scalability. GOMEA was recently shown to be extendable to real-valued optimization through a combination with the real-valued estimation of distribution algorithm AMaLGaM. In this article, we definitively introduce the Real-Valued GOMEA (RV-GOMEA), and introduce a new variant, constructed by combining GOMEA with what is arguably the best-known real-valued EA, the Covariance Matrix Adaptation Evolution Strategies (CMA-ES). Both variants of GOMEA are compared to L-BFGS and the Limited Memory CMA-ES (LM-CMA-ES). We show that both variants of RV-GOMEA achieve excellent performance and scalability in a GBO setting, which can be orders of magnitude better than that of EAs unable to efficiently exploit the GBO setting.

Reduced inter-observer and intra-observer delineation variation in esophageal cancer radiotherapy by use of fiducial markers.

Objective: Delineation variation of esophageal tumors remains a large source of geometric uncertainty. In the present study, we investigated the inter- and intra-observer variation in esophageal gross tumor volume (GTV) delineation and the impact of endoscopically implanted fiducial markers on these variations. Material/Methods: Ten esophageal cancer patients with at least two markers endoscopically implanted at the cranial and caudal tumor borders and visible on the planning computed tomography (pCT) were included in this study. Five dedicated gastrointestinal radiation oncologists independently delineated GTVs on the pCT without markers and with markers. The GTV was first delineated on pCTs where markers were digitally removed and next on the original pCT with markers. Both delineation series were executed twice to determine intra-observer variation. For both the inter- and intra-observer analyses, the generalized conformity index (CIgen), and the standard deviation (SD) of the distances between delineated surfaces (i.e., overall, longitudinal, and radial SDs) were calculated. Linear mixed-effect models were used to compare the without and with markers series (α = 0.05). Results: Both the inter- and intra-observer CIgen were significantly larger in the series with markers than in the series without markers (p < .001). For the series without markers vs. with markers, the inter-observer overall SD, longitudinal SD, and radial SD was 0.63 cm vs. 0.22 cm, 1.44 cm vs. 0.42 cm, and 0.26 cm vs. 0.18 cm, respectively (p < .05); moreover, the intra-observer overall SD, longitudinal SD, and radial SD was 0.45 cm vs. 0.26 cm, 1.10 cm vs. 0.41 cm, and 0.22 cm vs. 0.15 cm, respectively (p < .05). Conclusion: The presence of markers at the cranial and caudal tumor borders significantly reduced both inter- and intra-observer GTV delineation variation, especially in the longitudinal direction. Our results endorse the use of markers in GTV delineation for esophageal cancer patients.

Sensitivity of dose-volume indices to computation settings in high-dose-rate prostate brachytherapy treatment plan evaluation.

PURPOSE: To investigate the variation in computed dose-volume (DV) indices for high-dose-rate (HDR) prostate brachytherapy that can result from typical differences in computation settings in treatment planning systems (TPSs). METHODS: Five factors were taken into account: number of dose-calculation points, radioactive source description, interpolation between delineated contours, intersections between delineated organ contours, and organ shape at the top and bottom contour using either full or partial slice thickness. Using in-house developed software, the DV indices of the treatment plans of 26 patients were calculated with different settings, and compared to a baseline setting that closely followed the default settings of the TPS used in our medical center. Studied organs were prostate and seminal vesicles, denoted as targets, and bladder, rectum, and urethra, denoted as organs at risk (OARs), which were delineated on MRI scans with a 3.3 mm slice thickness. RESULTS: When sampling a fixed number of points in each organ, in order to achieve a width of the 95% confidence interval over all patients of the DV indices of 1% or less, only 32,000 points had to be sampled per target, but 256,000 points had to be sampled per OAR. For the remaining factors, DV indices changed up to 0.4% for rectum, 1.3% for urethra, and 2.6% for prostate. DV indices of the bladder changed especially if the high-dose-region was (partly) located at the most caudal contour, up to 8.5%, and DV indices of the vesicles changed especially if there were few delineated contours, up to 9.8%, both due to the use of full slice thickness for the top and bottom contour. CONCLUSIONS: The values of DV indices used in prostate HDR brachytherapy treatment planning are influenced by the computation settings in a TPS, especially at the most caudal part of the bladder, as well as in the seminal vesicles.

The effectiveness of 4DCT in children and adults: A pooled analysis.

BACKGROUND: While four-dimensional computed tomography (4DCT) is extensively used in adults, reluctance remains to use 4DCT in children. Day-to-day (interfractional) variability and irregular respiration (intrafractional variability) have shown to be limiting factors of 4DCT effectiveness in adults. In order to evaluate 4DCT applicability in children, the purpose of this study is to quantify inter- and intrafractional variability of respiratory motion in children and adults. The pooled analysis enables a solid comparison to reveal if 4DCT application for planning purposes in children could be valid. METHODS/MATERIALS: We retrospectively included 90 patients (45 children and 45 adults), for whom the diaphragm was visible on abdominal/thoracic free-breathing cone beam CTs (480 pediatric, 524 adult CBCTs). For each CBCT, the cranial-caudal position of end-exhale and end-inhale positions of the right diaphragm dome were manually selected in the projection images. The difference in position between both phases defines the amplitude. Cycle time equaled inspiratory plus expiratory time. We analyzed the variability of the inter- and intrafractional respiratory-induced diaphragm motion. RESULTS: Ranges of respiratory motion characteristics were large in both children and adults (amplitude: 4-17 vs 5-24 mm, cycle time 2.1-3.9 vs 2.7-6.5 s). The mean amplitude was slightly smaller in children than in adults (10.7 vs 12.3 mm; P = 0.06). Interfractional amplitude variability was statistically significantly smaller in children than in adults (1.4 vs 2.2 mm; P = 0.00). Mean cycle time was statistically significantly shorter in children (2.9 vs 3.6 s; P = 0.00). Additionally, intrafractional cycle time variability was statistically significantly smaller in children (0.5 vs 0.7 s; P = 0.00). CONCLUSIONS: Overall variability is smaller in children than in adults, indicating that respiratory motion is more regular in children than in adults. This implies that a single pretreatment 4DCT could be a good representation of daily respiratory motion in children and will be at least equally beneficial for planning purposes as it is in adults.

How do patient characteristics and anatomical features correlate to accuracy of organ dose reconstruction for Wilms' tumor radiation treatment plans when using a surrogate patient's CT scan?

In retrospective radiation treatment (RT) dosimetry, a surrogate anatomy is often used for patients without 3D CT. To gain insight in what the crucial aspects in a surrogate anatomy are to enable accurate dose reconstruction, we investigated the relation of patient characteristics and internal anatomical features with deviations in reconstructed organ dose using surrogate patient's CT scans. Abdominal CT scans of 35 childhood cancer patients (age: 2.1-5.6 yr; 17 boys, 18 girls) undergoing RT during 2004-2016 were included. Based on whether an intact right or left kidney is present in the CT scan, two groups were formed each containing 24 patients. From each group, four CTs associated with Wilms' tumor RT plans with an anterior-posterior-posterior-anterior field setup were selected as references. For each reference, a 2D digitally reconstructed radiograph was computed from the reference CT to simulate a 2D radiographic image and dose reconstruction was performed on the other CTs in the respective group. Deviations in organ mean dose (DEmean) of the reconstructions versus the references were calculated, as were deviations in patient characteristics (i.e. age, height, weight) and in anatomical features including organ volume, location (in 3D), and spatial overlaps. Per reference, the Pearson's correlation coefficient between deviations in DEmean and patient characteristics/features were studied. Deviation in organ locations and DEmean for the liver, spleen, and right kidney were moderately correlated (R2 > 0.5) for 8/8, 5/8, and 3/4 reference plans, respectively. Deviations in organ volume or spatial overlap and DEmean for the right and left kidney were weakly correlated (0.3 < R2 < 0.5) in 4/4 and 1/4 reference plans. No correlations (R2 < 0.3) were found between deviations in age or height and DEmean. Therefore, the performance of organ dose reconstruction using surrogate patients' CT scans is primarily related to deviation in organ location, followed by volume and spatial overlap. Further, results were plan dependent.

Density override in treatment planning to mitigate the dosimetric effect induced by gastrointestinal gas in esophageal cancer radiation therapy.

PURPOSE: To investigate the dosimetric effect of variable gas volume in esophageal cancer radiation therapy (RT) and whether a density override (DO) in treatment planning can effectively mitigate this dosimetric effect. MATERIAL AND METHODS: Nine patients with gastrointestinal gas pockets in the planning computed tomography (pCT) were retrospectively included. Per patient, the intensity-modulated RT (IMRT) and volumetric-modulated arc therapy (VMAT) plans associated with no DO, DO = 0.5, and DO = 1 in the gas pockets were made. Initial and follow-up gas volumes were assessed from the pCTs and cone-beam CTs (CBCTs), respectively. Fractional CTs were created based on the pCT and CBCTs to calculate the fractional doses using all six plans. We then investigated for all six plans the correlation between the gas volume difference (relative to initial gas volume) and the dose difference (relative to planned dose). We also calculated and compared the accumulated dose by summing the fractional doses using two strategies: single-plan strategy (i.e. using each of the six plans separately) and plan-selection strategy (i.e. selecting one of the three plans depending on the fractional gas volume for IMRT and VMAT planning separately). RESULTS: The dose difference was approximately linearly correlated to the gas volume difference. Underdoses of >3.5% and overdoses of >7% were found for gas volume decreases >160 mL/330 mL and increases >260 mL/370 mL for IMRT/VMAT planning, respectively. Moreover, for most patients, the single-plan strategy with the use of DO = 0.5 resulted in neither undesired underdose nor much overdose. The plan-selection strategy, however, can always ensure sufficient target coverage and minimize high dose regions to the most extent. CONCLUSIONS: The variation in gas volume during the treatment course can result in clinically undesired underdose or overdose. The DO-based plan-selection strategy can effectively mitigate the gas-induced underdose and minimize the overdose for esophageal cancer RT.

Interfractional renal and diaphragmatic position variation during radiotherapy in children and adults: is there a difference?

BACKGROUND: Pediatric safety margins are generally based on data from adult studies; however, adult-based margins might be too large for children. The aim of this study was to quantify and compare interfractional organ position variation in children and adults. MATERIAL AND METHODS: For 35 children and 35 adults treated with thoracic/abdominal irradiation, 850 (range 5-30 per patient) retrospectively collected cone beam CT images were registered to the reference CT that was used for radiation treatment planning purposes. Renal position variation was assessed in three orthogonal directions and summarized as 3D vector lengths. Diaphragmatic position variation was assessed in the cranio-caudal (CC) direction only. We calculated means and SDs to estimate group systematic (Σ) and random errors (σ) of organ position variation. Finally, we investigated possible correlations between organ position variation and patients' height. RESULTS: Interfractional organ position variation was different in children and adults. Median 3D right and left kidney vector lengths were significantly smaller in children than in adults (2.8, 2.9 mm vs. 5.6, 5.2 mm, respectively; p < .05). Generally, the pediatric Σ and σ were significantly smaller than in adults (p < .007). Overall and within both subgroups, organ position variation and patients' height were only negligibly correlated. CONCLUSIONS: Interfractional renal and diaphragmatic position variation in children is smaller than in adults indicating that pediatric margins should be defined differently from adult margins. Underlying mechanisms and other components of geometrical uncertainties need further investigation to explain differences and to appropriately define pediatric safety margins.

Endoscopy/EUS-guided fiducial marker placement in patients with esophageal cancer: a comparative analysis of 3 types of markers.

BACKGROUND: Markers placed at the borders of esophageal tumors are potentially useful to facilitate radiotherapy (RT) target delineation, which offers the possibility of image-guided RT. OBJECTIVE: To evaluate and compare the feasibility and technical benefit of endoscopy/EUS-guided marker placement of 3 different types of markers in patients with esophageal cancer referred for RT. DESIGN: Prospective, single-center, feasibility and comparative study. SETTING: Tertiary-care medical center. PATIENTS: Thirty patients with esophageal cancer who were referred for RT. INTERVENTIONS: Patients underwent endoscopy/EUS-guided implantation of 1 type of marker. A solid gold marker (SM) with fixed dimensions, a flexible coil-shaped gold marker (FM) with hand-cut length (2-10 mm), and a radiopaque hydrogel marker (HG) were used. Technical feasibility and adverse events were registered. CT scans and cone-beam CT scans (CBCT) acquired during RT were analyzed to determine and compare the visibility and continuous clear visibility of the implanted markers. MAIN OUTCOME MEASUREMENTS: Technical feasibility, technical benefit, and adverse events of 3 types of markers. RESULTS: A total of 101 markers were placed in 30 patients. Implantation was technically feasible in all patients without grade 3 to 4 adverse events. Two patients with asymptomatic mediastinitis and one with asymptomatic pneumothorax were seen. Visibility on CT scan of all 3 types of implanted markers was adequate for target delineation. Eighty percent of FMs remained continuously visible over the treatment period on CBCT, significantly better than SMs (63%) and HGs (11%) (P = .015). When we selected FMs ≥5 mm, 90.5% remained visible on CBCT between implantation and the end of RT. LIMITATIONS: Single-center, nonrandomized design. CONCLUSION: Endoscopy/EUS-guided fiducial marker placement for esophageal cancer is both safe and feasible and can be used for target volume delineation purposes on CT. Our results imply a significant advantage of FMs over SMs and HGs, regarding visibility and continuous clear visibility over the treatment period. ( CLINICAL TRIAL REGISTRATION NUMBER: NTR4724.).

Keeping your best options open with AI-based treatment planning in prostate and cervix brachytherapy.

PURPOSE: Without a clear definition of an optimal treatment plan, no optimization model can be perfect. Therefore, instead of automatically finding a single "optimal" plan, finding multiple, yet different near-optimal plans, can be an insightful approach to support radiation oncologists in finding the plan they are looking for. METHODS AND MATERIALS: BRIGHT is a flexible AI-based optimization method for brachytherapy treatment planning that has already been shown capable of finding high-quality plans that trade-off target volume coverage and healthy tissue sparing. We leverage the flexibility of BRIGHT to find plans with similar dose-volume criteria, yet different dose distributions. We further describe extensions that facilitate fast plan adaptation should planning aims need to be adjusted, and straightforwardly allow incorporating hospital-specific aims besides standard protocols. RESULTS: Results are obtained for prostate (n = 12) and cervix brachytherapy (n = 36). We demonstrate the possible differences in dose distribution for optimized plans with equal dose-volume criteria. We furthermore demonstrate that adding hospital-specific aims enables adhering to hospital-specific practice while still being able to automatically create cervix plans that more often satisfy the EMBRACE-II protocol than clinical practice. Finally, we illustrate the feasibility of fast plan adaptation. CONCLUSIONS: Methods such as BRIGHT enable new ways to construct high-quality treatment plans for brachytherapy while offering new insights by making explicit the options one has. In particular, it becomes possible to present to radiation oncologists a manageable set of alternative plans that, from an optimization perspective are equally good, yet differ in terms of coverage-sparing trade-offs and shape of the dose distribution.

Guiding breast-conserving surgery in patients after neoadjuvant systemic therapy for breast cancer: a comparison of radioactive seed localization with the ROLL technique.

BACKGROUND: Radioguided occult lesion localization (ROLL) with technetium-99 m colloid (ROLL-(99m)Tc) is commonly used to perform breast-conserving surgery in patients with nonpalpable breast tumors. Radioactive seed localization is a relatively new technique that localizes the tumor with a radioactive iodine-125 ((125)I) seed. The feasibility and outcome of these techniques after neoadjuvant systemic treatment has not been widely investigated. METHODS: All patients treated with neoadjuvant systemic treatment between 2007 and 2010 in the Netherlands Cancer Institute who underwent breast-conserving surgery with the ROLL-(99m)Tc technique (n = 83) or with (125)I seed localization (n = 71) were analyzed. The weight of the resected specimen, the margins, and the percentage of patients requiring a second surgical intervention as a result of positive margins were assessed. RESULTS: Patient and tumor characteristics and systemic treatment regimens were comparable between both groups. The median weight of the resected specimen (53 vs. 48 g), the median smallest margin (3.5 vs. 3.0 mm), and the risk for additional surgery for incomplete resections (7 vs. 8 %) did not differ significantly between patients treated with the ROLL-(99m)Tc technique and (125)I seed localization. CONCLUSIONS: The ROLL-(99m)Tc technique and (125)I seed localization demonstrate comparable results when used to perform breast-conserving surgery after neoadjuvant systemic treatment. Because (125)I seed localization does not require additional radiological localization shortly before surgery, it simplifies surgery scheduling. Therefore, we prefer (125)I seed localization to perform breast-conserving surgery after neoadjuvant systemic treatment.

Automatic landmark correspondence detection in medical images with an application to deformable image registration.

Purpose: Deformable image registration (DIR) can benefit from additional guidance using corresponding landmarks in the images. However, the benefits thereof are largely understudied, especially due to the lack of automatic landmark detection methods for three-dimensional (3D) medical images. Approach: We present a deep convolutional neural network (DCNN), called DCNN-Match, that learns to predict landmark correspondences in 3D images in a self-supervised manner. We trained DCNN-Match on pairs of computed tomography (CT) scans containing simulated deformations. We explored five variants of DCNN-Match that use different loss functions and assessed their effect on the spatial density of predicted landmarks and the associated matching errors. We also tested DCNN-Match variants in combination with the open-source registration software Elastix to assess the impact of predicted landmarks in providing additional guidance to DIR. Results: We tested our approach on lower abdominal CT scans from cervical cancer patients: 121 pairs containing simulated deformations and 11 pairs demonstrating clinical deformations. The results showed significant improvement in DIR performance when landmark correspondences predicted by DCNN-Match were used in the case of simulated ( p = 0 e 0 ) as well as clinical deformations ( p = 0.030 ). We also observed that the spatial density of the automatic landmarks with respect to the underlying deformation affect the extent of improvement in DIR. Finally, DCNN-Match was found to generalize to magnetic resonance imaging scans without requiring retraining, indicating easy applicability to other datasets. Conclusions: DCNN-match learns to predict landmark correspondences in 3D medical images in a self-supervised manner, which can improve DIR performance.

Radiation-Induced Retinopathy and Optic Neuropathy after Radiation Therapy for Brain, Head, and Neck Tumors: A Systematic Review.

BACKGROUND: Patients with brain, head, and neck tumors experience a decline in their quality of life due to radiation retinopathy and optic neuropathy. Little is known about the dose-response relationship and patient characteristics. We aimed to systematically review the prevalence of radiation retinopathy and optic neuropathy. METHOD: The primary outcome was the pooled prevalence of radiation retinopathy and optic neuropathy. The secondary outcome included the effect of the total radiation dose prescribed for the tumor according to the patient's characteristics. Furthermore, we aimed to evaluate the radiation dose parameters for organs at risk of radiation retinopathy and optic neuropathy. RESULTS: The pooled prevalence was 3.8%. No retinopathy was reported for the tumor's prescribed dose of <50 Gy. Optic neuropathy was more prevalent for a prescribed dose of >50 Gy than <50 Gy. We observed a higher prevalence rate for retinopathy (6.0%) than optic neuropathy (2.0%). Insufficient data on the dose for organs at risk were reported. CONCLUSION: The prevalence of radiation retinopathy was higher compared to optic neuropathy. This review emphasizes the need for future studies considering retinopathy and optic neuropathy as primary objective parameters.

Towards artificial intelligence-based automated treatment planning in clinical practice: A prospective study of the first clinical experiences in high-dose-rate prostate brachytherapy.

PURPOSE: This prospective study evaluates our first clinical experiences with the novel ``BRachytherapy via artificial Intelligent GOMEA-Heuristic based Treatment planning'' (BRIGHT) applied to high-dose-rate prostate brachytherapy. METHODS AND MATERIALS: Between March 2020 and October 2021, 14 prostate cancer patients were treated in our center with a 15Gy HDR-brachytherapy boost. BRIGHT was used for bi-objective treatment plan optimization and selection of the most desirable plans from a coverage-sparing trade-off curve. Selected BRIGHT plans were imported into the commercial treatment planning system Oncentra Brachy . In Oncentra Brachy a dose distribution comparison was performed for clinical plan choice, followed by manual fine-tuning of the preferred BRIGHT plan when deemed necessary. The reasons for plan selection, clinical plan choice, and fine-tuning, as well as process speed were monitored. For each patient, the dose-volume parameters of the (fine-tuned) clinical plan were evaluated. RESULTS: In all patients, BRIGHT provided solutions satisfying all protocol values for coverage and sparing. In four patients not all dose-volume criteria of the clinical plan were satisfied after manual fine-tuning. Detailed information on tumour coverage, dose-distribution, dwell time pattern, and insight provided by the patient-specific trade-off curve, were used for clinical plan choice. Median time spent on treatment planning was 42 min, consisting of 16 min plan optimization and selection, and 26 min undesirable process steps. CONCLUSIONS: BRIGHT is implemented in our clinic and provides automated prostate high-dose-rate brachytherapy planning with trade-off based plan selection. Based on our experience, additional optimization aims need to be implemented to further improve direct clinical applicability of treatment plans and process efficiency.

Interactive Education on Sleep Hygiene with a Social Robot at a Pediatric Oncology Outpatient Clinic: Feasibility, Experiences, and Preliminary Effectiveness.

OBJECTIVES: Children with cancer often experience sleep problems, which are associated with many negative physical and psychological health outcomes, as well as with a lower quality of life. Therefore, interventions are strongly required to improve sleep in this population. We evaluated interactive education with respect to sleep hygiene with a social robot at a pediatric oncology outpatient clinic regarding the feasibility, experiences, and preliminary effectiveness. METHODS: Researchers approached children (8 to 12 years old) who were receiving anticancer treatment and who were visiting the outpatient clinic with their parents during the two-week study period. The researchers completed observation forms regarding feasibility, and parents completed the Children's Sleep Hygiene Scale before and two weeks after the educational regimen. The experiences of children and parents were evaluated in semi-structured interviews. We analyzed open answers by labeling each answer with a topic reflecting the content and collapsed these topics into categories. We used descriptive statistics to describe the feasibility and experiences, and a dependent-samples t-test to evaluate the preliminary effectiveness. RESULTS: Twenty-eight families participated (58% response rate) and all interactions with the robot were completed. The children and parents reported that they learned something new (75% and 50%, respectively), that they wanted to learn from the robot more often (83% and 75%, respectively), and that they applied the sleeping tips from the robot afterwards at home (54%). Regarding the preliminary effectiveness, children showed a statistically significant improvement in their sleep hygiene (p = 0.047, d = 0.39). CONCLUSIONS: Providing an educational regimen on sleep hygiene in a novel, interactive way by using a social robot at the outpatient clinic seemed feasible, and the children and parents mostly exhibited positive reactions. We found preliminary evidence that the sleep hygiene of children with cancer improved.

Validation and Comparison of Radiograph-Based Organ Dose Reconstruction Approaches for Wilms Tumor Radiation Treatment Plans.

Purpose: Our purpose was to validate and compare the performance of 4 organ dose reconstruction approaches for historical radiation treatment planning based on 2-dimensional radiographs. Methods and Materials: We considered 10 patients with Wilms tumor with planning computed tomography images for whom we developed typical historic Wilms tumor radiation treatment plans, using anteroposterior and posteroanterior parallel-opposed 6 MV flank fields, normalized to 14.4 Gy. Two plans were created for each patient, with and without corner blocking. Regions of interest (lungs, heart, nipples, liver, spleen, contralateral kidney, and spinal cord) were delineated, and dose-volume metrics including organ mean and minimum dose (Dmean and Dmin) were computed as the reference baseline for comparison. Dosimetry for the 20 plans was then independently reconstructed using 4 different approaches. Three approaches involved surrogate anatomy, among which 2 used demographic-matching criteria for phantom selection/building, and 1 used machine learning. The fourth approach was also machine learning-based, but used no surrogate anatomies. Absolute differences in organ dose-volume metrics between the reconstructed and the reference values were calculated. Results: For Dmean and Dmin (average and minimum point dose) all 4 dose reconstruction approaches performed within 10% of the prescribed dose (≤1.4 Gy). The machine learning-based approaches showed a slight advantage for several of the considered regions of interest. For Dmax (maximum point dose), the absolute differences were much higher, that is, exceeding 14% (2 Gy), with the poorest agreement observed for near-beam and out-of-beam organs for all approaches. Conclusions: The studied approaches give comparable dose reconstruction results, and the choice of approach for cohort dosimetry for late effects studies should still be largely driven by the available resources (data, time, expertise, and funding).

Radioactive seed localization of breast lesions: an adequate localization method without seed migration.

Preoperative localization is important to optimize the surgical treatment of breast lesions, especially in nonpalpable lesions. Radioactive seed localization (RSL) using iodine-125 is a relatively new approach. To provide accurate guidance to surgery, it is important that the seeds do not migrate after placement. The aim of this study was to assess short-term and long-term seed migration after RSL of breast lesions. In 45 patients, 48 RSL procedures were performed under ultrasound or stereotactic guidance. In the first 12 patients, the lesion was localized with two markers: an iodine-125 seed and a reference marker. In 33 patients, 36 RSL procedures were performed using a single iodine-125 seed. All patients received control mammograms after seed placement and prior to surgery. In the patients with two markers, migration was defined as the difference in the largest distance between the markers observed in the mammograms. For single-marked lesions, migration was assessed by comparing distances between anatomical landmarks in the mammograms. RSL was successful in all patients. Seeds were in-situ for 59.5 days on average (3-136 days). The detection rate during surgery was 100%. Overall, an average seed migration of 0.9 mm (standard deviation 1.0 mm) was observed. Neither differences in lesion type, nor days in situ, type of surgery or radiologic localization method were found to have impact on seed migration. RSL is an accurate preoperative localization method for breast lesions with negligible seed migration, independent of time in-situ.

Robust optimization for HDR prostate brachytherapy applied to organ reconstruction uncertainty.

PURPOSE: Recently, we introduced a bi-objective optimization approach based on dose-volume indices to automatically create clinically good HDR prostate brachytherapy plans. To calculate dose-volume indices, a reconstruction algorithm is used to determine the 3D organ shape from 2D contours, inevitably containing settings that influence the result. We augment the optimization approach to quickly find plans that are robust to differences in 3D reconstruction. METHODS: Studied reconstruction settings were: interpolation between delineated organ contours, overlap between contours, and organ shape at the top and bottom contour. Two options for each setting yields 8 possible 3D organ reconstructions per patient, over which the robust model defines minimax optimization. For the original model, settings were based on our treatment planning system. Both models were tested on data of 26 patients and compared by re-evaluating selected optimized plans both in the original model (1 organ reconstruction, the difference determines the cost), and in the robust model (8 organ reconstructions, the difference determines the benefit). RESULTS: Robust optimization increased the run time from 3 to 6 min. The median cost for robust optimization as observed in the original model was -0.25% in the dose-volume indices with a range of [-0.01%, -1.03%]. The median benefit of robust optimization as observed in the robust model was 0.93% with a range of [0.19%, 4.16%]. For 4 patients, selected plans that appeared good when optimized in the original model, violated the clinical protocol with more than 1% when considering different settings. This was not the case for robustly optimized plans. CONCLUSIONS: Plans of high quality, irrespective of 3D organ reconstruction settings, can be obtained using our robust optimization approach. With its limited effect on total runtime, our approach therefore offers a way to account for dosimetry uncertainties that result from choices in organ reconstruction settings that is viable in clinical practice.

On the feasibility of MRI-guided navigation to demarcate breast cancer for breast-conserving surgery.

PURPOSE: The aim of this study was to investigate the feasibility of image-guided navigation approaches to demarcate breast cancer on the basis of preacquired magnetic resonance (MR) imaging in supine patient orientation. METHODS: Strategies were examined to minimize the uncertainty in the instrument-tip position, based on the hypothesis that the release of instrument pressure returns the breast tissue to its predeformed state. For this purpose, four sources of uncertainty were taken into account: (1) U(ligaments): Uncertainty in the reproducibility of the internal mammary gland geometry during repeat patient setup in supine orientation; (2) U(r_breathing): Residual uncertainty in registration of the breast after compensation for breathing motion using an external marker; (3) U(reconstruction): Uncertainty in the reconstructed location of the tip of the needle using an optical image-navigation system (phantom experiments, n = 50); and (4) U(deformation): Uncertainty in displacement of breast tumors due to needle-induced tissue deformations (patients, n = 21). A Monte Carlo study was performed to establish the 95% confidence interval (CI) of the combined uncertainties. This region of uncertainty was subsequently visualized around the reconstructed needle tip as an additional navigational aid in the preacquired MR images. Validation of the system was performed in five healthy volunteers (localization of skin markers only) and in two patients. In the patients, the navigation system was used to monitor ultrasound-guided radioactive seed localization of breast cancer. Nearest distances between the needle tip and the tumor boundary in the ultrasound images were compared to those in the concurrently reconstructed MR images. RESULTS: Both U(reconstruction) and U(deformation) were normally distributed with 0.1 +/- 1.2 mm (mean +/- 1 SD) and 0.1 +/- 0.8 mm, respectively. Taking prior estimates for U(ligaments) (0.0 +/- 1.5 mm) and U(r_breathing) (-0.1 +/- 0.6 mm) into account, the combined impact resulted in 3.9 mm uncertainty in the position of the needle tip (95% CI) after release of pressure. The volunteer study showed a targeting accuracy comparable to that in the phantom experiments: 2.9 +/- 1.3 versus 2.7 +/- 1.1 mm, respectively. In the patient feasibility study, the deviations were within the 3.9 mm CI. CONCLUSIONS: Image-guided navigation to demarcate breast cancer on the basis of preacquired MR images in supine orientation appears feasible if patient breathing is tracked during the navigation procedure, positional uncertainty is visualized and pressure on the localization instrument is released prior to verification of its position.

Machine learning for the prediction of pseudorealistic pediatric abdominal phantoms for radiation dose reconstruction.

Purpose: Current phantoms used for the dose reconstruction of long-term childhood cancer survivors lack individualization. We design a method to predict highly individualized abdominal three-dimensional (3-D) phantoms automatically. Approach: We train machine learning (ML) models to map (2-D) patient features to 3-D organ-at-risk (OAR) metrics upon a database of 60 pediatric abdominal computed tomographies with liver and spleen segmentations. Next, we use the models in an automatic pipeline that outputs a personalized phantom given the patient's features, by assembling 3-D imaging from the database. A step to improve phantom realism (i.e., avoid OAR overlap) is included. We compare five ML algorithms, in terms of predicting OAR left-right (LR), anterior-posterior (AP), inferior-superior (IS) positions, and surface Dice-Sørensen coefficient (sDSC). Furthermore, two existing human-designed phantom construction criteria and two additional control methods are investigated for comparison. Results: Different ML algorithms result in similar test mean absolute errors: ∼ 8 mm for liver LR, IS, and spleen AP, IS; ∼ 5 mm for liver AP and spleen LR; ∼ 80 % for abdomen sDSC; and ∼ 60 % to 65% for liver and spleen sDSC. One ML algorithm (GP-GOMEA) significantly performs the best for 6/9 metrics. The control methods and the human-designed criteria in particular perform generally worse, sometimes substantially ( + 5 - mm error for spleen IS, - 10 % sDSC for liver). The automatic step to improve realism generally results in limited metric accuracy loss, but fails in one case (out of 60). Conclusion: Our ML-based pipeline leads to phantoms that are significantly and substantially more individualized than currently used human-designed criteria.