Incorporation of Functional Lung Imaging Into Radiation Therapy Planning in Patients With Lung Cancer: A Systematic Review and Meta-Analysis.

Our purpose was to provide an understanding of current functional lung imaging (FLI) techniques and their potential to improve dosimetry and outcomes for patients with lung cancer receiving radiation therapy (RT). Excerpta Medica dataBASE (EMBASE), PubMed, and Cochrane Library were searched from 1990 until April 2023. Articles were included if they reported on FLI in one of: techniques, incorporation into RT planning for lung cancer, or quantification of RT-related outcomes for patients with lung cancer. Studies involving all RT modalities, including stereotactic body RT and particle therapy, were included. Meta-analyses were conducted to investigate differences in dose-function parameters between anatomic and functional RT planning techniques, as well as to investigate correlations of dose-function parameters with grade 2+ radiation pneumonitis (RP). One hundred seventy-eight studies were included in the narrative synthesis. We report on FLI modalities, dose-response quantification, functional lung (FL) definitions, FL avoidance techniques, and correlations between FL irradiation and toxicity. Meta-analysis results show that FL avoidance planning gives statistically significant absolute reductions of 3.22% to the fraction of well-ventilated lung receiving 20 Gy or more, 3.52% to the fraction of well-perfused lung receiving 20 Gy or more, 1.3 Gy to the mean dose to the well-ventilated lung, and 2.41 Gy to the mean dose to the well-perfused lung. Increases in the threshold value for defining FL are associated with decreases in functional parameters. For intensity modulated RT and volumetric modulated arc therapy, avoidance planning results in a 13% rate of grade 2+ RP, which is reduced compared with results from conventional planning cohorts. A trend of increased predictive ability for grade 2+ RP was seen in models using FL information but was not statistically significant. FLI shows promise as a method to spare FL during thoracic RT, but interventional trials related to FL avoidance planning are sparse. Such trials are critical to understanding the effect of FL avoidance planning on toxicity reduction and patient outcomes.

Deep learning-based ultrasound auto-segmentation of the prostate with brachytherapy implanted needles.

BACKGROUND: Accurate segmentation of the clinical target volume (CTV) corresponding to the prostate with or without proximal seminal vesicles is required on transrectal ultrasound (TRUS) images during prostate brachytherapy procedures. Implanted needles cause artifacts that may make this task difficult and time-consuming. Thus, previous studies have focused on the simpler problem of segmentation in the absence of needles at the cost of reduced clinical utility. PURPOSE: To use a convolutional neural network (CNN) algorithm for segmentation of the prostatic CTV in TRUS images post-needle insertion obtained from prostate brachytherapy procedures to better meet the demands of the clinical procedure. METHODS: A dataset consisting of 144 3-dimensional (3D) TRUS images with implanted metal brachytherapy needles and associated manual CTV segmentations was used for training a 2-dimensional (2D) U-Net CNN using a Dice Similarity Coefficient (DSC) loss function. These were split by patient, with 119 used for training and 25 reserved for testing. The 3D TRUS training images were resliced at radial (around the axis normal to the coronal plane) and oblique angles through the center of the 3D image, as well as axial, coronal, and sagittal planes to obtain 3689 2D TRUS images and masks for training. The network generated boundary predictions on 300 2D TRUS images obtained from reslicing each of the 25 3D TRUS images used for testing into 12 radial slices (15° apart), which were then reconstructed into 3D surfaces. Performance metrics included DSC, recall, precision, unsigned and signed volume percentage differences (VPD/sVPD), mean surface distance (MSD), and Hausdorff distance (HD). In addition, we studied whether providing algorithm-predicted boundaries to the physicians and allowing modifications increased the agreement between physicians. This was performed by providing a subset of 3D TRUS images of five patients to five physicians who segmented the CTV using clinical software and repeated this at least 1 week apart. The five physicians were given the algorithm boundary predictions and allowed to modify them, and the resulting inter- and intra-physician variability was evaluated. RESULTS: Median DSC, recall, precision, VPD, sVPD, MSD, and HD of the 3D-reconstructed algorithm segmentations were 87.2 [84.1, 88.8]%, 89.0 [86.3, 92.4]%, 86.6 [78.5, 90.8]%, 10.3 [4.5, 18.4]%, 2.0 [-4.5, 18.4]%, 1.6 [1.2, 2.0] mm, and 6.0 [5.3, 8.0] mm, respectively. Segmentation time for a set of 12 2D radial images was 2.46 [2.44, 2.48] s. With and without U-Net starting points, the intra-physician median DSCs were 97.0 [96.3, 97.8]%, and 94.4 [92.5, 95.4]% (p < 0.0001), respectively, while the inter-physician median DSCs were 94.8 [93.3, 96.8]% and 90.2 [88.7, 92.1]%, respectively (p < 0.0001). The median segmentation time for physicians, with and without U-Net-generated CTV boundaries, were 257.5 [211.8, 300.0] s and 288.0 [232.0, 333.5] s, respectively (p = 0.1034). CONCLUSIONS: Our algorithm performed at a level similar to physicians in a fraction of the time. The use of algorithm-generated boundaries as a starting point and allowing modifications reduced physician variability, although it did not significantly reduce the time compared to manual segmentations.

Is Ultrahypofractionated Whole Pelvis Radiation Therapy (WPRT) as Well Tolerated as Conventionally Fractionated WPRT in Patients With Prostate Cancer? Early Results From the HOPE Trial.

OBJECTIVE: The aim of this work was to evaluate the acute toxicity and quality-of-life (QOL) impact of ultrahypofractionated whole pelvis radiation therapy (WPRT) compared with conventional WPRT fractionation after high-dose-rate prostate brachytherapy (HDR-BT). METHODS AND MATERIALS: The HOPE trial is a phase 2, multi-institutional randomized controlled trial of men with prostate-confined disease and National Comprehensive Cancer Network unfavorable intermediate-, high-, or very-high-risk prostate cancer. Patients were randomly assigned to receive conventionally fractionated WPRT (standard arm) or ultrahypofractionated WPRT (experimental arm) in a 1:1 ratio. All patients underwent radiation therapy with 15 Gy HDR-BT boost in a single fraction followed by WPRT delivered with conventional fractionation (45 Gy in 25 daily fractions or 46 Gy in 23 fractions) or ultrahypofractionation (25 Gy in 5 fractions delivered on alternate days). Acute toxicities measured during radiation therapy and at 6 weeks posttreatment were assessed using the clinician-reported Common Terminology Criteria for Adverse Events version 5.0, and QOL was measured using the Expanded Prostate Cancer Index Composite (EPIC-50) and International Prostate Symptom Score (IPSS). RESULTS: A total of 80 patients were enrolled and treated across 3 Canadian institutions, of whom 39 and 41 patients received external radiation therapy with conventionally fractionated and ultrahypofractionated WPRT, respectively. All patients received androgen deprivation therapy except for 2 patients treated in the ultrahypofractionated arm. The baseline clinical characteristics of the 2 arms were similar, with 51 (63.8%) patients having high or very-high-risk prostate cancer disease. Treatment was well tolerated with no significant differences in the rate of acute adverse events between arms. No grade 4 adverse events or treatment-related deaths were reported. Ultrahypofractionated WPRT had a less detrimental impact on the EPIC-50 bowel total, function, and bother domain scores compared with conventional WPRT in the acute setting. By contrast, more patients treated with ultrahypofractionated WPRT reached the minimum clinical important difference on the EPIC-50 urinary domains. No significant QOL differences between arms were noted in the sexual and hormonal domains. CONCLUSIONS: Ultrahypofractionated WPRT after HDR-BT is a well-tolerated treatment strategy in the acute setting that has less detrimental impact on bowel QOL domains compared with conventional WPRT.

The use of Lutetium-177 PSMA radioligand therapy with high dose rate brachytherapy for locally recurrent prostate cancer after previous definitive radiation therapy: a randomized, single-institution, phase I/II study (ROADSTER).

BACKGROUND: Isolated local failure (ILF) can occur in patients who initially receive definitive radiation therapy for prostate cancer. Salvage therapy for ILF includes high dose rate (HDR) brachytherapy. Prostate Specific Membrane Antigen (PSMA) Positron Emission Tomography (PET) can accurately detect ILF and can exclude extraprostatic disease. Lutetium-177 PSMA Radioligand Therapy (RLT) is a novel treatment for prostate cancer that can target prostate cancer accurately, while sparing radiation dose to normal tissues. METHODS: ROADSTER is a phase I/II randomized, single-institution study. Patients with an ILF of prostate cancer after definitive initial radiation therapy are eligible. The ILF will be confirmed with biopsy, magnetic resonance imaging (MRI) and PSMA PET. Patients will be randomized between HDR brachytherapy in two fractions (a standard of care salvage treatment at our institution) (cohort 1) or one treatment of intravenous Lutetium-177 PSMA RLT, followed by one fraction of HDR brachytherapy (cohort 2). The primary endpoints for the phase I portion of the study (n = 12) will be feasibility, defined as 10 or more patients completing the study protocol within 24 months of study activation; and safety, defined as zero or one patients in cohort 2 experiencing grade 3 or higher toxicity in the first 6 months post-treatment. If feasibility and safety are achieved, the study will expand to a phase II study (n = 30 total) where preliminary efficacy data will be evaluated. Secondary endpoints include changes in prostate specific antigen levels, acute toxicity, changes in quality of life, and changes in translational biomarkers. Translational endpoints will include interrogation of blood, urine, and tissue for markers of DNA damage and immune activation with each treatment. DISCUSSION: ROADSTER explores a novel salvage therapy for ILF after primary radiotherapy with combined Lutetium-177 PSMA RLT and HDR brachytherapy. The randomized phase I/II design will provide a contemporaneous patient population treated with HDR alone to facilitate assessment of feasibility, tolerability, and biologic effects of this novel therapy. TRIAL REGISTRATION: NCT05230251 (ClinicalTrials.gov).

A power Doppler ultrasound method for improving intraoperative tip localization for visually obstructed needles in interstitial prostate brachytherapy.

PURPOSE: High-dose-rate (HDR) interstitial brachytherapy (BT) is a common treatment technique for localized intermediate to high-risk prostate cancer. Transrectal ultrasound (US) imaging is typically used for guiding needle insertion, including localization of the needle tip which is critical for treatment planning. However, image artifacts can limit needle tip visibility in standard brightness (B)-mode US, potentially leading to dose delivery that deviates from the planned dose. To improve intraoperative tip visualization in visually obstructed needles, we propose a power Doppler (PD) US method which utilizes a novel wireless mechanical oscillator, validated in phantom experiments and clinical HDR-BT cases as part of a feasibility clinical trial. METHODS: Our wireless oscillator contains a DC motor housed in a 3D printed case and is powered by rechargeable battery allowing the device to be operated by one person with no additional equipment required in the operating room. The oscillator end-piece features a cylindrical shape designed for BT applications to fit on top of the commonly used cylindrical needle mandrins. Phantom validation was completed using tissue-equivalent agar phantoms with the clinical US system and both plastic and metal needles. Our PD method was tested using a needle implant pattern matching a standard HDR-BT procedure as well as an implant pattern designed to maximize needle shadowing artifacts. Needle tip localization accuracy was assessed using the clinical method based on ideal reference needles as well as a comparison to computed tomography (CT) as a gold standard. Clinical validation was completed in five patients who underwent standard HDR-BT as part of a feasibility clinical trial. Needle tips positions were identified using B-mode US and PD US with perturbation from our wireless oscillator. RESULTS: Absolute mean ± standard deviation tip error for B-mode alone, PD alone, and B-mode combined with PD was respectively: 0.3 ± 0.3 mm, 0.6 ± 0.5 mm, and 0.4 ± 0.2 mm for the mock HDR-BT needle implant; 0.8 ± 1.7 mm, 0.4 ± 0.6 mm, and 0.3 ± 0.5 mm for the explicit shadowing implant with plastic needles; and 0.5 ± 0.2 mm, 0.5 ± 0.3 mm, and 0.6 ± 0.2 mm for the explicit shadowing implant with metal needles. The total mean absolute tip error for all five patients in the feasibility clinical trial was 0.9 ± 0.7 mm using B-mode US alone and 0.8 ± 0.5 mm when including PD US, with increased benefit observed for needles classified as visually obstructed. CONCLUSIONS: Our proposed PD needle tip localization method is easy to implement and requires no modifications or additions to the standard clinical equipment or workflow. We have demonstrated decreased tip localization error and variation for visually obstructed needles in both phantom and clinical cases, including providing the ability to visualize needles previously not visible using B-mode US alone. This method has the potential to improve needle visualization in challenging cases without burdening the clinical workflow, potentially improving treatment accuracy in HDR-BT and more broadly in any minimally invasive needle-based procedure.

Validation of a surface-based deformable MRI-3D ultrasound image registration algorithm toward clinical implementation for interstitial prostate brachytherapy.

PURPOSE: The purpose of this study was to evaluate and clinically implement a deformable surface-based magnetic resonance imaging (MRI) to three-dimensional ultrasound (US) image registration algorithm for prostate brachytherapy (BT) with the aim to reduce operator dependence and facilitate dose escalation to an MRI-defined target. METHODS AND MATERIALS: Our surface-based deformable image registration (DIR) algorithm first translates and scales to align the US- and MR-defined prostate surfaces, followed by deformation of the MR-defined prostate surface to match the US-defined prostate surface. The algorithm performance was assessed in a phantom using three deformation levels, followed by validation in three retrospective high-dose-rate BT clinical cases. For comparison, manual rigid registration and cognitive fusion by physician were also employed. Registration accuracy was assessed using the Dice similarity coefficient (DSC) and target registration error (TRE) for embedded spherical landmarks. The algorithm was then implemented intraoperatively in a prospective clinical case. RESULTS: In the phantom, our DIR algorithm demonstrated a mean DSC and TRE of 0.74 ± 0.08 and 0.94 ± 0.49 mm, respectively, significantly improving the performance compared to manual rigid registration with 0.64 ± 0.16 and 1.88 ± 1.24 mm, respectively. Clinical results demonstrated reduced variability compared to the current standard of cognitive fusion by physicians. CONCLUSIONS: We successfully validated a DIR algorithm allowing for translation of MR-defined target and organ-at-risk contours into the intraoperative environment. Prospective clinical implementation demonstrated the intraoperative feasibility of our algorithm, facilitating targeted biopsies and dose escalation to the MR-defined lesion. This method provides the potential to standardize the registration procedure between physicians, reducing operator dependence.

Functional Lung Avoidance for Individualized Radiation Therapy: Results of a Double-Masked, Randomized Controlled Trial.

PURPOSE: To determine whether functional lung avoidance based on 3He magnetic resonance imaging (MRI) improves quality of life (QOL) for patients undergoing concurrent chemoradiotherapy (CCRT) for advanced non-small cell lung cancer. METHODS AND MATERIALS: Patients with stage III non-small cell lung cancer (or oligometastatic disease treated with curative intent) undergoing CCRT with at least a 10 pack-year smoking history were eligible. Patients underwent pretreatment 3He MRI to measure lung ventilation and had 2 radiation therapy (RT) plans created before randomization: a standard plan, which did not make use of the 3He MRI, and an avoidance plan, preferentially sparing well-ventilated lung. All participants were masked to assignment except the physicist responsible for exporting the selected plan. The primary end point was patient-reported QOL measured at 3-months post-RT by the FACT-L lung cancer subscale (LCS); secondary end points included other QOL metrics, toxicity, and survival outcomes. Target accrual was 64. RESULTS: Twenty-seven patients were randomized before the trial was closed due to slower-than-expected accrual, with 11 randomized to the standard arm and 16 to the avoidance arm. Baseline patient characteristics were well-balanced. At 3 months post-RT, the mean ± SD LCS scores were 17.4 ± 2.8 versus 17.3 ± 6.1 for the standard and avoidance arms, respectively (P = .485). A clinically meaningful, prespecified decline of ≥3 points in the LCS score was observed in 50% (4/8) in the standard arm and 33% (4/12) in the avoidance arm (P = .648). Two patients in each arm developed grade ≥2 radiation pneumonitis, with no grade ≥4 toxicities. CONCLUSIONS: Although this trial did not reach full accrual, QOL scores were very similar between arms. Due to the scarcity of 3He MRI, other, more commonly available methods to measure functional lung, such as 4-dimensional computed tomography ventilation mapping, may be considered in the assessment of functional lung avoidance RT, and a larger, multicenter approach would be needed to accrue sufficient patients to test such approaches.

Effect of dataset size, image quality, and image type on deep learning-based automatic prostate segmentation in 3D ultrasound.

Three-dimensional (3D) transrectal ultrasound (TRUS) is utilized in prostate cancer diagnosis and treatment, necessitating time-consuming manual prostate segmentation. We have previously developed an automatic 3D prostate segmentation algorithm involving deep learning prediction on radially sampled 2D images followed by 3D reconstruction, trained on a large, clinically diverse dataset with variable image quality. As large clinical datasets are rare, widespread adoption of automatic segmentation could be facilitated with efficient 2D-based approaches and the development of an image quality grading method. The complete training dataset of 6761 2D images, resliced from 206 3D TRUS volumes acquired using end-fire and side-fire acquisition methods, was split to train two separate networks using either end-fire or side-fire images. Split datasets were reduced to 1000, 500, 250, and 100 2D images. For deep learning prediction, modified U-Net and U-Net++ architectures were implemented and compared using an unseen test dataset of 40 3D TRUS volumes. A 3D TRUS image quality grading scale with three factors (acquisition quality, artifact severity, and boundary visibility) was developed to assess the impact on segmentation performance. For the complete training dataset, U-Net and U-Net++ networks demonstrated equivalent performance, but when trained using split end-fire/side-fire datasets, U-Net++ significantly outperformed the U-Net. Compared to the complete training datasets, U-Net++ trained using reduced-size end-fire and side-fire datasets demonstrated equivalent performance down to 500 training images. For this dataset, image quality had no impact on segmentation performance for end-fire images but did have a significant effect for side-fire images, with boundary visibility having the largest impact. Our algorithm provided fast (<1.5 s) and accurate 3D segmentations across clinically diverse images, demonstrating generalizability and efficiency when employed on smaller datasets, supporting the potential for widespread use, even when data is scarce. The development of an image quality grading scale provides a quantitative tool for assessing segmentation performance.

Targeting prostate lesions on multiparametric MRI with HDR brachytherapy: Optimal planning margins determined using whole-mount digital histology.

PURPOSE: Multiparametric magnetic resonance imaging (mpMRI) has demonstrated the ability to localize intraprostatic lesions. It is our goal to determine how to optimally target the underlying histopathological cancer within the setting of high-dose-rate brachytherapy (HDR-BT). METHODS AND MATERIALS: Ten prostatectomy patients had pathologist-annotated mid-gland histology registered to pre-procedural mpMRI, which were interpreted by four different observers. Simulated HDR-BT plans with realistic catheter placements were generated by registering the mpMRI lesions and corresponding histology annotations to previously performed clinical HDR-BT implants. Inverse treatment planning was used to generate treatment plans that treated the entire gland to a single dose of 15 Gy, as well as focally targeted plans that aimed to escalate dose to the mpMRI lesions to 20.25 Gy. Three margins to the lesion were explored: 0 mm, 1 mm, and 2 mm. The analysis compared the dose that would have been delivered to the corresponding histologically-defined cancer with the different treatment planning techniques. RESULTS: mpMRI-targeted plans delivered a significantly higher dose to the histologically-defined cancer (p < 0.001), in comparison to the standard treatment plans. Additionally, adding a 1 mm margin resulted in significantly higher D98, and D90 to the histologically-defined cancer in comparison to the 0 mm margin targeted plans (p = 0.019 & p = 0.0026). There was no significant difference between plans using 1 mm and 2 mm margins. CONCLUSIONS: Adding a 1 mm margin to intraprostatic mpMRI lesions significantly increased the dose to histologically-defined cancer, in comparison applying no margin. No significant effect was observed by further expanding the margins.

Palliative Radiation for Advanced Central Lung Tumors With Intentional Avoidance of the Esophagus (PROACTIVE): A Phase 3 Randomized Clinical Trial.

IMPORTANCE: Palliative thoracic radiotherapy (RT) can alleviate local symptoms associated with advanced non-small cell lung cancer (NSCLC), but esophagitis is a common treatment-related adverse event. Whether esophageal-sparing intensity-modulated RT (ES-IMRT) achieves a clinically relevant reduction in esophageal symptoms remains unclear. OBJECTIVE: To examine whether ES-IMRT achieves a clinically relevant reduction in esophageal symptoms compared with standard RT. DESIGN, SETTING, AND PARTICIPANTS: Palliative Radiation for Advanced Central Lung Tumors With Intentional Avoidance of the Esophagus (PROACTIVE) is a multicenter phase 3 randomized clinical trial that enrolled patients between June 24, 2016, and March 6, 2019. Data analysis was conducted from January 23, 2020, to October 22, 2021. Patients had up to 1 year of follow-up. Ninety patients at 6 tertiary academic cancer centers who had stage III/IV NSCLC and were eligible for palliative thoracic RT (20 Gy in 5 fractions or 30 Gy in 10 fractions) were included. INTERVENTIONS: Patients were randomized (1:1) to standard RT (control arm) or ES-IMRT. Target coverage was compromised to ensure the maximum esophagus dose was no more than 80% of the RT prescription dose. MAIN OUTCOMES AND MEASURES: The primary outcome was esophageal quality of life (QOL) 2 weeks post-RT, measured by the esophageal cancer subscale (ECS) of the Functional Assessment of Cancer Therapy: Esophagus questionnaire. Higher esophageal cancer subscale scores correspond with improved QOL, with a 2- to 3-point change considered clinically meaningful. Secondary outcomes included overall survival, toxic events, and other QOL metrics. Intention-to-treat analysis was used. RESULTS: Between June 24, 2016, and March 6, 2019, 90 patients were randomized to standard RT or ES-IMRT (median age at randomization, 72.0 years [IQR, 65.6-80.3]; 50 [56%] were female). Thirty-six patients (40%) received 20 Gy and 54 (60%) received 30 Gy. For the primary end point, the mean (SD) 2-week ECS score was 50.5 (10.2) in the control arm (95% CI, 47.2-53.8) and 54.3 (7.6) in the ES-IMRT arm (95% CI, 51.9-56.7) (P = .06). Symptomatic RT-associated esophagitis occurred in 24% (n = 11) of patients in the control arm vs 2% (n = 1) in the ES-IMRT arm (P = .002). In a post hoc subgroup analysis based on the stratification factor, reduction in esophagitis was most evident in patients receiving 30 Gy (30% [n = 8] vs 0%; P = .004). Overall survival was similar with standard RT (median, 8.6; 95% CI, 5.7-15.6 months) and ES-IMRT (median, 8.7; 95% CI, 5.1-10.2 months) (P = .62). CONCLUSIONS AND RELEVANCE: In this phase 3 randomized clinical trial, ES-IMRT did not significantly improve esophageal QOL but significantly reduced the incidence of symptomatic esophagitis. Because post hoc analysis found that reduced esophagitis was most evident in patients receiving 30 Gy of RT, these findings suggest that ES-IMRT may be most beneficial when the prescription dose is higher (30 Gy). TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02752126.

Prostate specific membrane antigen positron emission tomography for lesion-directed high-dose-rate brachytherapy dose escalation.

BACKGROUND AND PURPOSE: Prostate specific membrane antigen positron emission tomography imaging (PSMA-PET) has demonstrated potential for intra-prostatic lesion localization. We leveraged our existing database of co-registered PSMA-PET imaging with cross sectional digitized pathology to model dose coverage of histologically-defined prostate cancer when tailoring brachytherapy dose escalation based on PSMA-PET imaging. MATERIALS AND METHODS: Using a previously-developed automated approach, we created segmentation volumes delineating underlying dominant intraprostatic lesions for ten men with co-registered pathology-imaging datasets. To simulate realistic high-dose-rate brachytherapy (HDR-BT) treatments, we registered the PSMA-PET-defined segmentation volumes and underlying cancer to 3D trans-rectal ultrasound images of HDR-BT cases where 15 Gray (Gy) was delivered. We applied dose/volume optimization to focally target the dominant intraprostatic lesion identified on PSMA-PET. We then compared histopathology dose for all high-grade cancer within whole-gland treatment plans versus PSMA-PET-targeted plans. Histopathology dose was analyzed for all clinically significant cancer with a Gleason score of 7or greater. RESULTS: The standard whole-gland plans achieved a median [interquartile range] D98 of 15.2 [13.8-16.4] Gy to the histologically-defined cancer, while the targeted plans achieved a significantly higher D98 of 16.5 [15.0-19.0] Gy (p = 0.007). CONCLUSION: This study is the first to use digital histology to confirm the effectiveness of PSMA-PET HDR-BT dose escalation using automatically generated contours. Based on the findings of this study, PSMA-PET lesion dose escalation can lead to increased dose to the ground truth histologically defined cancer.

Feasibility of fusing three-dimensional transabdominal and transrectal ultrasound images for comprehensive intraoperative visualization of gynecologic brachytherapy applicators.

PURPOSE: In this study, we propose combining three-dimensional (3D) transrectal ultrasound (TRUS) and 3D transabdominal ultrasound (TAUS) images of gynecologic brachytherapy applicators to leverage the advantages of each imaging perspective, providing a broader field-of-view and allowing previously obscured features to be recovered. The aim of this study was to evaluate the feasibility of fusing these 3D ultrasound (US) perspectives based on the applicator geometry in a phantom prior to clinical implementation. METHODS: In proof-of-concept experiments, 3D US images of application-specific multimodality pelvic phantoms were acquired with tandem-and-ring and tandem-and-ovoids applicators using previously validated imaging systems. Two TRUS images were acquired at different insertion depths and manually fused based on the position of the ring/ovoids to broaden the TRUS field-of-view. The phantom design allowed "abdominal thickness" to be modified to represent different body habitus and TAUS images were acquired at three thicknesses for each applicator. The merged TRUS images were then combined with TAUS images by rigidly aligning applicator components and manually refining the registration using the positions of source channels and known tandem length, as well as the ring diameter for the tandem-and-ring applicator. Combined 3D US images were manually, rigidly registered to images from a second modality (magnetic resonance (MR) imaging for the tandem-and-ring applicator and X-ray computed tomography (CT) for the tandem-and-ovoids applicator (based on applicator compatibility)) to assess alignment. Four spherical fiducials were used to calculate target registration errors (TREs), providing a metric for validating registrations, where TREs were computed using root-mean-square distances to describe the alignment of manually identified corresponding fiducials. An analysis of variance (ANOVA) was used to identify statistically significant differences (p < 0.05) between the TREs for the three abdominal thicknesses for each applicator type. As an additional indicator of geometric accuracy, the bladder was segmented in the 3D US and corresponding MR/CT images, and volumetric differences and Dice similarity coefficients (DSCs) were calculated. RESULTS: For both applicator types, the combination of 3D TRUS with 3D TAUS images allowed image information obscured by the shadowing artifacts under single imaging perspectives to be recovered. For the tandem-and-ring applicator, the mean ± one standard deviation (SD) TREs from the images with increasing thicknesses were 1.37 ± 1.35 mm, 1.84 ± 1.22 mm, and 1.60 ± 1.00 mm. Similarly, for the tandem-and-ovoids applicator, the mean ± SD TREs from the images with increasing thicknesses were 1.37 ± 0.35 mm, 1.95 ± 0.90 mm, and 1.61 ± 0.76 mm. No statistically significant difference was detected in the TREs for the three thicknesses for either applicator type. The mean volume differences for the bladder segmentations were 3.14% and 2.33% and mean DSCs were 87.8% and 87.7% for the tandem-and-ring and tandem-and-ovoids applicators, respectively. CONCLUSIONS: In this proof-of-concept study, we demonstrated the feasibility of fusing 3D TRUS and 3D TAUS images based on the geometry of tandem-and-ring and tandem-and-ovoids applicators. This represents a step toward an accessible and low-cost 3D imaging method for gynecologic brachytherapy, with the potential to extend this approach to other intracavitary configurations and hybrid applicators.

A multiobserver study investigating the effectiveness of prostatic multiparametric magnetic resonance imaging to dose escalate corresponding histologic lesions using high-dose-rate brachytherapy.

PURPOSE: Using multiparametric MRI data and the pathologic data from radical prostatectomy specimens, we simulated the treatment planning of dose-escalated high-dose-rate brachytherapy (HDR-BT) to the Multiparametric MRI dominant intraprostatic lesion (mpMRI-DIL) to compare the dose potentially delivered to the pathologically confirmed locations of the high-grade component of the cancer. METHODS AND MATERIALS: Pathologist-annotated prostatectomy midgland histology sections from 12 patients were registered to preprostatectomy mpMRI scans that were interpreted by four radiologists. To simulate realistic HDR-BT, we registered each observer's mpMRI-DILs and corresponding histology to two transrectal ultrasound images of other HDR-BT patients with a 15-Gy whole-gland prescription. We used clinical inverse planning to escalate the mpMRI-DILs to 20.25 Gy. We compared the dose that the histopathology would have received if treated with standard treatment plans to the dose mpMRI-targeting would have achieved. The histopathology was grouped as high-grade cancer (any Gleason Grade 4 or 5) and low-grade cancer (only Gleason Grade 3). RESULTS: 212 mpMRI-targeted HDR-BT plans were analyzed. For high-grade histology, the mpMRI-targeted plans achieved significantly higher median [IQR] D98 and D90 values of 18.2 [16.7-19.5] Gy and 19.4 [17.8-20.9] Gy, respectively, in comparison with the standard plans (p = 0.01 and p = 0.003). For low-grade histology, the targeted treatment plans would have resulted in a significantly higher median D90 of 17.0 [16.1-18.4] Gy in comparison with standard plans (p = 0.015); the median D98 was not significantly higher (p = 0.2). CONCLUSIONS: In this retrospective pilot study of 12 patients, mpMRI-based dose escalation led to increased dose to high-grade, but not low-grade, cancer. In our data set, different observers and mpMRI sequences had no substantial effect on dose to histologic cancer.

In-vivo lung biomechanical modeling for effective tumor motion tracking in external beam radiation therapy.

Lung cancer is the most common cause of cancer-related death in both men and women. Radiation therapy is widely used for lung cancer treatment; however, respiratory motion presents challenges that can compromise the accuracy and/or effectiveness of radiation treatment. Respiratory motion compensation using biomechanical modeling is a common approach used to address this challenge. This study focuses on the development and validation of a lung biomechanical model that can accurately estimate the motion and deformation of lung tumor. Towards this goal, treatment planning 4D-CT images of lung cancer patients were processed to develop patient-specific finite element (FE) models of the lung to predict the patients' tumor motion/deformation. The tumor motion/deformation was modeled for a full respiration cycle, as captured by the 4D-CT scans. Parameters driving the lung and tumor deformation model were found through an inverse problem formulation. The CT datasets pertaining to the inhalation phases of respiration were used for validating the model's accuracy. The volumetric Dice similarity coefficient between the actual and simulated gross tumor volumes (GTVs) of the patients calculated across respiration phases was found to range between 0.80 ± 0.03 and 0.92 ± 0.01. The average error in estimating tumor's center of mass calculated across respiration phases ranged between 0.50 ± 0.10 (mm) and 1.04 ± 0.57 (mm), indicating a reasonably good accuracy of the proposed model. The proposed model demonstrates favorable accuracy for estimating the lung tumor motion/deformation, and therefore can potentially be used in radiation therapy applications for respiratory motion compensation.

Optimization of multi-electrode implant configurations and programming for the delivery of non-ablative electric fields in intratumoral modulation therapy.

PURPOSE: Application of low intensity electric fields to interfere with tumor growth is being increasingly recognized as a promising new cancer treatment modality. Intratumoral modulation therapy (IMT) is a developing technology that uses multiple electrodes implanted within or adjacent tumor regions to deliver electric fields to treat cancer. In this study, the determination of optimal IMT parameters was cast as a mathematical optimization problem, and electrode configurations, programming, optimization, and maximum treatable tumor size were evaluated in the simplest and easiest to understand spherical tumor model. The establishment of electrode placement and programming rules to maximize electric field tumor coverage designed specifically for IMT is the first step in developing an effective IMT treatment planning system. METHODS: Finite element method electric field computer simulations for tumor models with 2 to 7 implanted electrodes were performed to quantify the electric field over time with various parameters, including number of electrodes (2 to 7), number of contacts per electrode (1 to 3), location within tumor volume, and input waveform with relative phase shift between 0 and 2π radians. Homogeneous tissue specific conductivity and dielectric values were assigned to the spherical tumor and surrounding tissue volume. In order to achieve the goal of covering the tumor volume with a uniform threshold of 1 V/cm electric field, a custom least square objective function was used to maximize the tumor volume covered by 1 V/cm time averaged field, while maximizing the electric field in voxels receiving less than this threshold. An additional term in the objective function was investigated with a weighted tissue sparing term, to minimize the field to surrounding tissues. The positions of the electrodes were also optimized to maximize target coverage with the fewest number of electrodes. The complexity of this optimization problem including its non-convexity, the presence of many local minima, and the computational load associated with these stochastic based optimizations led to the use of a custom pattern search algorithm. Optimization parameters were bounded between 0 and 2π radians for phase shift, and anywhere within the tumor volume for location. The robustness of the pattern search method was then evaluated with 50 random initial parameter values. RESULTS: The optimization algorithm was successfully implemented, and for 2 to 4 electrodes, equally spaced relative phase shifts and electrodes placed equidistant from each other was optimal. For 5 electrodes, up to 2.5 cm diameter tumors with 2.0 V, and 4.1 cm with 4.0 V could be treated with the optimal configuration of a centrally placed electrode and 4 surrounding electrodes. The use of 7 electrodes allow for 3.4 cm diameter coverage at 2.0 V and 5.5 cm at 4.0 V. The evaluation of the optimization method using 50 random initial parameter values found the method to be robust in finding the optimal solution. CONCLUSIONS: This study has established a robust optimization method for temporally optimizing electric field tumor coverage for IMT, with the adaptability to optimize a variety of parameters including geometrical and relative phase shift configurations.

Technical Note: A fast inverse direct aperture optimization algorithm for volumetric-modulated arc therapy.

PURPOSE: In a recent article, our group proposed a fast direct aperture optimization (DAO) algorithm for fixed-gantry intensity-modulated radiation therapy (IMRT) called fast inverse direct aperture optimization (FIDAO). When tested on fixed-gantry IMRT plans, we observed up to a 200-fold increase in the optimization speed. Compared to IMRT, rotational volumetric-modulated arc therapy (VMAT) is a much larger optimization problem and has many more delivery constraints. The purpose of this work is to extend and evaluate FIDAO for inverse planning of VMAT plans. METHODS: A prototype FIDAO algorithm for VMAT treatment planning was developed in MATLAB using the open-source treatment planning toolkit matRad (v2.2 dev_VMAT build). VMAT treatment plans using one 3600 arc were generated on the AAPM TG-119 phantom, as well as sample clinical liver and prostate cases. The plans were created by first performing fluence map optimization on 28° equispaced beams, followed by aperture sequencing and arc sequencing with a gantry angular sampling rate of 4°. After arc sequencing, a copy of the plan underwent DAO using the prototype FIDAO algorithm, while another copy of the plan underwent DAO using matRad's DAO method, which served as the conventional algorithm. RESULTS: Both algorithms achieved similar plan quality, although the FIDAO plans had considerably fewer hot spots in the unspecified normal tissue. The optimization time (number of iterations) for FIDAO and the conventional DAO algorithm, respectively, were: 65 s (245) vs 602 s (275) in the TG-119 phantom case; 25 s (85) vs 803 s (159) in the liver case; and 99 s (174) vs 754 s (149) in the prostate case. CONCLUSIONS: This study demonstrated promising speed enhancements in using FIDAO for the direct aperture optimization of VMAT plans.

4DCT Ventilation Map Construction Using Biomechanics-base Image Registration and Enhanced Air Segmentation.

Current lung radiation therapy (RT) treatment planning algorithms used in most centers assume homogeneous lung function. However, co-existing pulmonary dysfunctions present in many non-small cell lung cancer (NSCLC) patients, particularly smokers, cause regional variations in both perfusion and ventilation, leading to inhomogeneous lung function. An adaptive RT treatment planning that deliberately avoids highly functional lung regions can potentially reduce pulmonary toxicity and morbidity. The ventilation component of lung function can be measured using a variety of techniques. Recently, 4DCT ventilation imaging has emerged as a cost-effective and accessible method. Current 4DCT ventilation calculation methods, including the intensity-based and Jacobian models, suffer from inaccurate estimations of air volume distribution and unreliability of intensity-based image registration algorithms. In this study, we propose a novel method that utilizes a biomechanical model-based registration along with an accurate air segmentation algorithm to calculate 4DCT ventilation maps. The results show a successful development of ventilation maps using the proposed method.

Incorporating Pathology-Induced Heterogeneities in a Patient-Specific Biomechanical Model of the Lung for Accurate Tumor Motion Estimation.

Radiation therapy (RT) is an important component of treatment for lung cancer. However, the accuracy of this method can be affected by the complex respiratory motion/deformation of the target tumor during treatment. To improve the accuracy of RT, patient-specific biomechanical models of the lung have been proposed for estimating the tumor's respiratory motion/deformation. Chronic obstructive pulmonary disease (COPD) has a high incidence among lung cancer patients and is associated with heterogeneous destruction of lung parenchyma. This key heterogeneity element, however, has not been incorporated in lung biomechanical models developed in previous studies. In this work, we have developed a physiologically and patho-physiologically realistic lung biomechanical model that accounts for lung tissue heterogeneity. Four-dimensional computed tomography (4DCT) images were used to build a patient-specific finite element (FE) model of the lung. Image information was used to identify and incorporate inhomogeneities within the model. Mechanical properties of normal and diseased regions in the lung and the transpulmonary pressure driving the respiratory motion were estimated using an optimization algorithm that maximizes the similarity between the actual and simulated tumor and lung image data. Results from this proof of concept study on a lung cancer patient indicated improved accuracy of tumor motion estimation when COPD-induced lung tissue heterogeneities were incorporated in the model.

A fast inverse direct aperture optimization algorithm for intensity-modulated radiation therapy.

PURPOSE: The goal of this work was to develop and evaluate a fast inverse direct aperture optimization (FIDAO) algorithm for IMRT treatment planning and plan adaptation. METHODS: A previously proposed fluence map optimization algorithm called fast inverse dose optimization (FIDO) was extended to optimize the aperture shapes and weights of IMRT beams. FIDO is a very fast fluence map optimization algorithm for IMRT that finds the global minimum using direct matrix inversion without unphysical negative beam weights. In this study, an equivalent second-order Taylor series expansion of the FIDO objective function was used, which allowed for the objective function value and gradient vector to be computed very efficiently during direct aperture optimization, resulting in faster optimization. To evaluate the speed gained with FIDAO, a proof-of-concept algorithm was developed in MATLAB using an interior-point optimization method to solve the reformulated aperture-based FIDO problem. The FIDAO algorithm was used to optimize four step-and-shoot IMRT cases: on the AAPM TG-119 phantom as well as a liver, prostate, and head-and-neck clinical cases. Results were compared with a conventional DAO algorithm that uses the same interior-point method but using the standard formulation of the objective function and its gradient vector. RESULTS: A substantial gain in optimization speed was obtained with the prototype FIDAO algorithm compared to the conventional DAO algorithm while producing plans of similar quality. The optimization time (number of iterations) for the prototype FIDAO algorithm vs the conventional DAO algorithm was 0.3 s (17) vs 56.7 s (50); 2.0 s (28) vs 134.1 s (57); 2.5 s (26) vs 180.6 s (107); and 6.7 s (20) vs 469.4 s (482) in the TG-119 phantom, liver, prostate, and head-and-neck examples, respectively. CONCLUSIONS: A new direct aperture optimization algorithm based on FIDO was developed. For the four IMRT test cases examined, this algorithm executed approximately 70-200 times faster without compromising the IMRT plan quality.

Patient-specific calibration of cone-beam computed tomography data sets for radiotherapy dose calculations and treatment plan assessment.

PURPOSE: In this work, we propose a new method of calibrating cone beam computed tomography (CBCT) data sets for radiotherapy dose calculation and plan assessment. The motivation for this patient-specific calibration (PSC) method is to develop an efficient, robust, and accurate CBCT calibration process that is less susceptible to deformable image registration (DIR) errors. METHODS: Instead of mapping the CT numbers voxel-by-voxel with traditional DIR calibration methods, the PSC methods generates correlation plots between deformably registered planning CT and CBCT voxel values, for each image slice. A linear calibration curve specific to each slice is then obtained by least-squares fitting, and applied to the CBCT slice's voxel values. This allows each CBCT slice to be corrected using DIR without altering the patient geometry through regional DIR errors. A retrospective study was performed on 15 head-and-neck cancer patients, each having routine CBCTs and a middle-of-treatment re-planning CT (reCT). The original treatment plan was re-calculated on the patient's reCT image set (serving as the gold standard) as well as the image sets produced by voxel-to-voxel DIR, density-overriding, and the new PSC calibration methods. Dose accuracy of each calibration method was compared to the reference reCT data set using common dose-volume metrics and 3D gamma analysis. A phantom study was also performed to assess the accuracy of the DIR and PSC CBCT calibration methods compared with planning CT. RESULTS: Compared with the gold standard using reCT, the average dose metric differences were ≤ 1.1% for all three methods (PSC: -0.3%; DIR: -0.7%; density-override: -1.1%). The average gamma pass rates with thresholds 3%, 3 mm were also similar among the three techniques (PSC: 95.0%; DIR: 96.1%; density-override: 94.4%). CONCLUSIONS: An automated patient-specific calibration method was developed which yielded strong dosimetric agreement with the results obtained using a re-planning CT for head-and-neck patients.