Validation of MLC leaf open time calculation methods for PSQA in adaptive radiotherapy with tomotherapy units.

BACKGROUND: Treatment delivery safety and accuracy are essential to control the disease and protect healthy tissues in radiation therapy. For usual treatment, a phantom-based patient specific quality assurance (PSQA) is performed to verify the delivery prior to the treatment. The emergence of adaptive radiation therapy (ART) adds new complexities to PSQA. In fact, organ at risks and target volume re-contouring as well as plan re-optimization and treatment delivery are performed with the patient immobilized on the treatment couch, making phantom-based pretreatment PSQA impractical. In this case, phantomless PSQA tools based on multileaf collimator (MLC) leaf open times (LOTs) verifications provide alternative approaches for the Radixact® treatment units. However, their validity is compromised by the lack of independent and reliable methods for calculating the LOT performed by the MLC during deliveries. PURPOSE: To provide independent and reliable methods of LOT calculation for the Radixact® treatment units. METHODS: Two methods for calculating the LOTs performed by the MLC during deliveries have been implemented. The first method uses the signal recorded by the build-in detector and the second method uses the signal recorded by optical sensors mounted on the MLC. To calibrate the methods to the ground truth, in-phantom ionization chamber LOT measurements have been conducted on a Radixact® treatment unit. The methods were validated by comparing LOT calculations with in-phantom ionization chamber LOT measurements performed on two Radixact® treatment units. RESULTS: The study shows a good agreement between the two LOT calculation methods and the in-phantom ionization chamber measurements. There are no notable differences between the two methods and the same results were observed on the different treatment units. CONCLUSIONS: The two implemented methods have the potential to be part of a PSQA solution for ART in tomotherapy.

The effects of mega-voltage CT scan parameters on offline adaptive radiation therapy.

TomoTherapy involves image-guided radiation therapy (IGRT) using Mega-voltage CT (MVCT) for each treatment session. The acquired MVCT images can be utilized for the retrospective assessment of dose distribution. The TomoTherapy provides 18 distinct imaging conditions that can be selected based on a combination of algorithms, acquisition pitch, and slice interval. We investigated the accuracy of dose calculation and deformable image registration (DIR) depending on MVCT scan parameters and their effects on adaptive radiation therapy (ART). We acquired image values for density calibration tables (IVDTs) under 18 different MVCT conditions and compared them. The planning CT (pCT) was performed using a thoracic phantom, and an esophageal intensity-modulated radiation therapy (IMRT) plan was created. MVCT images of the thoracic phantom were acquired under each of the 18 conditions, and dose recalculation was performed. DIR was performed on the MVCT images acquired under each condition. The accuracy of DIR, depending on the MVCT scan parameters, was compared using the mean distance to agreement (MDA) and Dice similarity coefficient (DSC). The dose distribution calculated on the MVCT images was deformed using deformed vector fields (DVF). No significant differences were observed in the results of the 18 IVDTs. The esophageal IMRT plan also showed a small dose difference. Regarding verifying the DIR accuracy, the MDA increased, and the DSC decreased as the acquisition pitch and slice interval increased. The difference between the dose distributions after dose mapping was comparable to that before DIR. The MVCT scan parameters had little effect on ART.

A multi-center survey on adaptive radiation therapy for head and neck cancer in Malaysia.

The survey is to assess the current state of adaptive radiation therapy (ART) for head and neck (H&N) cases among radiotherapy centers in Malaysia and to identify any implementation limitations. An online questionnaire was sent to all radiotherapy centers in Malaysia. The 24-question questionnaire consists of general information about the center, ART practices, and limitations faced in implementing ART. 28 out of 36 radiotherapy centers responded, resulting in an overall response rate of 78%. About 52% of the responding centers rescanned and replanned less than 5% of their H&N patients. The majority (88.9%) of the respondents reported the use Cone Beam Computed Tomography alone or in combination with other modalities to trigger the ART process. The main reasons cited for adopting ART were weight loss, changes in the immobilization fitting, and anatomical variation. The adaptation process typically occurred during week 3 or week 4 of treatment. More than half of the respondents require three days or more from re-simulation to starting a new treatment plan. Both target and organ at risk delineation on new planning CT relied heavily on manual delineation by physicians and physicists, respectively. All centers perform patient-specific quality assurance for their new adaptive plans. Two main limitations in implementing ART are "limited financial resources or equipment" and "limitation on technical knowledge". There is a need for a common consensus to standardize the practice of ART and address these limitations to improve the implementation of ART in Malaysia.

DAART: a deep learning platform for deeply accelerated adaptive radiation therapy for lung cancer.

Purpose: The study aimed to implement a novel, deeply accelerated adaptive radiation therapy (DAART) approach for lung cancer radiotherapy (RT). Lung cancer is the most common cause of cancer-related death, and RT is the preferred medically inoperable treatment for early stage non-small cell lung cancer (NSCLC). In the current lengthy workflow, it takes a median of four weeks from diagnosis to RT treatment, which can result in complete restaging and loss of local control with delay. We implemented the DAART approach, featuring a novel deepPERFECT system, to address unwanted delays between diagnosis and treatment initiation. Materials and methods: We developed a deepPERFECT to adapt the initial diagnostic imaging to the treatment setup to allow initial RT planning and verification. We used data from 15 patients with NSCLC treated with RT to train the model and test its performance. We conducted a virtual clinical trial to evaluate the treatment quality of the proposed DAART for lung cancer radiotherapy. Results: We found that deepPERFECT predicts planning CT with a mean high-intensity fidelity of 83 and 14 HU for the body and lungs, respectively. The shape of the body and lungs on the synthesized CT was highly conformal, with a dice similarity coefficient (DSC) of 0.91, 0.97, and Hausdorff distance (HD) of 7.9 mm, and 4.9 mm, respectively, compared with the planning CT scan. The tumor showed less conformality, which warrants acquisition of treatment Day1 CT and online adaptive RT. An initial plan was designed on synthesized CT and then adapted to treatment Day1 CT using the adapt to position (ATP) and adapt to shape (ATS) method. Non-inferior plan quality was achieved by the ATP scenario, while all ATS-adapted plans showed good plan quality. Conclusion: DAART reduces the common online ART (ART) treatment course by at least two weeks, resulting in a 50% shorter time to treatment to lower the chance of restaging and loss of local control.

Adaptive Radiation Therapy in the Treatment of Lung Cancer: An Overview of the Current State of the Field.

Lung cancer treatment is constantly evolving due to technological advances in the delivery of radiation therapy. Adaptive radiation therapy (ART) allows for modification of a treatment plan with the goal of improving the dose distribution to the patient due to anatomic or physiologic deviations from the initial simulation. The implementation of ART for lung cancer is widely varied with limited consensus on who to adapt, when to adapt, how to adapt, and what the actual benefits of adaptation are. ART for lung cancer presents significant challenges due to the nature of the moving target, tumor shrinkage, and complex dose accumulation because of plan adaptation. This article presents an overview of the current state of the field in ART for lung cancer, specifically, probing topics of: patient selection for the greatest benefit from adaptation, models which predict who and when to adapt plans, best timing for plan adaptation, optimized workflows for implementing ART including alternatives to re-simulation, the best radiation techniques for ART including magnetic resonance guided treatment, algorithms and quality assurance, and challenges and techniques for dose reconstruction. To date, the clinical workflow burden of ART is one of the major reasons limiting its widespread acceptance. However, the growing body of evidence demonstrates overwhelming support for reduced toxicity while improving tumor dose coverage by adapting plans mid-treatment, but this is offset by the limited knowledge about tumor control. Progress made in predictive modeling of on-treatment tumor shrinkage and toxicity, optimizing the timing of adaptation of the plan during the course of treatment, creating optimal workflows to minimize staffing burden, and utilizing deformable image registration represent ways the field is moving toward a more uniform implementation of ART.

Image-guided hypofractionated simultaneous integrated boost and adaptive radiotherapy for spine metastasis.

BACKGROUND: (I) Dosimetric comparison between Helical tomotherapy (HT) and intensity-modulated radiation therapy (IMRT) with hypofractionated simultaneously integrated boost (HF-SIB) technique for spine metastasis. (II) Mega-voltage CT (MVCT) imaging can be used to monitor changes and calculate the true spinal cord dose over multiple fractions, and compare it with the planned dose by deformable image registration. METHODS: We retrospectively analyzed 57 patients with spine metastasis receiving HT at our institution between March 2016 and March 2019. (I) The dose/fraction to planning gross tumor volume (PGTV) and planning target volume (PTV) were 40 or 50 Gy/10 fractions and 30 or 40 Gy/10 fractions. Plans were compared according to PTV coverage and OARs sparing. (II) The daily MVCT were strictly registered with plan CT according to the rigid structures. Contours of the target and critical organs were then deformed from plan CT to MVCT using MIM deformable registration algorithm. After rigid imaging registration, the planning dose matrix was mapped to the MVCT images. The total doses of 10 fractions to the deformed structures were compared with the planned doses. RESULTS: Comparing HT and IMRT plan averaged over all patients, differences were observed for both homogeneity index (HI) (P<0.001) and conformity index (CI) (P=0.032). The maximum dose of the spinal cord was significantly lower in the HT group than the IMRT group (P=0.037). The actual dose of the spinal cord obtained based on the MVCT modified adaptive radiation therapy (ART) was slightly higher than the initially planned dose, while no significant difference was observed (P=0.083). CONCLUSIONS: HF-SIB with HT was able to achieve lower spinal cord doses, which was dosimetrically superior to IMRT, especially in those cases where strict control of the spinal cord dose is required. With deformable contours from the planning CT, daily MVCT along with rigid dose transformation can provide quantitative dose guidance for replanning.

Comparison of positioning accuracy of different registration methods and dosimetric analysis of adaptive radiotherapy for breast cancer after breast conserving surgery.

BACKGROUND: This study explores the effect of different registration methods on the placement accuracy and dosimetric analysis of adaptive radiation therapy (ART) after breast conserving surgery for breast cancer, based on cone-beam computed tomography (CBCT). METHODS: Thirty breast cancer patients, who underwent breast conserving surgery, were divided into three groups, with 10 patients in each group: automatic grayscale registration (group A), automatic bony marker registration (group B), and automatic grayscale registration combined with manual bony marker registration (group C). Three registration methods were conducted before the first radiotherapy, and once a week under the guidance of CBCT. The dosimetric comparison was made with the original plan. RESULTS: The X direction was significantly different between groups A and B (P=0.036). The X and Y direction were significantly different between groups A and C (P=0.001, P=0.019). The placement errors were significantly different between groups B and C in the X and Y directions (P<0.001, P=0.003). The ART plan was significantly better than the original plan, in terms of the Dmax, Dmean, D90, V90, V100, V95, HI and CI of planning target volume (PTV) (P<0.05). Furthermore, the ART plan was significantly better, in terms of the Dmean, V5, V10, V20 and V30 of the affected lung, the Dmean, V5, V10, V20 and V30 of the double lung, and the Dmean, V5, V10, V20 and V30 of the heart. Moreover, the Dmax, V5 and V10 of the contralateral breast were significantly lower than those in the original CT plan (P<0.05). CONCLUSIONS: For the CBCT placement verification after breast conserving surgery, the accuracy and stability of automatic gray-scale registration combined with manual bone markers are better than those of the automatic gray-scale registration and automatic bone marker registration.

Comparison of CT number calibration techniques for CBCT-based dose calculation.

PURPOSE: The aim of this work was to compare and validate various computed tomography (CT) number calibration techniques with respect to cone beam CT (CBCT) dose calculation accuracy. METHODS: CBCT dose calculation accuracy was assessed for pelvic, lung, and head and neck (H&N) treatment sites for two approaches: (1) physics-based scatter correction methods (CBCTr); (2) density override approaches including assigning water density to the entire CBCT (W), assignment of either water or bone density (WB), and assignment of either water or lung density (WL). Methods for CBCT density assignment within a commercially available treatment planning system (RSauto), where CBCT voxels are binned into six density levels, were assessed and validated. Dose-difference maps and dose-volume statistics were used to compare the CBCT dose distributions with the ground truth of a planning CT acquired the same day as the CBCT. RESULTS: For pelvic cases, all CTN calibration methods resulted in average dose-volume deviations below 1.5 %. RSauto provided larger than average errors for pelvic treatments for patients with large amounts of adipose tissue. For H&N cases, all CTN calibration methods resulted in average dose-volume differences below 1.0 % with CBCTr (0.5 %) and RSauto (0.6 %) performing best. For lung cases, WL and RSauto methods generated dose distributions most similar to the ground truth. CONCLUSION: The RSauto density override approach is an attractive option for CTN adjustments for a variety of anatomical sites. RSauto methods were validated, resulting in dose calculations that were consistent with those calculated on diagnostic-quality CT images, for CBCT images acquired of the lung, for patients receiving pelvic RT in cases without excess adipose tissue, and for H&N cases.