Dosimetric assessment of patient dose calculation on a deep learning-based synthesized computed tomography image for adaptive radiotherapy.

PURPOSE: Dose computation using cone beam computed tomography (CBCT) images is inaccurate for the purpose of adaptive treatment planning. The main goal of this study is to assess the dosimetric accuracy of synthetic computed tomography (CT)-based calculation for adaptive planning in the upper abdominal region. We hypothesized that deep learning-based synthetically generated CT images will produce comparable results to a deformed CT (CTdef) in terms of dose calculation, while displaying a more accurate representation of the daily anatomy and therefore superior dosimetric accuracy. METHODS: We have implemented a cycle-consistent generative adversarial networks (CycleGANs) architecture to synthesize CT images from the daily acquired CBCT image with minimal error. CBCT and CT images from 17 liver stereotactic body radiation therapy (SBRT) patients were used to train, test, and validate the algorithm. RESULTS: The synthetically generated images showed increased signal-to-noise ratio, contrast resolution, and reduced root mean square error, mean absolute error, noise, and artifact severity. Superior edge matching, sharpness, and preservation of anatomical structures from the CBCT images were observed for the synthetic images when compared to the CTdef registration method. Three verification plans (CBCT, CTdef, and synthetic) were created from the original treatment plan and dose volume histogram (DVH) statistics were calculated. The synthetic-based calculation shows comparatively similar results to the CTdef-based calculation with a maximum mean deviation of 1.5%. CONCLUSIONS: Our findings show that CycleGANs can produce reliable synthetic images for the adaptive delivery framework. Dose calculations can be performed on synthetic images with minimal error. Additionally, enhanced image quality should translate into better daily alignment, increasing treatment delivery accuracy.

Fiducial detection and registration for 3D IMRT QA with organ-specific dose information.

PURPOSE: Two-dimensional (2D) IMRT QA has been widely performed in Radiation Oncology clinic. However, concerns regarding its sensitivity in detecting delivery errors and its clinical meaning have been raised in publications. In this study, a robust methodology of three-dimensional (3D) IMRT QA using fiducial registration and structure-mapping was proposed to acquire organ-specific dose information. METHODS: Computed tomography (CT) markers were placed on the PRESAGE dosimeter as fiducials before CT simulation. Subsequently, the images were transferred to the treatment planning system to create a verification plan for the examined treatment plan. Patient's CT images were registered to the CT images of the dosimeter for structure mapping according to the positions of the fiducials. After irradiation, the 3D dose distribution was read-out by an optical-CT (OCT) scanner with fiducials shown on the OCT dose images. An automatic localization algorithm was developed in MATLAB to register the markers in the OCT images to those in the CT images of the dosimeter. SlicerRT was used to show and analyze the results. Fiducial registration error was acquired by measuring the discrepancies in 20 fiducial registrations, and thus the fiducial localization error and target registration error (TRE) was estimated. RESULTS: Dosimetry comparison between the calculated and measured dose distribution in various forms were presented, including 2D isodose lines comparison, 3D isodose surfaces with patient's anatomical structures, 2D and 3D gamma index, dose volume histogram and 3D view of gamma failing points. From the analysis of 20 fiducial registrations, fiducial registration error was measured to be 0.62 mm and fiducial localization error was calculated to be 0.44 mm. Target registration uncertainty of the proposed methodology was estimated to be within 0.3 mm in the area of dose measurement. CONCLUSIONS: This study proposed a robust methodology of 3D measurement-based IMRT QA for organ-specific dose comparison and demonstrated its clinical feasibility.

Evaluation of tumor progression and detection of new tumors during repeat Gamma Knife® stereotactic radiosurgery utilizing the co-registration tool in Leksell Gamma Plan®: technical note.

BACKGROUND: Repeat Gamma Knife stereotactic radiosurgery (GKSR) procedures are becoming common, especially for brain metastases. It is important to identify tumors requiring treatment at repeat GKSR and it can be challenging to distinguish treated tumors, tumor progression and new tumors. Using the image co-registration tool within the Leksell Gamma Plan software, we developed a technique to aid in the identification of tumors needing treatment. OBJECTIVES: The objective was to explore a new co-registration technique to identify tumors requiring treatment at repeat GKSR procedures. METHODS: Ten patients who underwent repeat GKSR for brain metastases were identified. Contrast-enhanced volumetric T1 magnetic resonance images (MRI) from the previous GKSR were co-registered with the new images and the resulting two-color format image was used to evaluate tumor status. RESULTS: Using the co-registered images, tumors were characterized as: resolved, regressed, stable, larger or new. Overall, 13.6% of tumors completely resolved, 26.2% regressed, 13.1% remained stable, while 7.9% progressed. Thirty-nine percent of tumors were new. CONCLUSIONS: The co-registration technique makes clinically relevant changes conspicuous on MRI. It distinguishes between tumors potentially requiring treatment and those that have been treated successfully. It can be used with tumors other than metastases and for evaluating tumor response at follow-up.

Synthetic CT for gamma knife radiosurgery dose calculation: A feasibility study.

PURPOSE: To determine if MRI-based synthetic CTs (sCT), generated with no predefined pulse sequence, can be used for inhomogeneity correction in routine gamma knife radiosurgery (GKRS) treatment planning dose calculation. METHODS: Two sets of sCTs were generated from T1post and T2 images using cycleGAN. Twenty-eight patients (18 training, 10 validation) were retrospectively selected. The image quality of the generated sCTs was compared with the original CT (oCT) regarding the HU value preservation using histogram comparison, RMSE and MAE, and structural integrity. Dosimetric comparisons were also made among GKRS plans from 3 calculation approaches: TMR10 (oCT), and convolution (oCT and sCT), at four locations: original disease site, bone/tissue interface, air/tissue interface, and mid-brain. RESULTS: The study showed that sCTs and oCTs' HU were similar, with T2-sCT performing better. TMR10 significantly underdosed the target by a mean of 5.4% compared to the convolution algorithm. There was no significant difference in convolution algorithm shot time between the oCT and sCT generated with T2. The highest and lowest dosimetric differences between the two CTs were observed in the bone and air interface, respectively. Dosimetric differences of 3.3% were observed in sCT predicted from MRI with stereotactic frames, which was not included in the training sets. CONCLUSIONS: MRI-based sCT can be utilized for GKRS convolution dose calculation without the unnecessary radiation dose, and sCT without metal artifacts could be generated in framed cases. Larger datasets inclusive of all pulse sequences can improve the training set. Further investigation and validation studies are needed before clinical implementation.

Frameless Stereotactic Radiosurgery on the Gamma Knife Icon: Early Experience From 100 Patients.

BACKGROUND: The Gamma Knife (GK) Icon (Elekta AB) uses a cone-beam computed tomography (CBCT) scanner and an infrared camera system to support the delivery of frameless stereotactic radiosurgery (SRS). There are limited data on patients treated with frameless GK radiosurgery (GKRS). OBJECTIVE: To describe the early experience, process, technical details, and short-term outcomes with frameless GKRS at our institution. METHODS: We reviewed our patient selection and described the workflow in detail, including image acquisition, treatment planning, mask-based immobilization, stereotactic CBCT localization, registration, treatment, and intrafraction monitoring. Because of the short interval of follow-up, we provide crude rates of local control. RESULTS: Data from 100 patients are reported. Median age is 67 yr old. 56 patients were treated definitively, 21 postoperatively, and 23 had salvage GKRS for recurrence after surgery. Forty-two patients had brain metastases, 26 meningiomas, 16 vestibular schwannomas, 9 high-grade gliomas, and 7 other histologies. Median doses to metastases were 20 Gy in 1 fraction (range: 14-21), 24 Gy in 3 fractions (range: 19.5-27), and 25 Gy in 5 fractions (range: 25-30 Gy). Thirteen patients underwent repeat SRS to the same area. Median treatment time was 17.7 min (range: 5.8-61.7). We found an improvement in our workflow and a greater number of patients eligible for GKRS because of the ability to fractionate treatments. CONCLUSION: We report a large cohort of consecutive patients treated with frameless GKRS. We look forward to studies with longer follow-up to provide valuable data on clinical outcomes and to further our understanding of the radiobiology of hypofractionation in the brain.

Radiosurgery for benign tumors of the spine using the Synergy S with cone-beam computed tomography image guidance.

OBJECT: There is a growing body of evidence to support the safe and effective use of spine radiosurgery. However, there is much less experience regarding the use of radiosurgery for the treatment of benign as opposed to malignant spine tumors. This study represents an evaluation of, and reporting on, the technical aspects of using a dedicated radiosurgery system for the treatment of benign spine tumors. METHODS: Forty-five consecutive benign spine tumors were treated using the Elekta Synergy S 6-MV linear accelerator with a beam modulator and cone-beam computed tomography (CBCT) image guidance technology for target localization. The study cohort included 16 men and 29 women, ranging in age from 23 to 88 years (mean age 52 years). There were 14 cervical, 12 thoracic, 14 lumbar, and 5 sacral tumors. Forty-one lesions (91%) were intradural. The most common histological types of tumor were schwannoma, neurofibroma, and meningioma. Indications for radiosurgery included primary treatment in 24 cases (53%) and treatment of recurrent or residual tumor after open resection in 21 cases (47%). RESULTS: No subacute or long-term spinal cord or cauda equina toxicity occurred during the follow-up period (median 32 months). The mean maximum dose received by the gross tumor volume (GTV) was 16 Gy (range 12-24 Gy) delivered in a single fraction in 39 cases. The mean lowest dose received to the GTV was 12 Gy (range 8-16 Gy). The GTV ranged from 0.37 to 94.5 cm(3) (mean 13.7 cm(3), median 5.9 cm(3)). In the majority of cases, a planning target volume expansion of 2 mm was employed (38 cases; 84%). The mean maximum point dose delivered to the spinal cord was 8.7 Gy (range 4-11.5 Gy); the mean volume of the spinal cord that received greater than 8 Gy was 0.9 cm(3) (range 0.0-5.1 cm(3)); and the mean dose delivered to 0.1 cm(3) of the spinal cord was 7.5 Gy (range 3-10.5 Gy). The mean maximum point dose delivered to the cauda equina was 10 Gy (range 0-13 Gy); the mean volume of the cauda equina that received greater than 8 Gy was 1.45 cm(3) (range 0.0-10.6 cm(3)); and the mean dose delivered to 0.1 cm(3) of the cauda equina was 8 Gy (range 0.5-11 Gy). CONCLUSIONS: In this study the authors describe the contouring and prescribed dose techniques used in the treatment planning and delivery of radiosurgery for benign neoplasms of the spine using CBCT image guidance. This technique may serve as an important reference for the performance of radiosurgery when one believes it is clinically indicated as a treatment modality for a benign spine tumor that is associated with both a high safety profile and a strong positive clinical outcome.