Accuracy of robotic radiosurgery in renal cell carcinoma.

PURPOSE: Although emerging clinical evidence supports robotic radiosurgery as a highly effective treatment option for renal cell carcinoma (RCC) less than 4 cm in diameter, delivery uncertainties and associated target volume margins have not been studied in detail. We assess intrafraction tumor motion patterns and accuracy of robotic radiosurgery in renal tumors with real-time respiratory tracking to optimize treatment margins. METHODS: Delivery log files from 165 consecutive treatments of RCC were retrospectively analyzed. Five components were considered for planning target volume (PTV) margin estimation: (a) The model error from the correlation model between patient breath and tumor motion, (b) the prediction error from an algorithm predicting the patient breathing pattern, (c) the targeting error from the treatment robot, (d) the inherent total accuracy of the system for respiratory motion tracking, and (e) the margin required to cover potential target rotation, simulated with PTV rotations up to 10°. RESULTS: The median tumor motion was 10.5 mm, 2.4 mm and 4.4 mm in the superior-inferior, left-right, and anterior-posterior directions, respectively. The root of the sum of squares of all contributions to the system's inaccuracy results in a minimum PTV margin of 4.3 mm, 2.6 mm and 3.0 mm in the superior-inferior, left-right and anterior-posterior directions, respectively, assuming optimal fiducial position and neglecting target deformation. CONCLUSIONS: We have assessed kidney motion and derived PTV margins for the treatment of RCC with robotic radiosurgery, which helps to deliver renal treatments in a more consistent manner and potentially further improve outcomes.

Self-Shielding Gyroscopic Radiosurgery: A Prospective Experience and Analysis of the First 100 Patients.

Background Stereotactic radiosurgery is a well-established treatment option for the management of various benign and malignant brain tumors. It can be delivered with several treatment platforms, usually requiring shielded radiation vaults to meet regulatory safety requirements. Recent technical advances have led to the first self-shielding platform enabling the delivery of gyroscopic radiosurgery (GRS). Given the limited number of GRS treatment platforms, the novelty of its characteristics, and the lack of available data, we report our prospective experience with the first 100 patients treated with GRS. Materials and methods Patients undergoing GRS for the treatment of intracranial tumors were enrolled in this prospective study. Patient and treatment characteristics, including patient satisfaction, were collected and analyzed. Results A total of 100 patients with 155 tumors were treated. The most commonly treated tumors comprised brain metastases (BM) (49%), vestibular schwannomas (31%), and meningiomas (14%). The median prescription dose for malignant and benign tumors was 20 and 13 Gy, respectively. The median prescription isodose line was 56%. Gross tumor volumes were small, with a median of 0.37 cc for BM and 0.92 cc for the other entities. The median total treatment time was 40 minutes. Dosimetric performance indices showed median values of 1.20 (conformity index), 1.24 (new conformity index), 1.74 (homogeneity index), and 3.13 (gradient index). Volumetric assessment of the treated tumors showed an overall decrease in size at the first available follow-up. Most patients were satisfied with the treatment experience. Conclusion Our first prospective experience of the use of GRS is favorable. Analyses of the dosimetric performance, treatment times, volumetric assessment, and patient satisfaction demonstrate its suitability for stereotactic treatments of intracranial tumors. Further prospective clinical and dosimetric analyses for GRS are pending.

Deep Learning Electronic Cleansing for Single- and Dual-Energy CT Colonography.

Electronic cleansing (EC) is used for computational removal of residual feces and fluid tagged with an orally administered contrast agent on CT colonographic images to improve the visibility of polyps during virtual endoscopic "fly-through" reading. A recent trend in CT colonography is to perform a low-dose CT scanning protocol with the patient having undergone reduced- or noncathartic bowel preparation. Although several EC schemes exist, they have been developed for use with cathartic bowel preparation and high-radiation-dose CT, and thus, at a low dose with noncathartic bowel preparation, they tend to generate cleansing artifacts that distract and mislead readers. Deep learning can be used for improvement of the image quality with EC at CT colonography. Deep learning EC can produce substantially fewer cleansing artifacts at dual-energy than at single-energy CT colonography, because the dual-energy information can be used to identify relevant material in the colon more precisely than is possible with the single x-ray attenuation value. Because the number of annotated training images is limited at CT colonography, transfer learning can be used for appropriate training of deep learning algorithms. The purposes of this article are to review the causes of cleansing artifacts that distract and mislead readers in conventional EC schemes, to describe the applications of deep learning and dual-energy CT colonography to EC of the colon, and to demonstrate the improvements in image quality with EC and deep learning at single-energy and dual-energy CT colonography with noncathartic bowel preparation. ©RSNA, 2018.