In Vivo Validation of Elekta's Clarity Autoscan for Ultrasound-based Intrafraction Motion Estimation of the Prostate During Radiation Therapy

Abstract

Purpose: Our purpose was to perform an in vivo validation of ultrasound imaging for intrafraction motion estimation using the Elekta Clarity Autoscan system during prostate radiation therapy. The study was conducted as part of the Clarity-Pro trial (NCT02388308).

Methods and materials: Initial locations of intraprostatic fiducial markers were identified from cone beam computed tomography scans. Marker positions were translated according to Clarity intrafraction 3-dimensional prostate motion estimates. The updated locations were projected onto the 2-dimensional electronic portal imager plane. These Clarity-based estimates were compared with the actual portal-imaged 2-dimensional marker positions. Images from 16 patients encompassing 80 fractions were analyzed. To investigate the influence of intraprostatic markers and image quality on ultrasound motion estimation, 3 observers rated image quality, and the marker visibility on ultrasound images was assessed.

Results: The median difference between Clarity-defined intrafraction marker locations and portal-imaged marker locations was 0.6 mm (with 95% limit of agreement at 2.5 mm). Markers were identified on ultrasound in only 3 of a possible 240 instances. No linear relationship between image quality and Clarity motion estimation confidence was identified. The difference between Clarity-based motion estimates and electronic portal-imaged marker location was also independent of image quality. Clarity estimation confidence was degraded in a single fraction owing to poor probe placement.

Conclusions: The accuracy of Clarity intrafraction prostate motion estimation is comparable with that of other motion-monitoring systems in radiation therapy. The effect of fiducial markers in the study was deemed negligible as they were rarely visible on ultrasound images compared with intrinsic anatomic features. Clarity motion estimation confidence was robust to variations in image quality and the number of ultrasound-imaged anatomic features; however, it was degraded as a result of poor probe placement.

Fig. 1

a, Imaging workflow timeline for a typical 5-field intensity modulated radiation therapy fraction. b, Three-step image processing workflow depicting (1) manual marker localizations, (2) Autoscan-based localization, and (3) projection and comparison of marker centers of mass (CoM). CBCT = cone beam computed tomography; EPI = electronic portal imaging; 2D = 2-dimensional; 3D = 3-dimensional.

Fig. 2

a, Sagittal cone beam computed tomography image with associated transperineal ultrasound image depicting prostate guidance positioning volume contour (blue) and fiducial marker identified visually (green arrow). b, c, Guidance positioning volume features visible on transperineal ultrasound images but not cone beam computed tomography images. High-intensity (white) ultrasound features seen in the central region of the prostate likely are calcifications. Ultrasound features are also observed near the urethra and bladder-prostate interface. (A color version of this figure is available at https://doi.org/10.1016/j.ijrobp.2018.04.008.)

Fig. 3

Bland-Altman plots of Autoscan error (E), depicted on the plots' y axes, as the difference between monitoring and electronic portal imaging (EPI) estimates of prostate position. Median E is shown by the solid line, and 95% limits of agreement (LOAs) are shown by the dashed lines: in the portal image horizontal u axis, with a median of 0 mm and 95% LOAs of –2.0 to 2.1 mm (a); vertical v axis, with a median of 0.1 mm and 95% LOAs of –2.5 to 1.9 mm (b); and Bland-Altman plot of the 2-dimensional error vector magnitude $\left(\sqrt{u^2+v^2}\right)$, with a median of 1.0 mm and 95% LOA of 2.6 mm (c).