Feasibility Study for Markerless Tracking of Lung Tumors in Stereotactic Body Radiotherapy

Richter, Anne; Wilbert, Juergen; Baier, Kurt; Flentje, Michael; Gückenberger, Matthias

doi:10.1016/j.ijrobp.2009.11.028

Cited by 67 publications

(60 citation statements)

References 23 publications

(29 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The superior‐inferior (SI) and left‐right (LR) tumor detection errors between manual and tracking in this study are larger than those of Anne et al., in which they adopted the same tracking algorithm as ours; however, the means with standard deviations in SI and LR were 1.0 ± 1.1 mm and 0.6 ± 0.6 mm, respectively 8. The different accuracy may be attributed to their different approach for the manual determination of the reference point.…”

Section: Discussionmentioning

confidence: 86%

“…For the automatic detection of tumors on subsequent frames, the mask was moved pixel‐by‐pixel within a fixed region of 10 × 10 square pixels (7.8 × 7.8 mm 2 ), in which the tumor motions were pre‐examined and assured to be within the defined region. As a tracking algorithm, the minimum position of the mean of the sum of squared pixel differences (MSSD) between the first (reference) and the objective frame was taken as the best matching point ( T t ( k ): tracked tumor position for frame k ) 8, 27. The same procedures were repeated using deblurred, CLAHE and denoised sets.…”

Section: Methodsmentioning

confidence: 99%

“…One of the most useful applications of MV EPID is the markerless tumor tracking, in which the EPID is operated in cine mode and produces continuous portal images from the treatment beam 8, 9, 10, 11. The risk of pneumothorax from the marker implantation also prompted researchers to explore the possibility of markerless tumor tracking 12.…”

Section: Introductionmentioning

confidence: 99%

“…The risk of pneumothorax from the marker implantation also prompted researchers to explore the possibility of markerless tumor tracking 12. While most studies on tumor tracking have been focused on tracking algorithms,8, 9, 10, 11 the importance of consecutive image display on EPID cannot be neglected. The visual confirmation of the tracking accuracy during treatment greatly facilitates action against possible misalignment of beam aperture to the moving target.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Enhancement of megavoltage electronic portal images for markerless tumor tracking

Cheong

Yoon

Park

et al. 2018

J Applied Clin Med Phys

View full text Add to dashboard Cite

PurposeThe poor quality of megavoltage (MV) images from electronic portal imaging device (EPID) hinders visual verification of tumor targeting accuracy particularly during markerless tumor tracking. The aim of this study was to investigate the effect of a few representative image processing treatments on visual verification and detection capability of tumors under auto tracking.MethodsImages of QC‐3 quality phantom, a single patient's setup image, and cine images of two‐lung cancer patients were acquired. Three image processing methods were individually employed to the same original images. For each deblurring, contrast enhancement, and denoising, a total variation deconvolution, contrast‐limited adaptive histogram equalization (CLAHE), and median filter were adopted, respectively. To study the effect of image enhancement on tumor auto‐detection, a tumor tracking algorithm was adopted in which the tumor position was determined as the minimum point of the mean of the sum of squared pixel differences (MSSD) between two images. The detectability and accuracy were compared.ResultsDeblurring of a quality phantom image yielded sharper edges, while the contrast‐enhanced image was more readable with improved structural differentiation. Meanwhile, the denoising operation resulted in noise reduction, however, at the cost of sharpness. Based on comparison of pixel value profiles, contrast enhancement outperformed others in image perception. During the tracking experiment, only contrast enhancement resulted in tumor detection in all images using our tracking algorithm. Deblurring failed to determine the target position in two frames out of a total of 75 images. For original and denoised set, target location was not determined for the same five images. Meanwhile, deblurred image showed increased detection accuracy compared with the original set. The denoised image resulted in decreased accuracy. In the case of contrast‐improved set, the tracking accuracy was nearly maintained as that of the original image.ConclusionsConsidering the effect of each processing on tumor tracking and the visual perception in a limited time, contrast enhancement would be the first consideration to visually verify the tracking accuracy of tumors on MV EPID without sacrificing tumor detectability and detection accuracy.

show abstract

Section: Discussionmentioning

confidence: 86%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Enhancement of megavoltage electronic portal images for markerless tumor tracking

Cheong

Yoon

Park

et al. 2018

J Applied Clin Med Phys

View full text Add to dashboard Cite

show abstract

“…10 Markerless template matching approaches to track lung tumors on MV images have been proposed as well. 11,12 However, both published algorithms rely upon retrospective image analysis and are therefore not suitable for real-time applications.…”

Section: Introductionmentioning

confidence: 99%

Real‐time soft tissue motion estimation for lung tumors during radiotherapy delivery

2013

View full text Add to dashboard Cite

Purpose: To provide real-time lung tumor motion estimation during radiotherapy treatment delivery without the need for implanted fiducial markers or additional imaging dose to the patient. Methods: 2D radiographs from the therapy beam's-eye-view (BEV) perspective are captured at a frame rate of 12.8 Hz with a frame grabber allowing direct RAM access to the image buffer. An in-house developed real-time soft tissue localization algorithm is utilized to calculate soft tissue displacement from these images in real-time. The system is tested with a Varian TX linear accelerator and an AS-1000 amorphous silicon electronic portal imaging device operating at a resolution of 512 × 384 pixels. The accuracy of the motion estimation is verified with a dynamic motion phantom. Clinical accuracy was tested on lung SBRT images acquired at 2 fps. Results: Real-time lung tumor motion estimation from BEV images without fiducial markers is successfully demonstrated. For the phantom study, a mean tracking error <1.0 mm [root mean square (rms) error of 0.3 mm] was observed. The tracking rms accuracy on BEV images from a lung SBRT patient (≈20 mm tumor motion range) is 1.0 mm. Conclusions:The authors demonstrate for the first time real-time markerless lung tumor motion estimation from BEV images alone. The described system can operate at a frame rate of 12.8 Hz and does not require prior knowledge to establish traceable landmarks for tracking on the fly. The authors show that the geometric accuracy is similar to (or better than) previously published markerless algorithms not operating in real-time.

show abstract

Technical Note: Combination of multiple EPID imager layers improves image quality and tracking performance of low contrast‐to‐noise objects

et al. 2017

View full text Add to dashboard Cite

show abstract

Feasibility Study for Markerless Tracking of Lung Tumors in Stereotactic Body Radiotherapy

Cited by 67 publications

References 23 publications

Enhancement of megavoltage electronic portal images for markerless tumor tracking

Enhancement of megavoltage electronic portal images for markerless tumor tracking

Real‐time soft tissue motion estimation for lung tumors during radiotherapy delivery

Technical Note: Combination of multiple EPID imager layers improves image quality and tracking performance of low contrast‐to‐noise objects

Contact Info

Product

Resources

About