Assessment of lung tumor motion and setup uncertainties using implanted fiducials

Nelson, Christopher Lee; Starkschall, George; Balter, Peter A; Morice, Rodolfo C.; Stevens, Craig W.; Chang, Joe Y.

doi:10.1016/j.ijrobp.2006.10.033

Cited by 69 publications

(61 citation statements)

References 24 publications

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“…Setup uncertainties quantified by patient skin marks in a simulated setup were similar to those that we previously measured, which was expected, because the same immobilization was used in the present study as in the previous study. As in the Nelson et al (17) study, we observed fiducials dislodging from the patient shortly after implantation. This dislodgement is probably a result of the bronchoscopic implantation technique, which has been observed to have a lower incidence of pneumothorax relative to percutaneous fiducial implantation (24) …”

Section: Discussionsupporting

confidence: 82%

“…Cylindrical gold fiducials (

0.9 \times 3 mm

: NMPE, Inc.) were inserted in the phantom (17) . Insertion involved drilling small holes in thermoluminescent dosimeter inserts and securely placing the fiducials in these inserts.…”

Section: Methodsmentioning

confidence: 99%

“…Fiducials were implanted bronchoscopically in the periphery of the tumor (17) . For this particular patient, 5 fiducials were implanted, but 2 fiducials had dislodged by time the simulation was performed.…”

Section: Methodsmentioning

confidence: 99%

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A technique for reducing patient setup uncertainties by aligning and verifying daily positioning of a moving tumor using implanted fiducials

Nelson

Balter

Morice

et al. 2008

J Applied Clin Med Phys

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This study aimed to validate and implement a methodology in which fiducials implanted in the periphery of lung tumors can be used to reduce uncertainties in tumor location.Alignment software that matches marker positions on two‐dimensional (2D) kilovoltage portal images to positions on three‐dimensional (3D) computed tomography data sets was validated using static and moving phantoms. This software also was used to reduce uncertainties in tumor location in a patient with fiducials implanted in the periphery of a lung tumor.Alignment of fiducial locations in orthogonal projection images with corresponding fiducial locations in 3D data sets can position both static and moving phantoms with an accuracy of 1 mm. In a patient, alignment based on fiducial locations reduced systematic errors in the left–right direction by 3 mm and random errors by 2 mm, and random errors in the superior–inferior direction by 3 mm as measured by anterior–posterior cine images.Software that matches fiducial markers on 2D and 3D images is effective for aligning both static and moving fiducials before treatment and can be implemented to reduce patient setup uncertainties.PACS number: 81.40.Wx

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Section: Discussionsupporting

confidence: 82%

“…Cylindrical gold fiducials (

0.9 \times 3 mm

: NMPE, Inc.) were inserted in the phantom (17) . Insertion involved drilling small holes in thermoluminescent dosimeter inserts and securely placing the fiducials in these inserts.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A technique for reducing patient setup uncertainties by aligning and verifying daily positioning of a moving tumor using implanted fiducials

Nelson

Balter

Morice

et al. 2008

J Applied Clin Med Phys

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show abstract

“…[21][22][23] However, such an approach involves an invasive procedure and carries risks of pneumothorax and exacerbation of underlying chronic obstructive pulmonary disease. 11 Although earlier studies have shown that displacement of the markers in the lung may be significant, [21][22][23] migration will be dependent on the type of marker used. [24][25][26] Another method utilizes external markers as surrogates for respiratory motion.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a template-based algorithm for markerless lung tumour localization on single- and dual-energy kilovoltage images

Block

Patel

Sürücü

et al. 2016

The British Journal of Radiology

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Objective: To evaluate a template-based matching algorithm on single-energy (SE) and dual-energy (DE) radiographs for markerless localization of lung tumours. Methods: A total of 74 images from 17 patients with Stages IA-IV lung cancer were considered. At the time of radiotherapy treatment, gated end-expiration SE radiographs were obtained at 60 and 120 kVp at different gantry angles (33°anterior and 41°oblique), from which soft-tissue-enhanced DE images were created. A template-based matching algorithm was used to localize individual tumours on both SE and DE radiographs. Tumour centroid co-ordinates obtained from the template-matching software on both SE and DE images were compared with co-ordinates defined by physicians.Results: The template-based matching algorithm was able to successfully localize the gross tumor volume within 5 mm on 70% (52/74) of the SE images vs 91% (66/ 74) of the DE images (p , 0.01). The mean vector differences between the co-ordinates of the template matched by the algorithm and the co-ordinates of the physician-defined ground truth were 3.2 6 2.8 mm for SE images vs 2.3 6 1.7 mm for DE images (p 5 0.03). Conclusion: Template-based matching on DE images was more accurate and precise than using SE images. Advances in knowledge: This represents, to the authors' knowledge, the largest study evaluating template matching on clinical SE and DE images, considering not only anterior gantry angles but also oblique angles, suggesting a novel lung tumour matching technique using DE subtraction that is reliable, accurate and precise.

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“…3,4 Mitigating the effect of respiration-induced tumor motion-with a variety of techniques such as gating, tracking, or breath-hold-can reduce the amount of normal tissue irradiated. [5][6][7][8] However, day-today changes in respiration and mean tumor position within the lung [9][10][11][12] cannot be directly managed with these same techniques ͑except, potentially, by tracking͒. Instead, direct localization of the soft-tissue target afforded by image guidance is required and can reduce the required margin by several millimeters.…”

Section: Introductionmentioning

confidence: 99%

Optimizing principal component models for representing interfraction variation in lung cancer radiotherapy

Badawi¹,

Weiss²,

Sleeman³

et al. 2010

Medical Physics

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Purpose: To optimize modeling of interfractional anatomical variation during active breath-hold radiotherapy in lung cancer using principal component analysis ͑PCA͒. Methods: In 12 patients analyzed, weekly CT sessions consisting of three repeat intrafraction scans were acquired with active breathing control at the end of normal inspiration. The gross tumor volume ͑GTV͒ and lungs were delineated and reviewed on the first week image by physicians and propagated to all other images using deformable image registration. PCA was used to model the target and lung variability during treatment. Four PCA models were generated for each specific patient: ͑1͒ Individual models for the GTV and each lung from one image per week ͑week to week, W2W͒; ͑2͒ a W2W composite model of all structures; ͑3͒ individual models using all images ͑weekly plus repeat intrafraction images, allscans͒; and ͑4͒ composite model with all images. Models were reconstructed retrospectively ͑using all available images acquired͒ and prospectively ͑using only data acquired up to a time point during treatment͒. Dominant modes representing at least 95% of the total variability were used to reconstruct the observed anatomy. Residual reconstruction error between the model-reconstructed and observed anatomy was calculated to compare the accuracy of the models. Results: An average of 3.4 and 4.9 modes was required for the allscans models, for the GTV and composite models, respectively. The W2W model required one less mode in 40% of the patients. For the retrospective composite W2W model, the average reconstruction error was 0.7Ϯ 0.2 mm, which increased to 1.1Ϯ 0.5 mm when the allscans model was used. Individual and composite models did not have significantly different errors ͑p = 0.15, paired t-test͒. The average reconstruction error for the prospective models of the GTV stabilized after four measurements at 1.2Ϯ 0.5 mm and for the composite model after five measurements at 0.8Ϯ 0.4 mm. Conclusions: Retrospective PCA models were capable of reconstructing original GTV and lung shapes and positions within several millimeters with three to four dominant modes, on average. Prospective models achieved similar accuracy after four to five measurements.

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Assessment of lung tumor motion and setup uncertainties using implanted fiducials

Cited by 69 publications

References 24 publications

A technique for reducing patient setup uncertainties by aligning and verifying daily positioning of a moving tumor using implanted fiducials

A technique for reducing patient setup uncertainties by aligning and verifying daily positioning of a moving tumor using implanted fiducials

Evaluation of a template-based algorithm for markerless lung tumour localization on single- and dual-energy kilovoltage images

Optimizing principal component models for representing interfraction variation in lung cancer radiotherapy

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