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Title: SU-E-J-155: Automatic Quantitative Decision Making Metric for 4DCT Image Quality

Abstract

Purpose: To develop a quantitative decision making metric for automatically detecting irregular breathing using a large patient population that received phase-sorted 4DCT. Methods: This study employed two patient cohorts. Cohort#1 contained 256 patients who received a phasesorted 4DCT. Cohort#2 contained 86 patients who received three weekly phase-sorted 4DCT scans. A previously published technique used a single abdominal surrogate to calculate the ratio of extreme inhalation tidal volume to normal inhalation tidal volume, referred to as the κ metric. Since a single surrogate is standard for phase-sorted 4DCT in radiation oncology clinical practice, tidal volume was not quantified. Without tidal volume, the absolute κ metric could not be determined, so a relative κ (κrel) metric was defined based on the measured surrogate amplitude instead of tidal volume. Receiver operator characteristic (ROC) curves were used to quantitatively determine the optimal cutoff value (jk) and efficiency cutoff value (τk) of κrel to automatically identify irregular breathing that would reduce the image quality of phase-sorted 4DCT. Discriminatory accuracy (area under the ROC curve) of κrel was calculated by a trapezoidal numeric integration technique. Results: The discriminatory accuracy of ?rel was found to be 0.746. The key values of jk and tk were calculated tomore » be 1.45 and 1.72 respectively. For values of ?rel such that jk≤κrel≤τk, the decision to reacquire the 4DCT would be at the discretion of the physician. This accounted for only 11.9% of the patients in this study. The magnitude of κrel held consistent over 3 weeks for 73% of the patients in cohort#3. Conclusion: The decision making metric, ?rel, was shown to be an accurate classifier of irregular breathing patients in a large patient population. This work provided an automatic quantitative decision making metric to quickly and accurately assess the extent to which irregular breathing is occurring during phase-sorted 4DCT.« less

Authors:
; ; ;  [1];  [2]
  1. University of Pennsylvania, Philadelphia, PA (United States)
  2. Deparment of Radiation Oncology, University of California Los Angeles, Los Angeles, CA (United States)
Publication Date:
OSTI Identifier:
22494165
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 42; Journal Issue: 6; Other Information: (c) 2015 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; ACCURACY; COMPUTERIZED TOMOGRAPHY; DECISION MAKING; IMAGE PROCESSING; IMAGES; INHALATION; PATIENTS; RESPIRATION

Citation Formats

Kiely, J Blanco, Olszanski, A, Both, S, White, B, and Low, D. SU-E-J-155: Automatic Quantitative Decision Making Metric for 4DCT Image Quality. United States: N. p., 2015. Web. doi:10.1118/1.4924240.
Kiely, J Blanco, Olszanski, A, Both, S, White, B, & Low, D. SU-E-J-155: Automatic Quantitative Decision Making Metric for 4DCT Image Quality. United States. doi:10.1118/1.4924240.
Kiely, J Blanco, Olszanski, A, Both, S, White, B, and Low, D. Mon . "SU-E-J-155: Automatic Quantitative Decision Making Metric for 4DCT Image Quality". United States. doi:10.1118/1.4924240.
@article{osti_22494165,
title = {SU-E-J-155: Automatic Quantitative Decision Making Metric for 4DCT Image Quality},
author = {Kiely, J Blanco and Olszanski, A and Both, S and White, B and Low, D},
abstractNote = {Purpose: To develop a quantitative decision making metric for automatically detecting irregular breathing using a large patient population that received phase-sorted 4DCT. Methods: This study employed two patient cohorts. Cohort#1 contained 256 patients who received a phasesorted 4DCT. Cohort#2 contained 86 patients who received three weekly phase-sorted 4DCT scans. A previously published technique used a single abdominal surrogate to calculate the ratio of extreme inhalation tidal volume to normal inhalation tidal volume, referred to as the κ metric. Since a single surrogate is standard for phase-sorted 4DCT in radiation oncology clinical practice, tidal volume was not quantified. Without tidal volume, the absolute κ metric could not be determined, so a relative κ (κrel) metric was defined based on the measured surrogate amplitude instead of tidal volume. Receiver operator characteristic (ROC) curves were used to quantitatively determine the optimal cutoff value (jk) and efficiency cutoff value (τk) of κrel to automatically identify irregular breathing that would reduce the image quality of phase-sorted 4DCT. Discriminatory accuracy (area under the ROC curve) of κrel was calculated by a trapezoidal numeric integration technique. Results: The discriminatory accuracy of ?rel was found to be 0.746. The key values of jk and tk were calculated to be 1.45 and 1.72 respectively. For values of ?rel such that jk≤κrel≤τk, the decision to reacquire the 4DCT would be at the discretion of the physician. This accounted for only 11.9% of the patients in this study. The magnitude of κrel held consistent over 3 weeks for 73% of the patients in cohort#3. Conclusion: The decision making metric, ?rel, was shown to be an accurate classifier of irregular breathing patients in a large patient population. This work provided an automatic quantitative decision making metric to quickly and accurately assess the extent to which irregular breathing is occurring during phase-sorted 4DCT.},
doi = {10.1118/1.4924240},
journal = {Medical Physics},
number = 6,
volume = 42,
place = {United States},
year = {Mon Jun 15 00:00:00 EDT 2015},
month = {Mon Jun 15 00:00:00 EDT 2015}
}
  • Purpose: To assess regional changes in human lung ventilation and mechanics using four-dimensional computed tomography (4DCT) and deformable image registration. This work extends our prior analysis of the entire lung to a lobe-based analysis. Methods: 4DCT images acquired from 20 patients prior to radiation therapy (RT) were used for this analysis. Jacobian ventilation and motion maps were computed from the displacement field after deformable image registration between the end of expiration breathing phase and the end of inspiration breathing phase. The lobes were manually segmented on the reference phase by a medical physicist expert. The voxel-by-voxel ventilation and motion magnitudemore » for all subjects were grouped by lobes and plotted into cumulative voxel frequency curves respectively. In addition, to eliminate the effect of different breathing efforts across subjects, we applied the inter-subject equivalent lung volume (ELV) method on a subset of the cohort and reevaluated the lobar ventilation. Results: 95% of voxels in the lung are expanding during inspiration. However, some local regions of lung tissue show far more expansion than others. The greatest expansion with respiration occurs within the lower lobes; between exhale and inhale the median expansion in lower lobes is approximately 15%, while the median expansion in upper lobes is 10%. This appears to be driven by a subset of lung tissues within the lobe that have greater expansion; twice the number of voxels in the lower lobes (20%) expand by > 30% when compared to the upper lobes (10%). Conclusion: Lung ventilation and motion show significant difference on the lobar level. There are different lobar fractions of driving voxels that contribute to the major expansion of the lung. This work was supported by NIH grant CA166703.« less
  • Purpose: Irregular breathing motion has a deleterious impact on 4DCT image quality. The breathing guidance system: audiovisual biofeedback (AVB) is designed to improve breathing regularity, however, its impact on 4DCT image quality has yet to be quantified. The purpose of this study was to quantify the impact of AVB on thoracic 4DCT image quality by utilizing the digital eXtended Cardiac Torso (XCAT) phantom driven by lung tumor motion patterns. Methods: 2D tumor motion obtained from 4 lung cancer patients under two breathing conditions (i) without breathing guidance (free breathing), and (ii) with guidance (AVB). There were two breathing sessions, yieldingmore » 8 tumor motion traces. This tumor motion was synchronized with the XCAT phantom to simulate 4DCT acquisitions under two acquisition modes: (1) cine mode, and (2) prospective respiratory-gated mode. Motion regularity was quantified by the root mean square error (RMSE) of displacement. The number of artefacts was visually assessed for each 4DCT and summed up for each breathing condition. Inter-session anatomic reproducibility was quantified by the mean absolute difference (MAD) between the Session 1 4DCT and Session 2 4DCT. Results: AVB improved tumor motion regularity by 30%. In cine mode, the number of artefacts was reduced from 61 in free breathing to 40 with AVB, in addition to AVB reducing the MAD by 34%. In gated mode, the number of artefacts was reduced from 63 in free breathing to 51 with AVB, in addition to AVB reducing the MAD by 23%. Conclusion: This was the first study to compare the impact of breathing guidance on 4DCT image quality compared to free breathing, with AVB reducing the amount of artefacts present in 4DCT images in addition to improving inter-session anatomic reproducibility. Results thus far suggest that breathing guidance interventions could have implications for improving radiotherapy treatment planning and interfraction reproducibility.« less
  • Purpose: To study breathing related tumor motion amplitudes by lung lobe location under controlled breathing conditions used in Stereotactic Body Radiation Therapy (SBRT) for NSCLC. Methods: Sixty-five NSCLC SBRT patients since 2009 were investigated. Patients were categorized based on tumor anatomic location (RUL-17, RML-7, RLL-18, LUL-14, LLL-9). A 16-slice CT scanner [GE RT16 Pro] along with Varian Realtime Position Management (RPM) software was used to acquire the 4DCT data set using 1.25 mm slice width. Images were binned in 10 phases, T00 being at maximum inspiration ' T50 at maximum expiration phase. Tumor volume was segmented in T50 using themore » CT-lung window and its displacement were measured from phase to phase in all three axes; superiorinferior, anterior-posterior ' medial-lateral at the centroid level of the tumor. Results: The median tumor movement in each lobe was as follows: RUL= 3.8±2.0 mm (mean ITV: 9.5 cm{sup 3}), RML= 4.7±2.8 mm (mean ITV: 9.2 cm{sup 3}), RLL=6.6±2.6 mm (mean ITV: 12.3 cm{sup 3}), LUL=3.8±2.4 mm (mean ITV: 18.5 cm{sup 3}), ' LLL=4.7±2.5 mm (mean ITV: 11.9 cm{sup 3}). The median respiratory cycle for all patients was found to be 3.81 ± 1.08 seconds [minimum 2.50 seconds, maximum 7.07 seconds]. The tumor mobility incorporating breathing cycle was RUL = 0.95±0.49 mm/s, RML = 1.35±0.62 mm/s, RLL = 1.83±0.71 mm/s, LUL = 0.98 ±0.50 mm/s, and LLL = 1.15 ±0.53 mm/s. Conclusion: Our results show that tumor displacement is location dependent. The range of motion and mobility increases as the location of the tumor nears the diaphragm. Under abdominal compression, the magnitude of tumor motion is reduced by as much as a factor of 2 in comparison to reported tumor magnitudes under conventional free breathing conditions. This study demonstrates the utility of abdominal compression in reducing the tumor motion leading to reduced ITV and planning tumor volumes (PTV)« less
  • Purpose: Thoracic motion changes from cycle-to-cycle and day-to-day. Conventional 4DCT does not capture these cycle to cycle variations. We present initial results of a novel 4DCT reconstruction technique based on maximum a posteriori (MAP) reconstruction. The technique uses the same acquisition process (and therefore dose) as a conventional 4DCT in order to create a high spatiotemporal resolution cine CT that captures several breathing cycles. Methods: Raw 4DCT data were acquired from a lung cancer patient. The continuous 4DCT was reconstructed using MAP algorithm which uses the raw, time-stamped CT data to reconstruct images while simultaneously estimating deformation in the subject'smore » anatomy. This framework incorporates physical effects such as hysteresis and is robust to detector noise and irregular breathing patterns. The 4D image is described in terms of a 3D reference image defined at one end of the hysteresis loop, and two deformation vector fields (DVFs) corresponding to inhale motion and exhale motion respectively. The MAP method uses all of the CT projection data and maximizes the log posterior in order to iteratively estimate a timevariant deformation vector field that describes the entire moving and deforming volume. Results: The MAP 4DCT yielded CT-quality images for multiple cycles corresponding to the entire duration of CT acquisition, unlike the conventional 4DCT, which only yielded a single cycle. Variations such as amplitude and frequency changes and baseline shifts were clearly captured by the MAP 4DC Conclusion: We have developed a novel, binning-free, parameterized 4DCT reconstruction technique that can capture cycle-to-cycle variations of respiratory motion. This technique provides an invaluable tool for respiratory motion management research. This work was supported by funding from the National Institutes of Health and VisionRT Ltd. Amit Sawant receives research funding from Varian Medical Systems, Vision RT and Elekta.« less
  • Purpose: The quantitative evaluation of deformable image registration (DIR) is currently challenging due to lack of a ground truth. In this study we test a new method proposed for quantifying multiple-image based DIRrelated uncertainties, for DIR of pelvic images. Methods: 19 patients were analyzed, each with 6 CT scans, who previously had radiotherapy for prostate cancer. Manually delineated structures for rectum and bladder, which served as ground truth structures, were delineated on the planning CT and each subsequent scan. For each patient, voxel-by-voxel DIR-related uncertainties were evaluated, following B-spline based DIR, by applying a previously developed metric, the distance discordancemore » metric (DDM; Saleh et al., PMB (2014) 59:733). The DDM map was superimposed on the first acquired CT scan and DDM statistics were assessed, also relative to two metrics estimating the agreement between the propagated and the manually delineated structures. Results: The highest DDM values which correspond to greatest spatial uncertainties were observed near the body surface and in the bowel due to the presence of gas. The mean rectal and bladder DDM values ranged from 1.1–11.1 mm and 1.5–12.7 mm, respectively. There was a strong correlation in the DDMs between the rectum and bladder (Pearson R = 0.68 for the max DDM). For both structures, DDM was correlated with the ratio between the DIR-propagated and manually delineated volumes (R = 0.74 for the max rectal DDM). The maximum rectal DDM was negatively correlated with the Dice Similarity Coefficient between the propagated and the manually delineated volumes (R= −0.52). Conclusion: The multipleimage based DDM map quantified considerable DIR variability across different structures and among patients. Besides using the DDM for quantifying DIR-related uncertainties it could potentially be used to adjust for uncertainties in DIR-based accumulated dose distributions.« less