Adam G. Chandler

Use of weekly 4DCT-based ventilation maps to quantify changes in lung function for patients undergoing radiation therapy

PURPOSE A method has been proposed to calculate ventilation maps from four-dimensional computed tomography (4DCT) images. Weekly 4DCT data were acquired throughout the course of radiation therapy for patients with lung cancer. The purpose of our work was to use ventilation maps calculated from weekly 4DCT data to study how ventilation changed throughout radiation therapy. METHODS Quantitative maps representing ventilation were generated for six patients. Deformable registration was used to link corresponding lung volume elements between the inhale and exhale phases of the 4DCT dataset. Following spatial registration, corresponding Hounsfield units were input into a density-change-based model for quantifying the local ventilation. The ventilation data for all weeks were registered to the pretreatment ventilation image set. We quantitatively analyzed the data by defining regions of interest (ROIs) according to dose (V(20)) and lung lobe and by tracking the weekly ventilation of each ROI throughout treatment. The slope of the linear fit to the weekly ventilation data was used to evaluate the change in ventilation throughout treatment. A positive slope indicated an increase in ventilation, a negative slope indicated a decrease in ventilation, and a slope of 0 indicated no change. The dose ROI ventilation and slope data were used to study how ventilation changed throughout treatment as a function of dose. The lung lobe ROI ventilation data were used to study the impact of the presence of tumor on pretreatment ventilation. In addition, the lobe ROI data were used to study the impact of tumor reduction on ventilation change throughout treatment. RESULTS Using the dose ROI data, we found that three patients had an increase in weekly ventilation as a function of dose (slopes of 1.1, 1.4, and 1.5) and three patients had no change or a slight decrease in ventilation as a function of dose (slopes of 0.3, -0.6, -0.5). Visually, pretreatment ventilation appeared to be lower in the lobes that contained tumor. Pretreatment ventilation was 39% for lobes that contained tumor and 54% for lobes that did not contain tumor. The difference in ventilation between the two groups was statistically significant (p = 0.017). When the weekly lobe ventilation data were qualitatively observed, two distinct patterns emerged. When the tumor volume in a lobe was reduced, ventilation increased in the lobe. When the tumor volume was not reduced, the ventilation distribution did not change. The average slope of the group of lobes that contained tumors that shrank was 1.18, while the average slope of the group that did not contain tumors (or contained tumors that did not shrink) was -0.32. The slopes for the two groups were significantly different (p = 0.014). CONCLUSIONS We did not find a consistent pattern of ventilation change as a function of radiation dose. Pretreatment ventilation was significantly lower for lobes that contained tumor, due to occlusion of the central airway. The weekly lobe ventilation data indicated that when tumor volume shrinks, ventilation increases, and when the thoracic anatomy is not visibly changed, ventilation is likely to remain unchanged.

Reproducibility of CT Perfusion Parameters in Liver Tumors and Normal Liver

PURPOSE To assess the reproducibility of computed tomographic (CT) perfusion measurements in liver tumors and normal liver and effects of motion and data acquisition time on parameters. MATERIALS AND METHODS Institutional review board approval and written informed consent were obtained for this prospective study. The study complied with HIPAA regulations. Two CT perfusion scans were obtained 2-7 days apart in seven patients with liver tumors with two scanning phases (phase 1: 30-second breath-hold cine; phase 2: six intermittent free-breathing cines) spanning 135 seconds. Blood flow (BF), blood volume (BV), mean transit time (MTT), and permeability-surface area product (PS) for tumors and normal liver were calculated from phase 1 with and without rigid registration and, for combined phases 1 and 2, with manually and rigid-registered phase 2 images, by using deconvolution modeling. Variability was assessed with within-patient coefficients of variation (CVs) and Bland-Altman analyses. RESULTS For tumors, BF, BV, MTT, and PS values and reproducibility varied by analytical method, the former by up to 11%, 23%, 21%, and 138%, respectively. Median PS values doubled with the addition of phase 2 data to phase 1 data. The best overall reproducibility was obtained with rigidly registered phase 1 and phase 2 images, with within-patient CVs for BF, BV, MTT, and PS of 11.2%, 14.4%, 5.5% and 12.1%, respectively. Normal liver evaluations were similar, except with marginally lower variability. CONCLUSION Absolute values and reproducibility of CT perfusion parameters were markedly influenced by motion and data acquisition time. PS, in particular, probably requires data acquisition beyond a single breath hold, for which motion-correction techniques are likely necessary.

Reproducibility of Perfusion Parameters Obtained From Perfusion CT in Lung Tumors

OBJECTIVE The purpose of this article is to assess the variability of perfusion CT measurements in lung tumors and the effects of motion and duration of data acquisition on perfusion CT parameter values. SUBJECTS AND METHODS Two perfusion CT scans were obtained in 11 patients with lung tumors, 2-7 days apart, using phase 1 scans (30-second breath-hold cine) followed by phase 2 scans (six intermittent helical breath-holds), spanning 125 seconds. Tumor blood flow (BF), blood volume (BV), mean transit time (MTT), and permeability were calculated for phase 1 using all-cine and motion-corrected (rigidly registered) images, both with and without matching phase 2 images (manually or rigidly registered). Variability was assessed by the within-patient coefficient of variation (CV) and Bland-Altman analyses. RESULTS BF, BV, MTT, and permeability values varied widely by method of analysis (median BF, 45.3-65.1 mL/min/100 g; median BV, 2.6-3.8 mL/100 g; median MTT, 3.6-4.1 seconds, and median permeability, 13.7-39.3 mL/min/100 g), as did within-patient CVs (10.9-114.4%, 25.3-117.6%, 22.3-51.5%, and 29.6-134.9%, respectively). Parameter values and variability were affected by motion and duration of data analyzed: permeability values doubled when phase 2 images were added to phase 1 data. Overall, the best reproducibility was obtained with registered phase 1 and 2 data, with within-patient CVs of 11.6%, 26.5%, 45.4%, and 30.2%, respectively. CONCLUSION The absolute values and reproducibility of perfusion parameters in lung tumors are markedly influenced by motion and duration of data acquisition. Permeability, in particular, probably requires data acquisition beyond a single breath-hold. The smallest variability in parameter values was obtained with motion correction and extended acquisition durations.

Metastases to the Liver from Neuroendocrine Tumors: Effect of Duration of Scan Acquisition on CT Perfusion Values

PURPOSE To assess the effects of acquisition duration on computed tomographic (CT) perfusion parameter values in neuroendocrine liver metastases and normal liver tissue. MATERIALS AND METHODS This retrospective study was institutional review board approved, with waiver of informed consent. CT perfusion studies in 16 patients (median age, 57.5 years; range, 42.0-69.7 years), including six men (median, 54.1 years; range, 42.0-69.7), and 10 women (median, 59.3 years; range 43.6-66.3), with neuroendocrine liver metastases were analyzed by means of distributed parametric modeling to determine tissue blood flow, blood volume, mean transit time, permeability, and hepatic arterial fraction for tumors and normal liver tissue. Analyses were undertaken with acquisition time of 12-590 seconds. Nonparameteric regression analyses were used to evaluate the functional relationships between CT perfusion parameters and acquisition duration. Evidence for time invariance was evaluated for each parameter at multiple time points by inferring the fitted derivative to assess its proximity to zero as a function of acquisition time by using equivalence tests with three levels of confidence (20%, 70%, and 90%). RESULTS CT perfusion parameter values varied, approaching stable values with increasing acquisition duration. Acquisition duration greater than 160 seconds was required to obtain at least low confidence stability in any of the CT perfusion parameters. At 160 seconds of acquisition, all five CT perfusion parameters stabilized with low confidence in tumor and normal tissues, with the exception of hepatic arterial fraction in tumors. After 220 seconds of acquisition, there was stabilization with moderate confidence for blood flow, blood volume, and hepatic arterial fraction in tumors and normal tissue, and for mean transit time in tumors; however, permeability values did not satisfy the moderate stabilization criteria in both tumors and normal tissue until 360 seconds of acquisition. Blood flow, mean transit time, permeability, and hepatic arterial fraction were significantly different between tumor and normal tissue at 360 seconds (P < .001). CONCLUSION CT perfusion parameter values are affected by acquisition duration and approach progressively stable values with increasing acquisition times. Online supplemental material is available for this article.

Semiautomated Motion Correction of Tumors in Lung CT-perfusion Studies

RATIONALE AND OBJECTIVES To compare the relative performance of one-dimensional (1D) manual, rigid-translational, and nonrigid registration techniques to correct misalignment of lung tumor anatomy acquired from computed tomography perfusion (CTp) datasets. MATERIALS AND METHODS Twenty-five datasets in patients with lung tumors who had undergone a CTp protocol were evaluated. Each dataset consisted of one reference CT image from an initial cine slab and six subsequent breathhold helical volumes (16-row multi-detector CT), acquired during intravenous contrast administration. Each helical volume was registered to the reference image using two semiautomated intensity-based registration methods (rigid-translational and nonrigid), and 1D manual registration (the only registration method available in the relevant application software). The performance of each technique to align tumor regions was assessed quantitatively (percent overlap and distance of center of mass), and by a visual validation study (using a 5-point scale). The registration methods were statistically compared using linear mixed and ordinal probit regression models. RESULTS Quantitatively, tumor alignment with the nonrigid method compared to rigid-translation was borderline significant, which in turn was significantly better than the 1D manual method: average (± SD) percent overlap, 91.8 ± 2.3%, 87.7 ± 5.5%, and 77.6 ± 5.9%, respectively; and average (± SD) DCOM, 0.41 ± 0.16 mm, 1.08 ± 1.13 mm, and 2.99 ± 2.93 mm, respectively (all P < .0001). Visual validation confirmed these findings. CONCLUSION Semiautomated registration methods achieved superior alignment of lung tumors compared to the 1D manual method. This will hopefully translate into more reliable CTp analyses.

Validation of motion correction techniques for liver CT perfusion studies

OBJECTIVES Motion in images potentially compromises the evaluation of temporally acquired CT perfusion (CTp) data; image registration should mitigate this, but first requires validation. Our objective was to compare the relative performance of manual, rigid and non-rigid registration techniques to correct anatomical misalignment in acquired liver CTp data sets. METHODS 17 data sets in patients with liver tumours who had undergone a CTp protocol were evaluated. Each data set consisted of a cine acquisition during a breath-hold (Phase 1), followed by six further sets of cine scans (each containing 11 images) acquired during free breathing (Phase 2). Phase 2 images were registered to a reference image from Phase 1 cine using two semi-automated intensity-based registration techniques (rigid and non-rigid) and a manual technique (the only option available in the relevant vendor CTp software). The performance of each technique to align liver anatomy was assessed by four observers, independently and blindly, on two separate occasions, using a semi-quantitative visual validation study (employing a six-point score). The registration techniques were statistically compared using an ordinal probit regression model. RESULTS 306 registrations (2448 observer scores) were evaluated. The three registration techniques were significantly different from each other (p=0.03). On pairwise comparison, the semi-automated techniques were significantly superior to the manual technique, with non-rigid significantly superior to rigid (p<0.0001), which in turn was significantly superior to manual registration (p=0.04). CONCLUSION Semi-automated registration techniques achieved superior alignment of liver anatomy compared with the manual technique. We hope this will translate into more reliable CTp analyses.

Differentiation of low-attenuation intracranial hemorrhage and calcification using dual-energy computed tomography in a phantom system.

ObjectivesCalcific and hemorrhagic intracranial lesions with attenuation levels of less than 100 Hounsfield units (HUs) cannot currently be reliably differentiated by single-energy computed tomography (SECT). The proper differentiation of these lesion types would have a multitude of clinical applications. A phantom model was used to test the ability of dual-energy CT (DECT) to differentiate such lesions. Materials and MethodsAgar gel-bound ferric oxide and hydroxyapatite were used to model hemorrhage and calcification, respectively. Gel models were scanned using SECT and DECT and organized into SECT attenuation-matched pairs at 16 attenuation levels between 0 and 100 HU. Dual-energy CT data were analyzed using 3-dimensional (3D) Gaussian mixture models (GMMs), as well as a simplified threshold plane metric derived from the 3D GMM, to assign voxels to hemorrhagic or calcific categories. Accuracy was calculated by comparing predicted voxel assignments with actual voxel identities. ResultsWe measured 6032 voxels from each gel model, for a total of 193,024 data points (16 matched model pairs). Both the 3D GMM and its more clinically implementable threshold plane derivative yielded similar results, with higher than 90% accuracy at matched SECT attenuation levels of 50 HU and greater. ConclusionsHemorrhagic and calcific lesions with attenuation levels between 50 and 100 HU were differentiable using DECT in a clinically relevant phantom system with higher than 90% accuracy. This method warrants further testing for potential clinical applications.

Dual-Energy Computed Tomography for the Characterization of Intracranial Hemorrhage and Calcification: A Systematic Approach in a Phantom System.

Objective The aim of this study was to develop a diagnostic framework for distinguishing calcific from hemorrhagic cerebral lesions using dual-energy computed tomography (DECT) in an anthropomorphic phantom system. Materials and Methods An anthropomorphic phantom was designed to mimic the CT imaging characteristics of the human head. Cylindrical lesion models containing either calcium or iron, mimicking calcification or hemorrhage, respectively, were developed to exhibit matching, and therefore indistinguishable, single-energy CT (SECT) attenuation values from 40 to 100 HU. These lesion models were fabricated at 0.5, 1, and 1.5 cm in diameter and positioned in simulated cerebrum and skull base locations within the anthropomorphic phantom. All lesion sizes were modeled in the cerebrum, while only 1.5-cm lesions were modeled in the skull base. Images were acquired using a GE 750HD CT scanner and an expansive dual-energy protocol that covered variations in dose (36.7–132.6 mGy CTDIvol, n = 12), image thickness (0.625–5 mm, n = 4), and reconstruction filter (soft, standard, detail, n = 3) for a total of 144 unique technique combinations. Images representing each technique combination were reconstructed into water and calcium material density images, as well as a monoenergetic image chosen to mimic the attenuation of a 120-kVp SECT scan. A true single-energy routine brain protocol was also included for verification of lesion SECT attenuation. Points representing the 3 dual-energy reconstructions were plotted into a 3-dimensional space (water [milligram/milliliter], calcium [milligram/milliliter], monoenergetic Hounsfield unit as x, y, and z axes, respectively), and the distribution of points analyzed using 2 approaches: support vector machines and a simple geometric bisector (GB). Each analysis yielded a plane of optimal differentiation between the calcification and hemorrhage lesion model distributions. By comparing the predicted lesion composition to the known lesion composition, we identified the optimal combination of CTDIvol, image thickness, and reconstruction filter to maximize differentiation between the lesion model types. To validate these results, a new set of hemorrhage and calcification lesion models were created, scanned in a blinded fashion, and prospectively classified using the planes of differentiation derived from support vector machine and GB methods. Results Accuracy of differentiation improved with increasing dose (CTDIvol) and image thickness. Reconstruction filter had no effect on the accuracy of differentiation. Using an optimized protocol consisting of the maximum CTDIvol of 132.6 mGy, 5-mm-thick images, and a standard filter, hemorrhagic and calcific lesion models with equal SECT attenuation (Hounsfield unit) were differentiated with over 90% accuracy down to 70 HU for skull base lesions of 1.5 cm, and down to 100 HU, 60 HU, and 60 HU for cerebrum lesions of 0.5, 1.0, and 1.5 cm, respectively. The analytic method that yielded the best results was a simple GB plane through the 3-dimensional DECT space. In the validation study, 96% of unknown lesions were correctly classified across all lesion sizes and locations investigated. Conclusions We define the optimal scan parameters and expected limitations for the accurate classification of hemorrhagic versus calcific cerebral lesions in an anthropomorphic phantom with DECT. Although our proposed DECT protocol represents an increase in dose compared with routine brain CT, this method is intended as a specialized evaluation of potential brain hemorrhage and is thus counterbalanced by increased diagnostic benefit. This work provides justification for the application of this technique in human clinical trials.

Effect of Sampling Frequency on Perfusion Values in Perfusion CT of Lung Tumors

OBJECTIVE The purpose of this study was to assess as a potential means of limiting radiation exposure the effect on perfusion CT values of increasing sampling intervals in lung perfusion CT acquisition. SUBJECTS AND METHODS Lung perfusion CT datasets in patients with lung tumors (> 2.5 cm diameter) were analyzed by distributed parameter modeling to yield tumor blood flow, blood volume, mean transit time, and permeability values. Scans were obtained 2-7 days apart with a 16-MDCT scanner without intervening therapy. Linear mixed-model analyses were used to compare perfusion CT values for the reference standard sampling interval of 0.5 second with those of datasets obtained at sampling intervals of 1, 2, and 3 seconds, which included relative shifts to account for uncertainty in preenhancement set points. Scan-rescan reproducibility was assessed by between-visit coefficient of variation. RESULTS Twenty-four lung perfusion CT datasets in 12 patients were analyzed. With increasing sampling interval, mean and 95% CI blood flow and blood volume values were increasingly overestimated by up to 14% (95% CI, 11-18%) and 8% (95% CI, 5-11%) at the 3-second sampling interval, and mean transit time and permeability values were underestimated by up to 11% (95% CI, 9-13%) and 3% (95% CI, 1-6%) compared with the results in the standard sampling interval of 0.5 second. The differences were significant for blood flow, blood volume, and mean transit time for sampling intervals of 2 and 3 seconds (p ≤ 0.0002) but not for the 1-second sampling interval. The between-visit coefficient of variation increased with subsampling for blood flow (32.9-34.2%), blood volume (27.1-33.5%), and permeability (39.0-42.4%) compared with the values in the 0.5-second sampling interval (21.3%, 23.6%, and 32.2%). CONCLUSION Increasing sampling intervals beyond 1 second yields significantly different perfusion CT parameter values compared with the reference standard (up to 18% for 3 seconds of sampling). Scan-rescan reproducibility is also adversely affected.

Effect of dual vascular input functions on CT perfusion parameter values and reproducibility in liver tumors and normal liver

Objective To assess the impact on absolute values and reproducibility of adding portal venous (PV) to arterial input functions in computed tomographic perfusion (CTp) evaluations of liver tumors and normal liver. Methods Institutional review board approval and written informed consent were obtained; the study complied with Health Insurance Portability and Accountability Act regulations. Computed tomographic perfusion source data sets, obtained from 7 patients (containing 9 liver tumors) on 2 occasions, 2 to 7 days apart, were analyzed by deconvolution modeling using dual (“Liver” protocol: PV and aorta) and single (“Body” protocol: aorta only) vascular inputs. Identical tumor, normal liver, aortic and, where applicable, PV regions of interest were used in corresponding analyses to generate tissue blood flow (BF), blood volume (BV), mean transit time (MTT), and permeability (PS) values. Test-retest variability was assessed by within-patient coefficients of variation. Results For liver tumor and normal liver, median BF, BV, and PS were significantly higher for the Liver protocol than for the Body protocol: 171.3 to 177.8 vs 39.4 to 42.0 mL/min per 100 g, 17.2 to 18.7 vs 3.1 to 4.2 mL/100 g, and 65.1 to 78.9 vs 50.4 to 66.1 mL/min per 100 g, respectively (P < 0.01 for all). There were no differences in MTT between protocols. Within-patient coefficients of variation were lower for all parameters with the Liver protocol than with the Body protocol: BF, 7.5% to 11.2% vs 11.7% to 20.8%; BV, 10.1% to 14.4% vs 16.6% to 30.1%; MTT, 4.2% to 5.5% vs 10.4% to 12.9%; and PS, 7.3% to 12.1% vs 12.6% to 20.3%, respectively. Conclusion Utilization of dual vascular input CTp liver analyses has substantial impact on absolute CTp parameter values and test-retest variability. Incorporation of the PV inputs may yield more precise results; however, it imposes substantial practical constraints on acquiring the necessary data.