Comparison of early radiological predictors of outcome in patients with colorectal cancer with unresectable hepatic metastases treated with bevacizumab.

OBJECTIVE: The purpose was to validate the prognostic value of an early optimal morphological response on CT in patients treated with bevacizumab-containing chemotherapy for unresectable colorectal cancer liver metastases (CLM). It also evaluated the prognostic value of size-based criteria and the association of optimal morphological response with the receipt of bevacizumab. DESIGN: 141 patients treated first using bevacizumab and 142 patients from a randomised study evaluating the addition of bevacizumab to oxaliplatin-based chemotherapy were retrospectively analysed. Radiologists evaluated pretreatment and restaging CT scans using morphological response criteria. Responses were also assessed with size-based criteria: Response Evaluation Criteria in Solid Tumors (RECIST), early tumour shrinkage (ETS) and deepness of response (DpR). The ability of each criterion to predict progression-free survival (PFS), overall survival (OS) and postprogression survival (PPS) was determined using a univariate Cox proportional hazards model. RESULTS: In both populations, median PFS was significantly longer for patients achieving an optimal morphological response (10.4 vs 6.8 months, p=0.03; and 8.3 vs 4.9 months, p<00001, respectively). Neither RECIST nor ETS responses were associated with a prolonged PFS. Median OS was longer for those with an optimal morphological response but only at second restaging in the first population (n=141, 20.8 vs 12.3 months, p=0.002). DpR but not optimal morphological response was associated with PPS. In the randomised study, an optimal morphological response was 6.2 times more likely among patients receiving bevacizumab (p<0.0001). CONCLUSION: In patients with unresectable CLM, early morphological response may be a better predictor of PFS than size-based response. The addition of bevacizumab improves morphological response rate.

Effect on perfusion values of sampling interval of computed tomographic perfusion acquisitions in neuroendocrine liver metastases and normal liver.

OBJECTIVE: This study aimed to assess the effects of sampling interval (SI) of computed tomographic (CT) perfusion acquisitions on CT perfusion values in normal liver and liver metastases from neuroendocrine tumors. METHODS: Computed tomographic perfusion in 16 patients with neuroendocrine liver metastases was analyzed using distributed-parameter modeling to yield tissue blood flow, blood volume, mean transit time, permeability, and hepatic arterial fraction for tumor and normal liver. Computed tomographic perfusion values for the reference SI of 0.5 s (SI0.5) were compared with those of SI data sets of 1 second, 2 seconds, 3 seconds, and 4 seconds using mixed-effects model analyses. RESULTS: Increases in SI beyond 1 second were associated with significant and increasing departures of CT perfusion parameters from the reference values at SI0.5 (P ≤ 0.0009). Computed tomographic perfusion values deviated from the reference with increasing uncertainty with increasing SIs. Findings for normal liver were concordant. CONCLUSIONS: Increasing SIs beyond 1 second yield significantly different CT perfusion parameter values compared with the reference values at SI0.5.

Effect of pre-enhancement set point on computed tomographic perfusion values in normal liver and metastases to the liver from neuroendocrine tumors.

OBJECTIVE: The objective of this study was to assess the effects of pre-enhancement set point (T1) positioning on computed tomographic perfusion (CTp) parameter values. METHODS: The CTp data from 16 patients with neuroendocrine liver metastases were analyzed with distributed parameter modeling to yield tissue blood flow (BF), blood volume, mean transit time, permeability, and hepatic arterial fraction for tumor and normal liver, with displacements in T1 of ±0.5, ±1.0, ±2.0 seconds, relative to the reference standard. A linear mixed-effects model was used to assess the displacement effects. RESULTS: Effects on the CTp parameter values were variable: BF was not significantly affected, but T1 positions of ≥+1.0 second and -2.0 seconds or longer significantly affected the other CTp parameters (P ≤ 0.004). Mean differences in the CTp parameter values versus the reference standard for BF, blood volume, mean transit time, permeability, and hepatic arterial fraction ranged from -5.0% to 5.2%, -12.7% to 8.9%, -12.5% to 8.1%, -5.3% to 5.7%, and -12.9% to 26.0%, respectively. CONCLUSIONS: CTp parameter values can be significantly affected by T1 positioning.

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.

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.

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.

Observer Variability in CT Perfusion Parameters in Primary and Metastatic Tumors in the Lung.

PURPOSE: Evaluate observer variability in computed tomography perfusion measurements in lung tumors and assess the relative contributions of individual factors to overall variability. MATERIALS AND METHODS: Four observers independently delineated tumor and defined arterial input function region of interests (tumor region of interest and arterial input function region of interest) on each of 4 contiguous slice levels of computed tomography perfusion images (arterial input function level), in 12 computed tomography perfusion data sets containing lung tumors (>2.5 cm size), on 2 separate occasions. Computed tomography perfusion parameters (blood flow, blood volume, mean transit time, and permeability surface area product) for tumor volumes of interest were computed for all combinations of these factors, totaling up to 1024 combinations per patient. Overall, inter- and intraobserver variability were assessed by within-patient coefficient of variation, variance components analyses, and intraclass correlation. RESULTS: Overall observer within-patient coefficient of variations for tumor blood flow, blood volume, mean transit time, and permeability surface area product were 20.3%, 11.9%, 6.3%, and 31.7%, and intraclass correlations were 0.94, 0.91, 0.82, and 0.72, respectively. Interobserver tumor volume of interest and arterial input function level were the highest contributors to overall variance for blood flow, blood volume, and mean transit time. Overall intraobserver wCVs for blood flow, blood volume, mean transit time, and permeability surface area product (4.3%, 2.4%, 0.9%, and 3.1%) were smaller than interobserver within-patient coefficient of variations (9.5%, 5.6%, 1.6%, and 7.0%), respectively. CONCLUSION: The largest contributors to observer variability were interobserver tumor volume of interest and arterial input function level. Overall variability in computed tomography perfusion studies can potentially be minimized by using a single observer and a consistent level for arterial input function, which would be important considerations in longitudinal and multicenter studies. Methods to reliably define arterial input function and delineate tumor volumes would help to reduce variability in estimations of computed tomography perfusion parameter values.

Effect of duration of scan acquisition on CT perfusion parameter values in primary and metastatic tumors in the lung.

OBJECTIVES: To assess the effect of acquisition duration (T(acq)) and pre-enhancement set points (T1) on computer tomography perfusion (CT(p)) parameter values in primary and metastatic tumors in the lung. MATERIALS AND METHODS: 24 lung CT(p) datasets (10 primary; 14 metastatic), acquired using a two phase protocol spanning 125 s, in 12 patients with lung tumors, were analyzed by deconvolution modeling to yield tumor blood flow (BF), blood volume (BV), mean transit time (MTT), and permeability (PS) values. CT(p) analyses were undertaken for the reference dataset (i.e., T1=t0) with varying T(acq) from 12 to 125 s. This was repeated for shifts in T1 (±0.5 s, ±1.0 s, ±2.0 s relative to the reference at t0). Resultant CTp values were plotted against T(acq); values at 30 s, 50 s, 65 s and 125 s were compared using linear mixed model. RESULTS: All CT(p) parameter values were noticeably influenced by T(acq), with generally less marked changes beyond 50 s, and with no difference in behavior between primary and secondary tumors. Apart from BV, which attained a plateau at approximately 50s, the other three CT(p) parameters did not reach steady-state values within the available 125 s of data, with values at 30 s, 50 s and 65 s significantly different from 125 s (p<0.004). Shifts in T1 also affected the CT(p) parameters values, with positive shifts having greater impact on CT(p) values than negative shifts. CONCLUSION: CT(p) parameter values derived from deconvolution modeling can be markedly affected by T(acq), and pre-enhancement set-points. 50 s acquisition may be adequate for BV, but longer than 125 s is probably required for reliable characterization of the other three CT(p) parameters.

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.

Body surface area and body weight predict total liver volume in Western adults.

Computed tomography (CT) is used increasingly to measure liver volume in patients undergoing evaluation for transplantation or resection. This study is designed to determine a formula predicting total liver volume (TLV) based on body surface area (BSA) or body weight in Western adults. TLV was measured in 292 patients from four Western centers. Liver volumes were calculated from helical computed tomographic scans obtained for conditions unrelated to the hepatobiliary system. BSA was calculated based on height and weight. Each center used a different established method of three-dimensional volume reconstruction. Using regression analysis, measurements were compared, and formulas correlating BSA or body weight to TLV were established. A linear regression formula to estimate TLV based on BSA was obtained: TLV = -794.41 + 1,267.28 x BSA (square meters; r(2) = 0.46; P <.0001). A formula based on patient weight also was derived: TLV = 191.80 + 18.51 x weight (kilograms; r(2) = 0.49; P <.0001). The newly derived TLV formula based on BSA was compared with previously reported formulas. The application of a formula obtained from healthy Japanese individuals underestimated TLV. Two formulas derived from autopsy data for Western populations were similar to the newly derived BSA formula, with a slight overestimation of TLV. In conclusion, hepatic three-dimensional volume reconstruction based on helical CT predicts TLV based on BSA or body weight. The new formulas derived from this correlation should contribute to the estimation of TLV before liver transplantation or major hepatic resection.