Two-Volume Dynamic CT Pulmonary Perfusion: Contrast Timing Optimization

Purpose: To develop and validate an optimal timing protocol for a low-radiation-dose CT pulmonary perfusion technique using only two volume scans. Methods: A total of 24 swine (48.5±14.3 kg) underwent contrast-enhanced dynamic CT. Multiple contrast injections were made under different pulmonary perfusion conditions, resulting in a total of 147 complete pulmonary arterial input functions(AIF). Using the AIFs, an optimal timing protocol for acquisition of two-volume scans was developed for the first-pass CT perfusion technique. Specifically, the first volume scan was obtained at the base of the AIF using bolus-tracking and the second volume scan was obtained at the peak of the AIF using a time-to-peak relation derived by regression analysis. Additionally, a subset of 14 swine with 60 CT acquisitions were used to validate the prospective timing protocol. The prospective perfusion measurements using the two-volume scans, were quantitatively compared to the retrospective perfusion measurements using the entire AIF with t-test, linear regression and Bland-Altman analysis. The CT dose index( CTDI vol32 ) and size-specific dose estimate(SSDE) of the two-volume perfusion technique were also determined. Results: The pulmonary artery time-to-peak ( 𝑇 𝑃𝐴 ) was related to one-half of the contrast injection duration( 𝑇 𝐼𝑛𝑗 2 ) by 𝑇 𝑃𝐴 = 1.06 𝑇 𝐼𝑛𝑗 2 + 0.90 (r=0.97). Simulated prospective two-volume perfusion measurements (P PRO ) in ml/min/g were related to the retrospective measurements (P RETRO ) by P PRO = 0.87P RETRO + 0.56 (r=0.88). The CTDI vol32 and SSDE of the two-volume CT technique were estimated to be 28.4 and 47.0mGy, respectively. Conclusion: The optimal timing protocol can enable an accurate, low-radiation-dose two-volume dynamic CT perfusion technique. an optimal timing protocol for a low-dose, two-volume dynamic CT pulmonary perfusion technique was retrospectively validated in 24 swine using pulmonary arterial AIF characterization and a first-pass analysis perfusion technique. Using dynamic bolus-tracking and time-to-peak delay estimation, the optimal timing protocol resulting in robust acquisition of the first volume scan at the base of the AIF and the second volume scan at the peak of AIF. Such finding enables a practical, low-dose, two-volume dynamic CT perfusion technique that may


Introduction
Computed tomography (CT) has enabled the non-invasive quantification of pulmonary perfusion allowing for the assessment of pulmonary embolism and pulmonary hypertension [1][2][3][4][5]. Existing dynamic CT perfusion techniques require the entire contrast pass curve over many cardiac cycles for perfusion measurement, resulting in high radiation dose [6,2,7,8,3]. Moreover, the pulmonary perfusion measured by such techniques is known to be underestimated due to the use of small tissue volumes for measurement [9][10][11]. Although dual-energy CT iodine map is also used to depict pulmonary perfusion defects, it has limited contrast-to-noise ratio and cannot provide absolute pulmonary blood flow [12][13][14][15]. Hence, an accurate, low-dose dynamic CT perfusion technique is necessary for improved physiological assessment of pulmonary disease.
Fortunately, previous studies have demonstrated that accurate cardiac and pulmonary perfusion measurement is feasible with a first-pass analysis (FPA) technique using only two volume scans [9][10][11]: one at the base (V1) and one at the peak (V2) of the arterial input function (AIF). Nevertheless, these prior validations required the entire AIF curve and retrospectively down-sampled to two volume scans for blood flow measurement. Hence, a timing protocol for the true prospective implementation of two-volume FPA technique remains necessary, where such protocol can also account for different hemodynamic conditions and cardiac outputs [16,17].
Thus, the purpose of this study is to develop an optimal timing protocol for the prospective two-volume FPA dynamic CT pulmonary perfusion technique. The central hypothesis is that the time interval between the two volume scans can be pre-determined using the contrast injection parameters and an empirical time constant. Finally, using the proposed timing protocol, the accuracy of the two-volume prospective FPA dynamic CT perfusion technique was assessed as compared to the previously validated retrospective FPA perfusion technique [11]. : The study was approved by the Institutional Animal Care and Use Committee (IACUC, Protocol   Number: AUP-18-191). A total of 24 male Yorkshire swine (48.5±14.3 kg) were used with 154 contrast injections, where seven were excluded due to injection failures (Fig 1). In total, 147 successful contrast injections were used to retrospectively develop an optimal timing protocol for the two-volume perfusion technique (Fig 1). The time-topeak delay between V1 and V2 was predicted using the contrast injection duration and a dispersion time constant.

General Method
Finally, using the predicted time-to-peak, prospective acquisition of V1 and V2 was simulated in a subset of fourteen swine, where the accuracy of the two-volume prospective technique was compared to the previously validated retrospective perfusion measurement [11]. All experimental data was prospectively acquired by all authors  Table 1. ECG-gated dynamic scanning was then performed with a 320-slice CT scanner (Aquilion One, Canon America Medical Systems, Tustin, CA) for approximately 30 cardiac cycles during a ventilator-controlled inspiratory breath hold. The following scan parameters were used: tube voltage, 100 kVp; tube current, 200mA; detector collimation, 320 x 0.5 mm; volume scanning mode; gantry rotation time, 0.35 seconds; slice thickness, 0.5 mm; scan field-of-view, 240-400 mm; voxel raster, 512×512; and a FC07 soft tissue reconstruction kernel with AIDR3D iterative reconstruction. A 20-minute time delay was used between all acquisitions to allow for adequate contrast material recirculation and redistribution.

Bolus Characterization and Time-to-Peak Delay Estimation:
Bolus tracking is commonly used to detect the contrast arrival time within a region of interest in a monitoring artery. A fixed time delay is then used to estimate the time to peak of the contrast bolus. In this study, we will use a patient-specific time to peak estimation. Prior to recirculation phase of the contrast agent bolus passage, the geometry of the arterial input function (AIF) is predominantly determined by the contrast bolus injection geometry and the bolus dispersion within the circulatory system, given a short contrast injection duration(< 15 seconds) [18,17]. Specifically, the initial approximate rectangular geometry of an undiluted contrast bolus injection will dilute and disperse into a contrast pass curve, where the area under the curve remains conserved and the width of the curve remains proportional to the amount of the contrast volume injected at a fixed rate [19,20]. Moreover, despite contrast mixing and hemodynamic perturbation, the dispersion of the bolus primarily occurs at its temporal edges or tails; hence, the center of the AIF has the maximal contrast attenuation. As such, we investigated the possibility of relating one-half the contrast bolus injection time ( ⁄ ) and the time-to-peak delay ( ) of the AIF (Fig 2). In this study, such a relation was derived using the known contrast injection duration and the time-to-peak delay from the AIF, as described in Eq 1. An empirically derived dispersion delay ( ) time constant was also introduced to describe the degree of the contrast bolus mixing. Such a factor is proportional to the physical distance between the contrast injection site and vessel of interest used for the AIF generation (Eq 1) where is the coefficient of the relation between one-half the injection time ( ⁄ ) and the time-to-peak ( ), is the dispersion delay time constant.

Data Pre-Processing:
The images from each contrast-enhanced CT acquisition were first registered using a nonrigid algorithm [21]. Regions-of-interest were placed in the right ventricle, pulmonary artery, and descending aorta to generate arterial input functions (AIFs, Fig 2). Next, a gamma-variate fitting (LSQCurveFit; Matlab 2013a, MathWorks) was performed on each dataset to generate smooth continuous AIF curves. Next, the 3D lung parenchyma was semi-automatically segmented using a standard commercial software (ViTAL Images, Lung CT, Pulmonary Analysis Workflow; Canon Medical Systems) and was used for the whole-lung FPA perfusion measurement. Further, 3D-segmentted binary masks of approximately 800-1400 mm 3 were generated to measure regional perfusion. In summary, nine segments were assessed for each animal, including one segment for the left cranial lobe, left lingula lobe, right cranial lobe, right middle lobe, and accessory lobe; two segments for the left and right caudal lobes.
Optimal Retrospective Protocol: Using the continuous AIF curve by the gamma variate fitting, the optimal acquisition timing for the baseline volume scan (V1) was defined as the peak of the second derivative, indicating the AIF curve starts to rise (Fig 2). The optimal acquisition timing for the second volume scan (V2) was then defined as the true peak of the gamma variate fit. The time-to-peak delay between V1 and V2 was then computed and then averaged over multiple acquisitions in each animal. The average time-to-peak delay was related to one-half of the contrast injection time through regression analysis for both pulmonary artery and descending aorta.

Prospective Protocol Simulation:
Bolus-tracking (SureStart, Aquilion One, Canon Medical Systems, Tustin, CA) was simulated for the prospective acquisition of the first volume scan (V1) at the base of the pulmonary artery AIF.
There is a minimal time delay of approximately 2 seconds between trigger during bolus-tracking and acquisition of the first volume scan [17]. Therefore, in order to acquire V1 early during pulmonary artery contrast enhancement, the monitoring region-of-interest was placed in the right ventricle (RV) instead of the pulmonary artery to acquire V1 at low contrast enhancement in pulmonary artery (Fig 2). Further, in order to define the baseline enhancement of the blood pool, a minimum of three pre-contrast images were used to emulate bolus-tracking. Multiple offset thresholds above the baseline, e.g. 40, 60, 80, 100, 120 and 140 HU, were compared to optimize the acquisition of V1. In addition, the second volume scan (V2) was automatically chosen using the predicted time-to-peak delay that was defined in Eq1. Hence, the prospective timing protocol simulation is summarized in Eq2 and Eq3 as: where and are the acquisition time of the V1 and V2, is the triggering time determined by bolustracking in RV, is the transition delay between the trigger of bolus-tracking and the acquisition of V1, and is the predicted time-to-peak between the trigger and the peak of the AIF (Fig 2).

Two-volume FPA CT Perfusion Measurement:
First-pass analysis has previously been used for blood flow measurement [22,23]. Assuming no contrast leakage over the measurement period ([ 1 , 2 ]), the whole-lobe compartment is used to calculate the integrated contrast mass change in the perfusion bed ( /∆ ) between V1 and V2 [9,24]. The average input contrast concentration ( ) of the pulmonary artery is also calculated between V1 and V2 (Fig 3). Thus, the blood flow ( ) measurement is represented by [9,24]: where is the average input concentration, /∆ is the rate of contrast mass change between 1 and 2 , ∆ = 2 − 1 . Finally, the regional perfusion of each 3D-segment is calculated and compared between the prospective and the reference retrospective FPA perfusion techniques, where the retrospective FPA was previously validated against fluorescent microspheres [24].

Cardiac Output Estimation: :
Since the pulmonary circulation carries the entire cardiac output (CO) from the right ventricle to the supply the lung, CO can be approximately estimated by the total pulmonary blood flow [25].
Thus, the cardiac output is the summation of the pulmonary blood flow into all voxels of the lung tissue: Radiation Dose: The CT dose index (CTDI vol 32 , mGy) and the dose-length product (DLP, mGy • cm) were recorded for each two-volume acquisition. Size-specific dose estimates(SSDE, mGy) were also calculated to account for the effective diameter of each swine [26].

Statistical Approach:
For the time-to-peak estimation, the empirical time-to-peak delays in the pulmonary artery and descending aorta were related to one-half the contrast injection time through linear regression analysis, where the root-mean-square-error (RMSE) and root-mean-square-deviation (RMSD) of the function were also calculated.
The V2 acquisition time and contrast enhancement determined by the prospective protocol simulation were then compared with the actual peak time and the actual peak enhancement using paired sample t-testing (SPSS, version 22, IBM, Armonk, NY). Finally, simulated prospective two-volume perfusion measurements were quantitatively compared to the corresponding retrospective perfusion measurements through regression, Bland-Altman, RMSE, RMSD, and Lin's concordance correlation coefficient (CCC).

General Data and Radiation Dose Exposure:
A total of 24 swine with an average weight of 48.5±14.3kg (25-91kg) and an average heart rate of 89.5±15.0 bpm were used for this study. In total, 147 successful injections were included for the time-to-peak prediction study (Fig 1). Overall, the contrast injection durations ranged from 2 to 15 seconds and the cardiac outputs ranged from 1.4 to 5.1 L/min. The average CTDI vol 32 and SSDE for each dynamic perfusion CT acquisition were 258.2 and 427.3mGy, respectively. For prospective perfusion measurement using only two volumes, the average CTDI vol 32 and SSDE were estimated to be 28.4 and 47.0mGy, respectively.

Prospective Protocol Simulation:
A total of 60 CT acquisitions from 14 swine were used for the prospective perfusion measurements with bolus-tracking simulation. For each of the triggering offsets, the pulmonary artery enhancement and acquisition time of the simulated volume scans were compared to the optimal volume scans, as shown in Table 2 and Table 3. To acquire V1 at a relatively low contrast enhancement, the triggering offset of 60HU in the RV was used in this prospective perfusion validation.

Two-Volume FPA CT Perfusion Measurement:
The perfusion assessments were based on a 9-segment model with a total of 540 lung segments. The mean perfusion of the retrospective and the simulated prospective measurements were 8.43±4.54 ml/min/g and 7.84±4.47 ml/min/g (p<0.001), respectively. The simulated prospective FPA perfusion (PPRO) were related to reference retrospective perfusion (PRETRO) measurements by PPRO=0.87PRETRO +0.56 (Pearson's r=0.88, RMSD=0.85 ml/min/g, RMSE=2.29 ml/min/g), with a concordance correlation coefficient of 0.87 (Fig 5a). The corresponding Bland-Altman analyses is also displayed in Fig 5b. The linear regression results of perfusion measurements for individual lobes are shown in Table 4. There is no evident bias between lobes except The perfusion defect by the balloon occlusion can be found in the distal left caudal lobe.

Discussion
In this study, the time-to-peak delay of the pulmonary and aortic AIFs were evaluated in animals with a range of body weights (25-91 kg), contrast doses (20-100mL), injection durations (2-15 seconds), and cardiac outputs (1.4-5.1 L/min). The results indicate that the injection duration is the most significant injection-related parameter impacting the bolus time-to-peak, particularly in the case of short contrast injection duration. Furthermore, the regional perfusion results show good correlation between the simulated prospective FPA measurements and the optimal retrospective FPA measurements. Such findings indicate that the proposed prospective timing protocol can potentially be used for accurate, prospective, two-volume FPA perfusion measurement.
Existing dynamic CT perfusion techniques, such as the maximum slope model and the deconvolution model, require the entire contrast pass curve for perfusion measurement resulting in a high effective radiation dose [27,28,7,29,30,3,31]. Previous reports have shown that the reduction of temporal sampling frequency reduces the accuracies of these current techniques [32]. Although previous reports have shown that the FPA technique can accurately measure the perfusion using only two volume scans as validated using microspheres [11,9], the prospective acquisition of the two volume scans is challenging. Given the findings of this paper, the prospective implementation of the two-volume perfusion technique can be achieved by the optimal timing protocol, enabling the accurate pulmonary perfusion measurement while substantially reducing the radiation dose.
In addition, our results demonstrate that the injection duration can be used to predict the time-to-peak for different injection rates and volumes, and are therefore in agreement with a previous report indicating that the scanning delay for the aortic peak is primarily affected by the injection duration [17]. Such results may also have important implications for optimal CT pulmonary angiography (CTPA), as the optimal time-to-peak delay can be predicted using the contrast injection time interval. Although further validation remains necessary, the proposed time-to-peak prediction may result in an improved contrast opacification in CTPA and visualization of the vasculature.
Finally, previous studies have shown that pulmonary perfusion assessed with dual-energy CT (DECT) iodine density maps can be used for the clinical risk stratification of patients with acute pulmonary embolism [12,33].
Another study reported that the use of DECT perfusion can be a better indicator for balloon pulmonary angioplasty in patients with chronic thromboembolic pulmonary hypertension [15]. A different study has shown that subtraction CT has comparable diagnostic performance to DECT in detection of pulmonary embolism [13]. However, both subtraction CT and DECT do not measure absolute perfusion. On the other hand, the proposed two-volume perfusion quantifies absolute perfusion (in ml/min/g). Quantitative absolute perfusion has the potential for improved assessment of the degree of perfusion defect. Hence, the dynamic two-volume perfusion technique can potentially be an alternative to the standard dynamic perfusion CT by providing functional assessment of pulmonary diseases, such as pulmonary embolism and chronic thromboembolic pulmonary hypertension, at a reduced radiation dose.
This study has several limitations. First, most of the swine used in the study were relatively small as compared to the average size of a patient. Additional studies may be necessary for larger patient sizes (> 90kg) to further validate the dispersion delay time constant robustness. Second, retrospective FPA perfusion measurement was used for validation of the simulated prospective two-volume perfusion measurement. However, the accuracy of the retrospective FPA perfusion technique has previously been validated using fluorescent microspheres as the reference standard [11]. Third, although the time-to-peak prediction has not been validated in patients with various cardiopulmonary conditions (such as acute pulmonary embolism, pulmonary hypertension, and heart failure), the prediction was tested following different levels of occlusion in the pulmonary artery of a swine model. Additionally, such timing protocol remained robust over a wide range of cardiac outputs. Fourth, since the scanner transition delay time is manufacturer-specific, the bolus tracking trigger location and threshold have not been optimized for other CT scanners. A longer scanner transition delay after triggering may result in a late acquisition of V1. This could be a potential reason for the slight underestimation of perfusion using the simulated prospective two-volume protocol.
Alternatively, the contrast arrival time can be pre-determined using a diluted test bolus acquisition [34], although the contrast and radiation dose will be slightly increased. The simulated pharmacokinetic global circulation models can also be helpful in prediction of contrast timing [35]. Finally, the optimal prospective timing protocol was developed and assessed empirically; hence, the diagnostic performance of the two-volume FPA pulmonary perfusion technique with simultaneous CTPA (using the V2 volume scan), will require further studies.
In conclusion, an optimal timing protocol for a low-dose, two-volume dynamic CT pulmonary perfusion technique was retrospectively validated in 24 swine using pulmonary arterial AIF characterization and a first-pass analysis perfusion technique. Using dynamic bolus-tracking and time-to-peak delay estimation, the optimal timing protocol resulting in robust acquisition of the first volume scan at the base of the AIF and the second volume scan at the peak of AIF. Such finding enables a practical, low-dose, two-volume dynamic CT perfusion technique that may  Fig 1: Flowchart of the study. N = number of swine. is the contrast injection duration, is the scanner-specific transition delay (2s), and is the pre-defined time-topeak delay. Bottom, right ventricle (RV) and pulmonary artery (PA) arterial input functions (AIF). and are the acquisition time of the first volume scan (V1) and the second volume scan (V2). The baseline volumes used to emulate the bolus-tracking are shown in blue circles.