Quantitative tumor perfusion assessment with multidetector CT: are measurements from two commercial software packages interchangeable?

Automated Quantitative Analysis of CT Perfusion to Classify Vascular Phenotypes of Pancreatic Ductal Adenocarcinoma

CT perfusion (CTP) analysis is difficult to implement in clinical practice. Therefore, we investigated a novel semi-automated CTP AI biomarker and applied it to identify vascular phenotypes of pancreatic ductal adenocarcinoma (PDAC) and evaluate their association with overall survival (OS).

METHODS

From January 2018 to November 2022, 107 PDAC patients were prospectively included, who needed to undergo CTP and a diagnostic contrast-enhanced CT (CECT). We developed a semi-automated CTP AI biomarker, through a process that involved deformable image registration, a deep learning segmentation model of tumor and pancreas parenchyma volume, and a trilinear non-parametric CTP curve model to extract the enhancement slope and peak enhancement in segmented tumors and pancreas. The biomarker was validated in terms of its use to predict vascular phenotypes and their association with OS. A receiver operating characteristic (ROC) analysis with five-fold cross-validation was performed. OS was assessed with Kaplan-Meier curves. Differences between phenotypes were tested using the Mann-Whitney U test.

RESULTS

The final analysis included 92 patients, in whom 20 tumors (21%) were visually isovascular. The AI biomarker effectively discriminated tumor types, and isovascular tumors showed higher enhancement slopes (2.9 Hounsfield unit HU/s vs. 2.0 HU/s, p < 0.001) and peak enhancement (70 HU vs. 47 HU, p < 0.001); the AUC was 0.86. The AI biomarker's vascular phenotype significantly differed in OS (p < 0.01).

CONCLUSIONS

The AI biomarker offers a promising tool for robust CTP analysis. In PDAC, it can distinguish vascular phenotypes with significant OS prognostication.

Effect of scan duration on CT perfusion values in metastases from renal cell carcinoma

Objective

CT perfusion (CTp) values are affected by CT scan acquisition duration (tacq); their reproducibility is adversely affected by uncertainty in their measurement. The objectives were to assess the effects of tacq on CTp parameter values in metastases from renal cell carcinoma (mRCC) in thoracic and abdominal locations.

Materials and Methods

131 CTp evaluations in 53 patients with mRCC were retrospectively analyzed by distributed parameter modeling to yield tissue blood flow (BF), blood volume (BV), mean transit time (MTT), permeability (PS), and also hepatic arterial perfusion (HAP) and hepatic arterial fraction (HAF) for liver metastases and normal liver, with tacq from 25 to 590 s. Penalized piecewise polynomial regression (SPLINE) characterized functional relationships between CTp parameters and acquisition duration, tacq. Evidence for time-invariance was evaluated for each parameter at multiple time points by conducting inference on the fitted derivative to assess its proximity to zero as a function of acquisition time. Equivalence testing was implemented with three levels of confidence (low (20%), moderate (70%), high (95%)).

Results

Systematic and non-systematic variability was observed for CTp parameter values with limited tacq. All parameters in all locations approached increasing stability with increasing tacq. PS, HAP and HAF required longer acquisition times than BF, BV and MTT to attain comparable levels of stability. Stabilization tended to require longer acquisition in liver than other tissues. tacq=380 s was required to obtain at least moderate level of confidence for all parameters and organs.

Conclusion

Increasing tacq yields increasingly more stable CT perfusion parameters, and thereby better reproducibility.

Evaluation of perfusion CT and dual-energy CT for predicting microvascular invasion of hepatocellular carcinoma

PURPOSE

Evaluation of perfusion CT and dual-energy CT (DECT) quantitative parameters for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC) prior to surgery.

METHODS

This prospective single-center study included fifty-six patients (44 men; median age 67; range 31-84) who provided written informed consent. Inclusion criteria were (1) treatment-naïve patients with a diagnosis of HCC, (2) an indication for hepatic resection, and (3) available arterial DECT phase and perfusion CT (GE revolution HD-GSI). Iodine concentrations (IC), arterial density (AD), and 9 quantitative perfusion parameters for HCC were correlated to pathological results. Radiological parameters based principal component analysis (PCA), corroborated by unsupervised heatmap classification, was meant to deliver a model for predicting MVI in HCC. Survival analysis was performed using univariable log-rank test and multivariable Cox model, both censored at time of relapse.

RESULTS

58 HCC lesions were analyzed (median size 42.3 mm; range of 20-140). PCA showed that the radiological model was predictive of tumor grade (p = 0.01), intratumoral MVI (p = 0.004), peritumoral MVI (p = 0.04), MTM (macrotrabecular-massive) subtype (p = 0.02), and capsular invasion (p = 0.02) in HCC. Heatmap classification of HCC showed tumor heterogeneity, stratified into three main clusters according to the risk of relapse. Survival analysis confirmed that permeability surface-area product (PS) was the only significant independent parameter, among all quantitative tumoral CT parameters, for predicting a risk of relapse (Cox p value = 0.004).

CONCLUSION

A perfusion CT and DECT-based quantitative imaging profile can provide a diagnosis of histological MVI in HCC. PS is an independent parameter for relapse.

CLINICAL TRIALS

ClinicalTrials.gov: NCT03754192.

Comparative analysis of two mathematical algorithms for the calculation of computed tomography perfusion parameters in the healthy and diseased pancreas

BACKGROUND

The maximum slope (MS) and deconvolution (DC) algorithms are commonly used to post-process computed tomography perfusion (CTP) data. This study aims to analyze the differences between MS and DC algorithms for the calculation of pancreatic CTP parameters.

METHODS

The pancreatic CTP data of 57 patients were analyzed using MS and DC algorithms. Two blinded radiologists calculated pancreatic blood volume (BV) and blood flow (BF). Interobserver correlation coefficients were used to evaluate the consistency between two radiologists. Paired t-tests, Pearson linear correlation analysis, and Bland-Altman analysis were performed to evaluate the correlation and consistency of the CTP parameters between the two algorithms.

RESULTS

Among the 30 subjects with normal pancreas, the BV values in the three pancreatic regions were higher in the case of the MS algorithm than in the case of the DC algorithm (t = 39.35, p < 0.001), and the BF values in the three pancreatic regions were slightly higher for the MS algorithm than for the DC algorithm (t = 2.19, p = 0.031). Similarly, among the 27 patients with acute pancreatitis, the BV values obtained using the MS methods were higher than those obtained using the DC methods (t = 54.14, p < 0.001). Furthermore, the BF values were higher with the MS methods than the DC methods (t = 8.45, p < 0.001). Besides, Pearson linear correlation and Bland-Altman analysis showed that the BF and BV values showed a good correlation and a bad consistency between the two algorithms.

CONCLUSIONS

The BF and BV values measured using MS and DC algorithms had a good correlation but were not consistent.

Computed Tomography Perfusion Analysis of Pancreatic Adenocarcinoma using Deconvolution, Maximum Slope, and Patlak Methods - Evaluation of Diagnostic Accuracy and Interchangeability of Cut-Off Values

PURPOSE

 The goal of this study was to evaluate the diagnostic accuracy of perfusion computed tomography (CT) parameters obtained by different mathematical-kinetic methods for distinguishing pancreatic adenocarcinoma from normal tissue. To determine cut-off values and to assess the interchangeability of cut-off values, which were determined by different methods.

MATERIALS AND METHODS

 Perfusion CT imaging of the pancreas was prospectively performed in 23 patients. 19 patients with histopathologically confirmed pancreatic adenocarcinoma were included in the study. Blood flow (BF), blood volume (BV) and permeability-surface area product (PS) were measured in pancreatic adenocarcinoma and normal tissue with the deconvolution (BF, BV, PS), maximum slope (BF), and Patlak methods (BV, PS). The interchangeability of cut-off values was examined by assessing agreement between BF, BV, and PS measured with different mathematical-kinetic methods.

RESULTS

 Bland-Altman analysis demonstrated poor agreement between perfusion parameters, measured with different mathematical-kinetic methods. According to receiver operating characteristic (ROC) analysis, PS measured with the Patlak method had the significantly lowest diagnostic accuracy (area under ROC curve = 0.748). All other parameters were of high diagnostic accuracy (area under ROC curve = 0.940-0.997), although differences in diagnostic accuracy were not statistically different. Cut-off values for BF of ≤ 91.83 ml/100 ml/min and for BV of ≤ 5.36 ml/100 ml, both measured with the deconvolution method, appear to be the most appropriate cut-off values to distinguish pancreatic adenocarcinoma from normal tissue.

CONCLUSION

 Perfusion parameters obtained by different methods are not interchangeable. Therefore, cut-off values, which were determined using different methods, are not interchangeable either. Perfusion parameters can help to distinguish pancreatic adenocarcinoma from normal tissue with high diagnostic accuracy, except for PS measured with the Patlak method.

KEY POINTS

  · Perfusion CT parameters showed high diagnostic accuracy in differentiating between pancreatic adenocarcinoma and normal tissue.. · Only PS measured with the Patlak method showed a significantly lower diagnostic accuracy.. · Perfusion parameters measured with different mathematical-kinetic methods are not interchangeable.. · A specific cut-off value must be determined for each method and each perfusion parameter..

CITATION FORMAT

· Koell M, Klauss M, Skornitzke S et al. Computed Tomography Perfusion Analysis of Pancreatic Adenocarcinoma with the Deconvolution, Maximum Slope, and Patlak Methods - Evaluation of Diagnostic Accuracy and Interchangeability of Cut-Off Values. Fortschr Röntgenstr 2021; 193: 1062 - 1073.

Dynamic perfusion CT - A promising tool to diagnose pancreatic ductal adenocarcinoma

Background and objective

This study deals with an important issue of setting the role and value of the dynamic computed tomography (CT) perfusion analysis in diagnosing pancreatic ductal adenocarcinoma (PDAC). The study aimed to assess the efficacy of perfusion CT in identifying PDAC, even isodense or hardly depicted in conventional multidetector computed tomography.

Methods

A total of 56 patients with PDAC and 56 control group patients were evaluated in this study. A local perfusion assessment, involving the main perfusion parameters, was evaluated for all the patients. Sensitivity, specificity, positive, and negative predictive values for each perfusion CT parameter were defined using cutoff values calculated using receiver operating characteristic curve analysis. We accomplished logistic regression to identify the probability of PDAC.

Results

Blood flow (BF) and blood volume (BV) values were significant independent diagnostic criteria for the presence of PDAC. If both values exceed the determined cutoff point, the estimated probability for the presence of PDAC was 97.69%.

Conclusions

Basic CT perfusion parameters are valuable in providing the radiological diagnosis of PDAC. The estimated BF and BV parameters may serve as independent diagnostic criteria predicting the probability of PDAC.

Comparison of automated beam hardening correction (ABHC) algorithms for myocardial perfusion imaging using computed tomography

PURPOSE

Myocardial perfusion imaging using computed tomography (MPI-CT) and coronary CT angiography (CTA) have the potential to make CT an ideal noninvasive imaging gatekeeper exam for invasive coronary angiography. However, beam hardening can prevent accurate blood flow estimation in dynamic MPI-CT and can create artifacts that resemble flow deficits in single-shot MPI-CT. In this work, we compare four automatic beam hardening correction algorithms (ABHCs) applied to CT images, for their ability to produce accurate single images of contrast and accurate MPI flow maps using images from conventional CT systems, without energy sensitivity.

METHODS

Previously, we reported a method, herein called ABHC-1, where we iteratively optimized a cost function sensitive to beam hardening artifacts in MPI-CT images and used a low order polynomial correction on projections of segmentation-processed CT images. Here, we report results from two new algorithms with higher order polynomial corrections, ABHC-2 and ABHC-3 (with three and seven free parameters, respectively), having potentially better correction but likely reduced estimability. Additionally, we compared results to an algorithm reported by others in the literature (ABHC-NH). Comparisons were made on a digital static phantom with simulated water, bone, and iodine regions; on a digital dynamic anthropomorphic phantom, with simulated blood flow; and on preclinical porcine experiments. We obtained CT images on a prototype spectral detector CT (Philips Healthcare) scanner that provided both conventional and virtual keV images, allowing us to quantitatively compare corrected CT images to virtual keV images. To test these methods' parameter optimization sensitivity to noise, we evaluated results on images obtained using different mAs.

RESULTS

In images of the static phantom, ABHC-2 reduced beam hardening artifacts better than our previous ABHC-1 algorithm, giving artifacts smaller than 1.8 HU, even in the presence of high noise which should affect parameter optimization. Taken together, the quality of static phantom results ordered ABHC-2> ABHC-3> ABHC-1>> ABHC-NH. In an anthropomorphic MPI-CT simulator with homogeneous myocardial blood flow of 100 ml⋅min-1 ⋅100 g-1 , blood flow estimation results were 122 ± 24 (FBP), 135 ± 24 (ABHC-NH), 104 ± 14 (ABHC-1), 100 ± 12 (ABHC-2), and 108 ± 18 (ABHC-3) ml⋅min-1 ⋅100 g-1 , showing ABHC-2 as a clear winner. Visual and quantitative evaluations showed much improved homogeneity of myocardial flow with ABHC-2, nearly eliminating substantial artifacts in uncorrected flow maps which could be misconstrued as flow deficits. ABHC-2 performed universally better than ABHC-1, ABHC-3, and ABHC-NH in simulations with different acquisitions (varying noise and kVp values). In the presence of a simulated flow deficit, all ABHC methods retained the flow deficit, and ABHC-2 gave the most accurate flow ratio and homogeneity. ABHC-3 corrected phantom flow values were slightly better than ABHC-2, in noiseless images, suggesting that reduced quality in noisy images was due to reduced estimability. In an experiment with a pig expected to have uniform flow, ABHC-2 applied to conventional images improved flow maps to compare favorably to those from 70keV images.

CONCLUSION

The automated algorithm can be used with different parametric BH correction models. ABHC-2 improved MPI-CT blood flow estimation as compared to other approaches and was robust to noisy images. In simulation and preclinical experiments, ABHC-2 gave results approaching gold standard 70 keV measurements.

The reliability of the computed tomography perfusion parameters as a predictor of colorectal cancer grade: influence of tumor region of interest position

Background

The aim of this study is to prospectively determine whether the computed tomography perfusion (CTP) can predict the tumor grade in colorectal cancer (CRC), and investigation of the best position of the tumor region of interest (ROI) could improve the tumor grade differentiation.

Results

The mean blood flow (mBF) at the tumor edge was significantly different among different tumor grades with the highest value noted in moderately differentiated and the lowest value in poorly differentiated CRC (111.67 ± 38.91 vs. 52.25 ± 21.97 ml/min/100 g, respectively, P = 0.03). At the tumor center, the BF and blood volume (BV) showed highest value in moderately differentiated and the lowest value in poorly differentiated CRC (P < 0.001, 0.02 respectively). The ROC curve revealed that the BF at the tumor edge showed its best results as regard its sensitivity 73.9% and specificity 82.1% in the characterization of moderately differentiated CRC from the other subtypes at > 92.2 ml/100 g/min cut off point and their AUC and P value were (0.82 and < 0.001 respectively), while the AUC of the BF at the tumor center was 0.81 and its P value was 0.03. In the characterization of poorly differentiated CRC from the other subtypes, BF cut off value at < 67.32 ml/100 g/min at the tumor edge showed the best performance of its sensitivity 88% and specificity 88% with 0.92 AUC and P value was < 0.001, while the AUC of the BF at the tumor center was 0.89. BF was higher at the edge than at the center of the tumor (88.53 ± 22.45 vs. 78.79 ± 28.98 ml/min/100 g; P < 0.001 respectively).

Conclusions

PCT could help in prediction of the poorly and the moderately differentiated CRC and the mBF was the most reliable parameter in prediction of the grade. The variation in ROI position has no substantial difference in the prediction of the tumor grade; however, this variation has a significant impact on the measurements of the PCT parameters especially the BF.

CT and MR perfusion techniques to assess diffuse liver disease

Perfusion imaging allows for the quantitative extraction of physiological perfusion parameters of the liver microcirculation at levels far below the spatial the resolution of CT and MR imaging. Because of its peculiar structure and architecture, perfusion imaging is more challenging in the liver than in other organs. Indeed, the liver is a mobile organ and significantly deforms with respiratory motion. Moreover, it has a dual vascular supply and the sinusoidal capillaries are fenestrated in the normal liver. Using extracellular contrast agents, perfusion imaging has shown its ability to discriminate patients with various stages of liver fibrosis. The recent introduction of hepatobiliary contrast agents enables quantification of both the liver perfusion and the hepatocyte transport function using advanced perfusion models. The purpose of this review article is to describe the characteristics of liver perfusion imaging to assess chronic liver disease, with a special focus on CT and MR imaging.

Spectral Computed Tomographic Parameters Predict the Therapeutic Efficacy and Overall Survival of the Angiogenesis Inhibitor AL3818 in Hepatic Lesions: Preliminary Animal Study

OBJECTIVE

This study aimed to investigate the predictive and prognostic values of repeated spectral computed tomographic (CT) parameter changes for the prediction of treatment responses to the angiogenesis inhibitor AL3818 in hepatic tumors.

METHODS

A total of 30 rabbits with VX2 hepatic tumors that underwent spectral contrast-enhanced abdominal CT before and during treatment were included in the study. The percent change (Δ, %) of the normalized iodine concentration (nIC) during the arterial phase (AP) and venous phase (VP) was used to predict the tumor response and to calculate the overall survival (OS). The threshold of the nIC for tumor response prediction and prognostic significance was determined by a receiver operating characteristic curve and Kaplan-Meier analysis.

RESULTS

After treatment, there were 43% (13/30) responders and 57% (17/30) nonresponders. When ΔnICAP ≥ -13.10% was used as the threshold, the sensitivity and specificity for the prediction of tumor response were 82.41% and 92.31%, respectively. ΔnICVP resulted in 88.20% sensitivity and 76.92% specificity for cutoff values ≥10.78%. Kaplan-Meier analyses showed that high ΔnICAP and ΔnICVP were associated with improved OS.

CONCLUSIONS

The current study shows the capability of the changes (Δ) in repeated spectral CT parameters to predict the tumor response during antiangiogenesis therapy in small hepatic tumors. ΔnICAP and ΔnICVP were predictors for treatment response and were associated with OS.

Imaging Features of the Whole Uterus Volume CT Perfusion and Influence Factors of Blood Supply: A Primary Study in Patients with Cervical Squamous Carcinoma

RATIONALE AND OBJECTIVES

To explore the imaging features of whole uterus volume CT perfusion (vCTP) and the influence factors of blood supply in cervical squamous carcinoma (CSC).

MATERIALS AND METHODS

vCTP was performed on a 640-slice computed tomography system in 43 patients with CSC diagnosed by biopsy, and 24 cases of them underwent magnetic resonance imaging. The size of the tumor was measured on vCTP and magnetic resonance (MR) images. Perfusion parameters, including arterial blood flow (AF), blood volume, and permeability surface (PS), were measured by two radiologists, using interclass correlation coefficient to evaluate the interobserver reliability. The difference of tumor size and perfusion data was analyzed by paired t test and rank sum test. The correlation of perfusion parameters with some factors was analyzed by Pearson or Spearman correlation analysis.

RESULTS

Tumor sizes were not significantly different between vCTP and MR images. The interclass correlation coefficient of each parameter was 0.818-0.945. The AF value of CSC was significantly higher than normal uterine body, and the blood volume and PS values of CSC were not statistically different compared with those of normal uterine body. There was no significant difference in AF value of CSC among different FIGO stages and pathological grades. The AF and PS values of CSC were negatively correlated with the age of the patients.

CONCLUSION

The vCTP could accurately shows the size of the CSC with use of MR as the reference standard, and its perfusion parameters have good measurement stability; the CSC was hypervascular, but this trend was less pronounced in older women.

Computed Tomography Perfusion Measurements in Renal Lesions Obtained by Bayesian Estimation, Advanced Singular-Value Decomposition Deconvolution, Maximum Slope, and Patlak Models: Intermodel Agreement and Diagnostic Accuracy of Tumor Classification

OBJECTIVES

The aims of this study were to evaluate the agreement of computed tomography (CT)-perfusion parameter values of the normal renal cortex and various renal tumors, which were obtained by different mathematical models, and to evaluate their diagnostic accuracy.

MATERIALS AND METHODS

Perfusion imaging was performed prospectively in 35 patients to analyze 144 regions of interest of the normal renal cortex and 144 regions of interest of renal tumors, including 21 clear-cell renal cell carcinomas (RCC), 6 papillary RCCs, 5 oncocytomas, 1 chromophobe RCC, 1 angiomyolipoma with minimal fat, and 1 tubulocystic RCC. Identical source data were postprocessed and analyzed on 2 commercial software applications with the following implemented mathematical models: maximum slope, Patlak plot, standard singular-value decomposition (SVD), block-circulant SVD, oscillation-limited block-circulant SVD, and Bayesian estimation technique. Results for blood flow (BF), blood volume (BV), and mean transit time (MTT) were recorded. Agreement and correlation between pairs of models and perfusion parameters were assessed. Diagnostic accuracy was evaluated by receiver operating characteristic (ROC) analysis.

RESULTS

Significant differences and poor agreement of BF, BV, and MTT values were noted for most of model comparisons in both the normal renal cortex and different renal tumors. The correlations between most model pairs and perfusion parameters ranged between good and perfect (Spearman ρ = 0.79-1.00), except for BV values obtained by Patlak method (ρ = 0.61-0.72). All mathematical models computed BF and BV values, which differed significantly between clear cell RCCs, papillary RCCs, and oncocytomas, which introduces them as useful diagnostic tests to differentiate between different histologic subgroups (areas under ROC curve, 0.83-0.99). The diagnostic accuracy to discriminate between clear-cell RCCs and the renal cortex was the lowest based on the Patlak plot model (area under ROC curve, 0.76); BF and BV values obtained by other algorithms did not differ significantly in their diagnostic accuracy.

CONCLUSIONS

Quantitative perfusion parameters obtained from different mathematical models cannot be used interchangeably. Based on BF and BV estimates, all models are a useful tool in the differential diagnosis of kidney tumors, with the Patlak plot model yielding a significantly lower diagnostic accuracy.

Diagnostic Performance of Perfusion Computed Tomography for Differentiating Lung Cancer from Benign Lesions: A Meta-Analysis

Background

Numerous studies have explored diagnosis of pulmonary nodules using perfusion computed tomography (CT); however, findings were not always consistent between studies. Th e present study aimed to summarize evidence on the diagnostic value of perfusion CT for distinguishing between lung cancer and benign lesions.

Material/Methods

We performed a systematic literature search on lung cancer and benign pulmonary lesions performed with perfusion CT. The searches were undertaken in English or Chinese language in Medline, PubMed, Embase, Cochrane Library, Web of Science, and China National Knowledge Infrastructure database from Jan 2010 to Nov 2018. Standardized mean differences (SMDs) and 95% confidence intervals (CIs) of blood volume (BV), blood flow (BF), mean transit time (MTT), and permeability surface (PS) were calculated using Review Manager 5.3. Publication bias, sensitivity, specificity, and the area under the curve (AUC) were calculated using Stata12.0.

Results

Fourteen studies comprising 1032 malignant and 447 benign pulmonary lesions were analyzed. Lung cancer had higher BV, BF, MTT, and PS values than benign lesions. SMDs and 95% CIs of BV, BF, MTT, and PS were 2.29 (1.43, 3.16), 0.50 (0.14, 0.86), 0.55 (0.39, 0.72), and 1.21 (0.87, 1.56), respectively. AUC values of BV and PS were 0.92 (0.90, 0.94) and 0.83 (0.80, 0.86), respectively.

Conclusions

CT perfusion imaging is a valuable technique for the diagnosis of pulmonary nodules. Lung cancer had higher perfusion and permeability than benign lesions. The evidence suggests blood volume is the best surrogate marker for characterizing the blood supply, while permeability surface has a high specificity in quantifying the vascular permeability.

Prediction of Treatment Outcome of Chemotherapy Using Perfusion Computed Tomography in Patients with Unresectable Advanced Gastric Cancer

Objective

To evaluate whether data acquired from perfusion computed tomography (PCT) parameters can aid in the prediction of treatment outcome after palliative chemotherapy in patients with unresectable advanced gastric cancer (AGC).

Materials and Methods

Twenty-one patients with unresectable AGCs, who underwent both PCT and palliative chemotherapy, were prospectively included. Treatment response was assessed according to Response Evaluation Criteria in Solid Tumors version 1.1 (i.e., patients who achieved complete or partial response were classified as responders). The relationship between tumor response and PCT parameters was evaluated using the Mann-Whitney test and receiver operating characteristic analysis. One-year survival was estimated using the Kaplan-Meier method.

Results

After chemotherapy, six patients exhibited partial response and were allocated to the responder group while the remaining 15 patients were allocated to the non-responder group. Permeability surface (PS) value was shown to be significantly different between the responder and non-responder groups (51.0 mL/100 g/min vs. 23.4 mL/100 g/min, respectively; p = 0.002), whereas other PCT parameters did not demonstrate a significant difference. The area under the curve for prediction in responders was 0.911 (p = 0.004) for PS value, with a sensitivity of 100% (6/6) and specificity of 80% (12/15) at a cut-off value of 29.7 mL/100 g/min. One-year survival in nine patients with PS value > 29.7 mL/100 g/min was 66.7%, which was significantly higher than that in the 12 patients (33.3%) with PS value ≤ 29.7 mL/100 g/min (p = 0.019).

Conclusion

Perfusion parameter data acquired from PCT demonstrated predictive value for treatment outcome after palliative chemotherapy, reflected by the significantly higher PS value in the responder group compared with the non-responder group.

The role of acquisition and quantification methods in myocardial blood flow estimability for myocardial perfusion imaging CT

In this work, we clarified the role of acquisition parameters and quantification methods in myocardial blood flow (MBF) estimability for myocardial perfusion imaging using CT (MPI-CT). We used a physiologic model with a CT simulator to generate time-attenuation curves across a range of imaging conditions, i.e. tube current-time product, imaging duration, and temporal sampling, and physiologic conditions, i.e. MBF and arterial input function width. We assessed MBF estimability by precision (interquartile range of MBF estimates) and bias (difference between median MBF estimate and reference MBF) for multiple quantification methods. Methods included: six existing model-based deconvolution models, such as the plug-flow tissue uptake model (PTU), Fermi function model, and single-compartment model (SCM); two proposed robust physiologic models (RPM1, RPM2); model-independent singular value decomposition with Tikhonov regularization determined by the L-curve criterion (LSVD); and maximum upslope (MUP). Simulations show that MBF estimability is most affected by changes in imaging duration for model-based methods and by changes in tube current-time product and sampling interval for model-independent methods. Models with three parameters, i.e. RPM1, RPM2, and SCM, gave least biased and most precise MBF estimates. The average relative bias (precision) for RPM1, RPM2, and SCM was  ⩽11% (⩽10%) and the models produced high-quality MBF maps in CT simulated phantom data as well as in a porcine model of coronary artery stenosis. In terms of precision, the methods ranked best-to-worst are: RPM1  >  RPM2  >  Fermi  >  SCM  >  LSVD  >  MUP [Formula: see text] other methods. In terms of bias, the models ranked best-to-worst are: SCM  >  RPM2  >  RPM1  >  PTU  >  LSVD [Formula: see text] other methods. Models with four or more parameters, particularly five-parameter models, had very poor precision (as much as 310% uncertainty) and/or significant bias (as much as 493%) and were sensitive to parameter initialization, thus suggesting the presence of multiple local minima. For improved estimates of MBF from MPI-CT, it is recommended to use reduced models that incorporate prior knowledge of physiology and contrast agent uptake, such as the proposed RPM1 and RPM2 models.

Absolute CBV for the differentiation of recurrence and radionecrosis of brain metastases after gamma knife radiotherapy: a comparison with relative CBV

AIM

To investigate the efficiency of absolute cerebral blood volume (CBV) in the differentiation of tumour recurrence (TR) and radionecrosis (RN) in brain metastases (BM) and to evaluate the performance of absolute CBV compared to relative CBV (rCBV).

MATERIALS AND METHODS

Between March 2015 and June 2017, 46 patients with BM underwent quantitative dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) because new enhancement had been demonstrated in irradiated lesions after gamma knife radiotherapy. The patients were assigned to either the TR group or RN group on the basis of MR perfusion follow-up or histopathological outcome. Absolute CBV of lesions (CBVlesion) and contralateral normal appearing white matter (CBVNAWM) in both groups were obtained. Mean rCBV were calculated as CBVlesion/CBVNAWM, which was equal to rCBV using traditional DSC-PWI.

RESULTS

CBVlesion of TR alone was significantly higher than the other parameters in both groups (p<0.001, separately). CBVlesion had smaller interobserver difference than CBVNAWM and rCBV (p<0.001, separately). Although CBVlesion significantly correlated with rCBV (r=0.914, p<0.001) and both had a similar specificity (96%) in differential diagnosis, CBVlesion had a higher sensitivity (96.9% versus 90.9%) to predict the treatment outcome. The best cut-off value of CBVlesion was 21.8 ml/100 g.

CONCLUSION

Quantitative DSC-PWI is a powerful method for the assessment of radiosurgically treated brain metastases. Absolute CBV has higher diagnostic efficiency than rCBV, which enables an absolute quantification of the regional CBV and prediction of tumour response. These advantages promote the intra- and inter-patient quantitative image comparison across different institutions.

Use of patient outcome endpoints to identify the best functional CT imaging parameters in metastatic renal cell carcinoma patients

OBJECTIVE

To use the patient outcome endpoints overall survival and progression-free survival to evaluate functional parameters derived from dynamic contrast-enhanced CT.

METHODS

69 patients with metastatic renal cell carcinoma had dynamic contrast-enhanced CT scans at baseline and after 5 and 10 weeks of treatment. Blood volume, blood flow and standardized perfusion values were calculated using deconvolution (BV_deconv, BF_deconv and SPV_deconv), blood flow and standardized perfusion values using maximum slope (BF_max and SPV_max) and blood volume and permeability surface area product using the Patlak model (BV_patlak and PS). Histogram data for each were extracted and associated to patient outcomes. Correlations and agreements were also assessed.

RESULTS

The strongest associations were observed between patient outcome and medians and modes for BV_deconv, BV_patlak and BF_deconv at baseline and during the early ontreatment period (p < 0.05 for all). For the relative changes in median and mode between baseline and weeks 5 and 10, PS seemed to have opposite associations dependent on treatment. Interobserver correlations were excellent (r ≥ 0.9, p < 0.001) with good agreement for BF_deconv, BF_max, SPV_deconv and SPV_max and moderate to good (0.5 < r < 0.7, p < 0.001) for BV_deconv and BV_patlak. Medians had a better reproducibility than modes.

CONCLUSION

Patient outcome was used to identify the best functional imaging parameters in patients with metastatic renal cell carcinoma. Taking patient outcome and reproducibility into account, BV_deconv, BV_patlak and BF_deconv provide the most clinically meaningful information, whereas PS seems to be treatment dependent. Standardization of acquisition protocols and post-processing software is necessary for future clinical utilization. Advances in knowledge: Taking patient outcome and reproducibility into account, BV_deconv, BV_patlak and BF_deconv provide the most clinically meaningful information. PS seems to be treatment dependent.

Multi-detector CT: Liver protocol and recent developments

Multi-detector computed tomography is today the workhorse in the evaluation of the vast majority of patients with known or suspected liver disease. Reasons for that include widespread availability, robustness and repeatability of the technique, time-efficient image acquisitions of large body volumes, high temporal and spatial resolution as well as multiple post-processing capabilities. However, as the technique employs ionizing radiation and intravenous iodine-based contrast media, the associated potential risks have to be taken into account. In this review article, liver protocols in clinical practice are discussed with emphasis on optimisation strategies. Furthermore, recent developments such as perfusion CT and dual-energy CT and their applications are presented.

Dynamic Contrast-Enhanced Perfusion Area-Detector CT: Preliminary Comparison of Diagnostic Performance for N Stage Assessment With FDG PET/CT in Non-Small Cell Lung Cancer

OBJECTIVE

The objective of our study was to directly compare the capability of dynamic first-pass contrast-enhanced (CE) perfusion area-detector CT (ADCT) and FDG PET/CT for differentiation of metastatic from nonmetastatic lymph nodes and assessment of N stage in patients with non-small cell lung carcinoma (NSCLC).

SUBJECTS AND METHODS

Seventy-seven consecutive patients, 45 men (mean age ± SD, 70.4 ± 5.9 years) and 32 women (71.2 ± 7.7 years), underwent dynamic first-pass CE-perfusion ADCT at two or three different positions for covering the entire thorax, FDG PET/CT, surgical treatment, and pathologic examination. From all ADCT data for each of the subjects, a whole-chest perfusion map was computationally generated using the dual- and single-input maximum slope and Patlak plot methods. For quantitative N stage assessment, perfusion parameters and the maximum standardized uptake value (SUV_max) for each lymph node were determined by measuring the relevant ROI. ROC curve analyses were performed for comparing the diagnostic capability of each of the methods on a per-node basis. N stages evaluated by each of the indexes were then statistically compared with the final pathologic diagnosis by means of chi-square and kappa statistics.

RESULTS

The area under the ROC curve (A_z) values of systemic arterial perfusion (A_z = 0.89), permeability surface (A_z = 0.78), and SUV_max (A_z = 0.85) were significantly larger than the A_z values of total perfusion (A_z = 0.70, p < 0.05) and distribution volume (A_z = 0.55, p < 0.05). For each of the threshold values, agreement for systemic arterial perfusion calculated using the dual-input maximum slope model was substantial (κ = 0.70, p < 0.0001), and agreement for SUV_max was moderate (κ = 0.60, p < 0.0001).

CONCLUSION

Dynamic first-pass CE-perfusion ADCT is as useful as FDG PET/CT for the differentiation of metastatic from nonmetastatic lymph nodes and assessment of N stage in patients with NSCLC.

Is liver perfusion CT reproducible? A study on intra- and interobserver agreement of normal hepatic haemodynamic parameters obtained with two different software packages

OBJECTIVE

To evaluate the agreement between the measurements of perfusion CT parameters in normal livers by using two different software packages.

METHODS

This retrospective study was based on 78 liver perfusion CT examinations acquired for detecting suspected liver metastasis. Patients with any morphological or functional hepatic abnormalities were excluded. The final analysis included 37 patients (59.7 ± 14.9 y). Two readers (1 and 2) independently measured perfusion parameters using different software packages from two major manufacturers (A and B). Arterial perfusion (AP) and portal perfusion (PP) were determined using the dual-input vascular one-compartmental model. Inter-reader agreement for each package and intrareader agreement between both packages were assessed with intraclass correlation coefficients (ICC) and Bland-Altman statistics.

RESULTS

Inter-reader agreement was substantial for AP using software A (ICC = 0.82) and B (ICC = 0.85-0.86), fair for PP using software A (ICC = 0.44) and fair to moderate for PP using software B (ICC = 0.56-0.77). Intrareader agreement between software A and B ranged from slight to moderate (ICC = 0.32-0.62) for readers 1 and 2 considering the AP parameters, and from fair to moderate (ICC = 0.40-0.69) for readers 1 and 2 considering the PP parameters.

CONCLUSION

At best there was only moderate agreement between both software packages, resulting in some uncertainty and suboptimal reproducibility. Advances in knowledge: Software-dependent factors may contribute to variance in perfusion measurements, demanding further technical improvements. AP measurements seem to be the most reproducible parameter to be adopted when evaluating liver perfusion CT.

CT Perfusion evaluation of gastric cancer: correlation with histologic type

OBJECTIVES

To prospectively evaluate if the perfusion parameters of gastric cancer can provide information on histologic subtypes of gastric cancer.

METHODS

We performed preoperative perfusion CT (PCT) and curative gastrectomy in 46 patients. PCT data were analysed using a dedicated software program. Perfusion parameters were obtained by two independent radiologists and were compared according to histologic type using Kruskal-Wallis, Mann-Whitney U test and receiver operating characteristic analysis. To assess inter-reader agreement, we used intraclass correlation coefficient (ICC).

RESULTS

Inter-reader agreement for perfusion parameters was moderate to substantial (ICC = 0.585-0.678). Permeability surface value of poorly cohesive carcinoma (PCC) was significantly higher than other histologic types (47.3 ml/100 g/min in PCC vs 26.5 ml/100 g/min in non-PCC, P < 0.001). Mean transit time (MTT) of PCC was also significantly longer than non-PCC (13.0 s in PCC vs 10.3 s in non-PCC, P = 0.032). The area under the curve to predict PCC was 0.891 (P < 0.001) for permeability surface and 0.697 (P = 0.015) for MTT.

CONCLUSION

Obtaining perfusion parameters from PCT was feasible in gastric cancer patients and can aid in the preoperative imaging diagnosis of PCC-type gastric cancer as the permeability surface and MTT value of PCC type gastric cancer were significantly higher than those of non-PCC.

KEY POINTS

• Obtaining perfusion parameters from PCT was feasible in patients with gastric cancer. • Permeability surface and MTT were significantly higher in poorly cohesive carcinoma (PCC). • Permeability surface, MTT can aid in the preoperative imaging diagnosis of PCC.

Liver MRI: From basic protocol to advanced techniques

Liver MR is a well-established modality with multiparametric capabilities. However, to take advantage of its full capacity, it is mandatory to master the technique and optimize imaging protocols, apply advanced imaging concepts and understand the use of different contrast media. Physiologic artefacts although inherent to upper abdominal studies can be minimized using triggering techniques and new strategies for motion control. For standardization, the liver MR protocol should include motion-resistant T2-w sequences, in-op phase GRE T1 and T2-w fast spin echo sequences with fat suppression. Diffusion-weighted imaging (DWI) is mandatory, especially for detection of sub-centimetre metastases. Contrast-enhanced MR is the cornerstone of liver MR, especially for lesion characterization. Although extracellular agents are the most extensively used contrast agents, hepatobiliary contrast media can provide an extra-layer of functional diagnostic information adding to the diagnostic value of liver MR. The use of high field strength (3T) increases SNR but is more challenging especially concerning artefact control. Quantitative MR belongs to the new and evolving field of radiomics where the use of emerging biomarkers such as perfusion or DWI can derive new information regarding disease detection, prognostication and evaluation of tumour response. This information can overcome some of the limitations of current tests, especially when using vascular disruptive agents for oncologic treatment assessment. MR is, today, a robust, mature, multiparametric imaging modality where clinical applications have greatly expanded from morphology to advanced imaging. This new concept should be acknowledged by all those involved in producing high quality, high-end liver MR studies.

Reproducibility and variability of very low dose hepatic perfusion CT in metastatic liver disease

PURPOSE

We aimed to determine the intra- and interobserver agreement on the software analysis of very low dose hepatic perfusion CT (pCT).

METHODS

A total of 53 pCT examinations were obtained from 21 patients (16 men, 5 women; mean age, 60.4 years) with proven liver metastasis from various primary cancers. The pCT examinations were analyzed by two readers independently and perfusion parameters were noted for whole liver, whole metastasis, metastasis wall, and normal-looking liver (liver tissue without metastasis) in regions of interest (ROIs). Readers repeated the analysis after an interval of one month. Intra- and interobserver agreements were assessed with intraclass correlation coefficients (ICC) and Bland-Altman statistics.

RESULTS

The mean ICCs of all ROIs between readers were 0.91, 0.93, 0.86, 0.45, 0.53, and 0.66 for blood flow (BF), blood volume (BV), permeability, arterial liver perfusion (ALP), portal venous perfusion (PVP) and hepatic perfusion index (HPI), respectively. The mean ICCs of all ROIs between readings were 0.86, 0.91, 0.81, 0.53, 0.56, and 0.71 for BF, BV, permeability, ALP, PVP, and HPI, respectively. There was greater agreement on the parameters measured for the whole metastasis than on the parameters measured for the metastasis wall. The effective dose of all perfusion CT studies was 2.9 mSv.

CONCLUSION

There is greater intra- and interobserver agreement for BF and BV than for permeability, ALP, PVP, and HPI at very low dose hepatic pCT. Permeability, ALP, PVP, and HPI parameters cannot be used in clinical practice for hepatic pCT with an effective dose of 2.9 mSv.

Perfusion parameters as potential imaging biomarkers for the early prediction of radiotherapy response in a rat tumor model

PURPOSE

We aimed to compare various tumor-related radiologic morphometric changes and computed tomography (CT) perfusion parameters before and after treatment, and to determine the optimal imaging assessment technique for the prediction of early response in a rat tumor model treated with radiotherapy.

METHODS

Among paired tumors of FN13762 murine breast cancer cells implanted bilaterally in the necks of eight Fischer rats, tumors on the right side were treated with a single 20 Gy dose of radiotherapy. Perfusion CT studies were performed on day 0 before radiotherapy, and on days 1 and 5 after radiotherapy. Variables based on the size, including the longest diameter, tumor area, and volume, were measured. Quantitative perfusion analysis was performed for the whole tumor volume and permeabilities and blood volumes (BVs) were obtained. The area under the curve (AUC) difference in the histograms of perfusion parameters and texture analyses of uniformity and entropy were quantified. Apoptotic cell density was measured on pathology specimens immediately after perfusion imaging on day 5.

RESULTS

On day 1 after radiotherapy, differences in size between the irradiated and nonirradiated tumors were not significant. In terms of percent changes in the uniformity of permeabilities between tumors before irradiation and on day 1 after radiotherapy, the changes were significantly higher in the irradiated tumors than in the nonirradiated tumors (0.085 [-0.417, 0.331] vs. -0.131 [-0.536, 0.261], respectively; P = 0.042). The differences in AUCs of the histogram of voxel-by-voxel vascular permeability and BV in tumors between day 0 and day 1 were significantly higher in treated tumors compared with the control group (permeability, 21.4 [-2.2, 37.5] vs. 9.5 [-8.9, 33.8], respectively, P = 0.030; BV, 52.9 [-6186.0, 419.2] vs. 11.9 [-198.3, 346.7], respectively, P = 0.049). Apoptotic cell density showed a significantly positive correlation with the AUC difference of BV, the percent change of uniformity in permeability and BV (r=0.202, r=0.644, and r=0.706, respectively).

CONCLUSION

By enabling earlier tumor response prediction than morphometric evaluation, the histogram analysis of CT perfusion parameters appears to have a potential in providing prognostic predictive information in an irradiated rat model.

CT-perfusion measurements in pancreatic carcinoma with different kinetic models: Is there a chance for tumour grading based on functional parameters?

BACKGROUND

To evaluate the interchangeability of perfusion parameters obtained with help of models used for post-processing of perfusion-CT images in pancreatic adenocarcinoma and to determine the mean values and ranges of perfusion in different tumour gradings.

METHODS

Perfusion-CT imaging was performed prospectively in 48 consecutive patients with pancreatic adenocarcinoma. In 42 patients biopsy-proven tumor grading was available (4 × G1/24 × G2/14 × G3/6× unknown). Images were post-processed using a model based on the maximum-slope (MS) approach (blood flow-BFMS) + Patlak analysis (P) (blood volume [BVP] and permeability [k-transP]), as well as a model with deconvolution-based (D) analysis (BFD, BVD and k-transD). 50 mL contrast agent were applied with a delay time of 7 s. Perfusion parameters were compared using intraclass correlation coefficient (ICC), the Wilcoxon matched-pairs test and Bland-Altman plots.

RESULTS

Forty eight VOIs of tumours were outlined and analysed. Moderate to good ICC values were found for the perfusion parameters (ICC = 0.62-0.75). Wilcoxon matched-pairs revealed significantly lower values (P < .001 and 0.008), for the BF and BV values obtained using the maximum-slope approach + Patlak analysis compared to deconvolution based analysis. For k-trans measurement, deconvolution revealed significantly lower values (P < 0.001). Different histologic subgroups (G1-G3) did not show significantly different functional parameters.

CONCLUSION

There were significant differences in the perfusion parameters obtained using the different calculation methods, and therefore these parameters are not directly interchangeable. However, the magnitude of pairs of parametric values is in constant relation to each other enabling the use of any of these methods. VPCT parameters did not allow for histologic classification.

Dynamic contrast-enhanced perfusion area-detector CT assessed with various mathematical models: Its capability for therapeutic outcome prediction for non-small cell lung cancer patients with chemoradiotherapy as compared with that of FDG-PET/CT

PURPOSE

To directly compare the capability of dynamic first-pass contrast-enhanced (CE-) perfusion area-detector CT (ADCT) and PET/CT for early prediction of treatment response, disease progression and overall survival of non-small cell carcinoma (NSCLC) patients treated with chemoradiotherapy.

MATERIALS AND METHODS

Fifty-three consecutive Stage IIIB NSCLC patients who had undergone PET/CT, dynamic first-pass CE-perfusion ADCT, chemoradiotherapy, and follow-up examination were enrolled in this study. They were divided into two groups: 1) complete or partial response (CR+PR) and 2) stable or progressive disease (SD+PD). Pulmonary arterial and systemic arterial perfusions and total perfusion were assessed at targeted lesions with the dual-input maximum slope method, permeability surface and distribution volume with the Patlak plot method, tumor perfusion with the single-input maximum slope method, and SUV_max, and results were averaged to determine final values for each patient. Next, step-wise regression analysis was used to determine which indices were the most useful for predicting therapeutic effect. Finally, overall survival of responders and non-responders assessed by using the indices that had a significant effect on prediction of therapeutic outcome was statistically compared.

RESULTS

The step-wise regression test showed that therapeutic effect (r²=0.63, p=0.01) was significantly affected by the following three factors in order of magnitude of impact: systemic arterial perfusion, total perfusion, and SUV_max. Mean overall survival showed a significant difference for total perfusion (p=0.003) and systemic arterial perfusion (p=0.04).

CONCLUSION

Dynamic first-pass CE-perfusion ADCT as well as PET/CT are useful for treatment response prediction in NSCLC patients treated with chemoradiotherapy.

Mechanism and non-mechanism based imaging biomarkers for assessing biological response to treatment in non-small cell lung cancer

Therapeutic options in locally advanced non-small cell lung cancer (NSCLC) have expanded in the past decade to include a palate of targeted interventions such as high dose targeted thermal ablations, radiotherapy and growing platform of antibody and small molecule therapies and immunotherapies. Although these therapies have varied mechanisms of action, they often induce changes in tumour architecture and microenvironment such that response is not always accompanied by early reduction in tumour mass, and evaluation by criteria other than size is needed to report more effectively on response. Functional imaging techniques, which probe the tumour and its microenvironment through novel positron emission tomography and magnetic resonance imaging techniques, offer more detailed insights into and quantitation of tumour response than is available on anatomical imaging alone. Use of these biomarkers, or other rational combinations as readouts of pathological response in NSCLC have potential to provide more accurate predictors of treatment outcomes. In this article, the robustness of the more commonly available positron emission tomography and magnetic resonance imaging biomarker indices is examined and the evidence for their application in NSCLC is reviewed.

Quantitative Myocardial Perfusion with Dynamic Contrast-Enhanced Imaging in MRI and CT: Theoretical Models and Current Implementation

Technological advances in magnetic resonance imaging (MRI) and computed tomography (CT), including higher spatial and temporal resolution, have made the prospect of performing absolute myocardial perfusion quantification possible, previously only achievable with positron emission tomography (PET). This could facilitate integration of myocardial perfusion biomarkers into the current workup for coronary artery disease (CAD), as MRI and CT systems are more widely available than PET scanners. Cardiac PET scanning remains expensive and is restricted by the requirement of a nearby cyclotron. Clinical evidence is needed to demonstrate that MRI and CT have similar accuracy for myocardial perfusion quantification as PET. However, lack of standardization of acquisition protocols and tracer kinetic model selection complicates comparison between different studies and modalities. The aim of this overview is to provide insight into the different tracer kinetic models for quantitative myocardial perfusion analysis and to address typical implementation issues in MRI and CT. We compare different models based on their theoretical derivations and present the respective consequences for MRI and CT acquisition parameters, highlighting the interplay between tracer kinetic modeling and acquisition settings.

Dynamic contrast-enhanced perfusion area detector CT for non-small cell lung cancer patients: Influence of mathematical models on early prediction capabilities for treatment response and recurrence after chemoradiotherapy

PURPOSE

To determine the capability and influence of the mathematical method on dynamic contrast-enhanced (CE-) perfusion area detector CT (ADCT) for early prediction of treatment response as well as progression free and overall survival (PFS and OS) of non-small cell lung cancer (NSCLC) patients treated with chemoradiotherapy.

MATERIALS AND METHODS

Sixty-six consecutive stage III NSCLC patients underwent dynamic CE-perfusion ADCT examinations, chemoradiotherapy and follow-up examinations. Response Evaluation Criteria in Solid Tumors (RECIST) criteria were used to divide all patients into responders and non-responders. Differences in each of the indices for all targeted lesions between measurements obtained 2 weeks prior to the first and the third course of chemotherapy were determined for all patients. ROC analyses were employed to determine the capability of perfusion indices as markers for distinguishing RECIST responders from non-responders. To evaluate their capability for early prediction of therapeutic effect, OS of perfusion index-based responders and non-responders were compared by using the Kaplan-Meier method followed by log-rank test.

RESULTS

Area under the curve (Az) for total perfusion by means of the dual-input maximum slope method was significantly larger than that of pulmonary arterial perfusion using the same method (p=0.007) and of perfusion with the single-input maximum slope method (p=0.007). Mean OS demonstrated significantly difference between responder- and non-responder groups for total perfusion (p=0.02).

CONCLUSION

Mathematical models have significant influence on assessment for early prediction of treatment response, disease progression and overall survival using dynamic CE-perfusion ADCT for NSCLC patients treated with chemoradiotherapy.

Dynamic volume perfusion computed tomography parameters versus RECIST for the prediction of outcome in lung cancer patients treated with conventional chemotherapy

INTRODUCTION

To compare dynamic volume perfusion computed tomography (dVPCT) parameters with Response Evaluation Criteria in Solid Tumors (RECIST 1.1) for prediction of therapy response and overall survival (OS) in non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC) patients treated with conventional chemotherapy.

METHODS

A total of 173 lung cancer patients (131 men; 61 ± 10 years) undergoing dVPCT before (T1) and after chemotherapy (T2) and follow-up were prospectively included. dVPCT-derived blood flow, blood volume, mean transit time, and permeability (PERM) were assessed, compared between NSCLC and SCLC and patients' response to therapy was determined according to RECIST 1.1.

RESULTS

One hundred of one hundred and seventy-three patients underwent dVPCT at T1 and T2 within a median of 44 (range, 31-108) days. dVPCT values were differing in NSCLC and SCLC, but were not significantly differing between patients with partial response, stable, or progressive disease. Eighty-five patients (NSCLC = 72 and SCLC = 13) with a follow-up for greater than or equal to 6 months were analyzed for OS. Fifty-six of eighty-five patients died during follow-up. Receiver operating characteristic analysis determined T1/T2 with highest predictive values regarding OS for blood flow, blood volume, mean transit time, and permeability (area under the curve: 0.53, 0.61, 0.54, and 0.53, respectively, all p > 0.05). Kaplan-Meier statistics revealed OS of patient groups assigned according to dVPCT T1/T2 cutoff values was not differing for neither dVPCT parameter, whereas RECIST groups significantly differed in OS (p = 0.02). Cox proportional hazards regression determined progressive disease status to independently predict OS (p = 0.004), while none of the dVPCT parameters did so.

CONCLUSIONS

dVPCT values, differ between NSCLC and SCLC, are not related to RECIST 1.1 classification and do not improve OS prediction in lung cancer patients treated with conventional chemotherapy.

Monitoring Vascular Disrupting Therapy in a Rabbit Liver Tumor Model: Relationship between Tumor Perfusion Parameters at IVIM Diffusion-weighted MR Imaging and Those at Dynamic Contrast-enhanced MR Imaging

PURPOSE

To investigate whether perfusion-related intravoxel incoherent motion (IVIM) diffusion-weighted (DW) magnetic resonance (MR) imaging parameters correlate with dynamic contrast material-enhanced MR imaging parameters in between-subject and/or within-subject longitudinal settings for monitoring the therapeutic effects of a vascular disrupting agent (VDA) (CKD-516) in rabbit VX2 liver tumors.

MATERIALS AND METHODS

With institutional Animal Care and Use Committee approval, 21 VX2 liver tumor-bearing rabbits (treated, n = 15; control, n = 6) underwent IVIM DW imaging with 12 b values (0-800 sec/mm(2)) and dynamic contrast-enhanced MR imaging performed before (baseline) CKD-516 administration and 4 hours, 24 hours, and 7 days after administration. Perfusion-related IVIM DW imaging parameters of the tumors, including the pseudodiffusion coefficient (D*) and perfusion fraction (f), as well as dynamic contrast-enhanced MR imaging parameters, including the volume transfer coefficient (K(trans)) and initial area under the gadolinium concentration-time curve until 60 seconds (iAUC), were measured. IVIM DW imaging parameters were correlated with dynamic contrast-enhanced MR imaging parameters by using Pearson correlation analysis between subjects at each given time and by using a linear mixed model for within-subject longitudinal data.

RESULTS

In the treated group, D*, f, K(trans), and iAUC significantly decreased (-40.7% to -26.3%) at 4-hour follow-up compared with these values in the control group (-6.9% to +5.9%) (P < .05). For longitudinal monitoring of CKD-516 treatment, D* and f showed significant positive correlations with K(trans) and iAUC (P = .004 and P = .02; P < .001 and P = .006, respectively), while no significant correlations were observed between IVIM DW imaging and dynamic contrast-enhanced MR imaging parameters between subjects at any given time (P > .05).

CONCLUSION

In a rabbit tumor model, perfusion parameters serially quantified with IVIM DW imaging can be used as alternatives to dynamic contrast-enhanced MR imaging parameters in reflecting the dynamic changes in tumor perfusion during the within-subject longitudinal monitoring of VDA treatment.

Quantitative radiology: applications to oncology

Oncologists, clinician-scientists, and basic scientists collect computed tomography, magnetic resonance, and positron emission tomography images in the process of caring for patients, managing clinical trials, and investigating cancer biology. As we have developed more sophisticated means for noninvasively delineating and characterizing neoplasms, these image data have come to play a central role in oncology. In parallel, the increasing complexity and volume of these data have necessitated the development of quantitative methods for assessing tumor burden, and by proxy, disease-free survival.

Patient characteristics influencing the variability of distributed parameter-based models in DCE-CT kinetic analysis

Kinetic parameter variability may be sensitive to kinetic model choice, kinetic model implementation or patient-specific effects. The purpose of this study was to assess their impact on the variability of dynamic contrast-enhanced computed tomography (DCE-CT) kinetic parameters. A total of 11 canine patients with sinonasal tumours received high signal-to-noise ratio, test-double retest DCE-CT scans. The variability for three distributed parameter (DP)-based models was assessed by analysis of variance. Mixed-effects modelling evaluated patient-specific effects. Inter-model variability (CV_inter ) was comparable to or lower than intra-model variability (CV_intra ) for blood flow (CV_inter :[4-28%], CV_intra :[28-31%]), fractional vascular volume (CV_inter :[3-17%], CV_intra :[16-19%]) and permeability-surface area product (CV_inter :[5-12%], CV_intra :[14-15%]). The kinetic models were significantly (P<0.05) impacted by patient characteristics for patient size, area underneath the curve of the artery and of the tumour. In conclusion, DP-based models demonstrated good agreement with similar differences between models and scans. However, high variability in the kinetic parameters and their sensitivity to patient size may limit certain quantitative applications.

Abdominal perfusion computed tomography

The purpose of this article is to provide an up to date review on the spectrum of applications of perfusion computed tomography (CT) in the abdomen. New imaging techniques have been developed with the objective of obtaining a structural and functional analysis of different organs. Recently, perfusion CT has aroused the interest of many researchers who are studying the applicability of imaging modalities in the evaluation of abdominal organs and diseases. Per-fusion CT enables fast, non-invasive imaging of the tumor vascular physiology. Moreover, it can act as an in vivo biomarker of tumor-related angiogenesis.

Comparison of perfusion- and diffusion-weighted imaging parameters in brain tumor studies processed using different software platforms

RATIONALE AND OBJECTIVES

To compare quantitative imaging parameter measures from diffusion- and perfusion-weighted imaging magnetic resonance imaging (MRI) sequences in subjects with brain tumors that have been processed with different software platforms.

MATERIALS AND METHODS

Scans from 20 subjects with primary brain tumors were selected from the Comprehensive Neuro-oncology Data Repository at Washington University School of Medicine (WUSM) and the Swedish Neuroscience Institute. MR images were coregistered, and each subject's data set was processed by three software packages: 1) vendor-specific scanner software, 2) research software developed at WUSM, and 3) a commercially available, Food and Drug Administration-approved, processing platform (Nordic Ice). Regions of interest (ROIs) were chosen within the brain tumor and normal nontumor tissue. The results obtained using these methods were compared.

RESULTS

For diffusion parameters, including mean diffusivity and fractional anisotropy, concordance was high when comparing different processing methods. For perfusion-imaging parameters, a significant variance in cerebral blood volume, cerebral blood flow, and mean transit time (MTT) values was seen when comparing the same raw data processed using different software platforms. Correlation was better with larger ROIs (radii ≥ 5 mm). Greatest variance was observed in MTT.

CONCLUSIONS

Diffusion parameter values were consistent across different software processing platforms. Perfusion parameter values were more variable and were influenced by the software used. Variation in the MTT was especially large suggesting that MTT estimation may be unreliable in tumor tissues using current MRI perfusion methods.

CT perfusion of the liver: principles and applications in oncology

With the introduction of molecularly targeted chemotherapeutics, there is an increasing need for defining new response criteria for therapeutic success because use of morphologic imaging alone may not fully assess tumor response. Computed tomographic (CT) perfusion imaging of the liver provides functional information about the microcirculation of normal parenchyma and focal liver lesions and is a promising technique for assessing the efficacy of various anticancer treatments. CT perfusion also shows promising results for diagnosing primary or metastatic tumors, for predicting early response to anticancer treatments, and for monitoring tumor recurrence after therapy. Many of the limitations of early CT perfusion studies performed in the liver, such as limited coverage, motion artifacts, and high radiation dose of CT, are being addressed by recent technical advances. These include a wide area detector with or without volumetric spiral or shuttle modes, motion correction algorithms, and new CT reconstruction technologies such as iterative algorithms. Although several issues related to perfusion imaging-such as paucity of large multicenter trials, limited accessibility of perfusion software, and lack of standardization in methods-remain unsolved, CT perfusion has now reached technical maturity, allowing for its use in assessing tumor vascularity in larger-scale prospective clinical trials. In this review, basic principles, current acquisition protocols, and pharmacokinetic models used for CT perfusion imaging of the liver are described. Various oncologic applications of CT perfusion of the liver are discussed and current challenges, as well as possible solutions, for CT perfusion are presented.

Assessment of tumor grade and angiogenesis in colorectal cancer: whole-volume perfusion CT

RATIONALE AND OBJECTIVES

The preoperative evaluation of tumor grading and angiogenesis has important clinical implications in the treatment and prognosis of patients with colorectal cancers (CRCs). The aim of the present study was to assess tumor perfusion with 256-slice computed tomography (CT) using whole-volume perfusion technology before surgery, and to investigate the differences in the perfusion parameters among tumor grades and the correlation between perfusion parameters and pathologic results in CRC.

MATERIALS AND METHODS

Thirty-seven patients with CRC confirmed by endoscopic pathology underwent whole-volume perfusion CT assessments with a 256-slice CT and surgery. Quantitative values for blood flow, blood volume, and time to peak were determined using commercial software. After surgery, resected specimens were analyzed immunohistochemically with CD105 antibodies for the quantification of microvessel density (MVD). The difference in CT perfusion parameters and MVD among different tumor differentiation grades was evaluated by the Student-Newman-Keuls test. The correlations between CT perfusion parameters and MVD were evaluated using the Pearson correlation analysis.

RESULTS

The mean blood flow was significantly different among well, moderately, and poorly differentiated groups (61.17 ± 17.97, 34.80 ± 13.06, and 22.24 ± 9.31 mL/minute/100 g, respectively; P < .05). The blood volume in the well-differentiated group was significantly higher than that in the moderately differentiated group (33.96 ± 24.81 vs. 16.93 ± 5.73 mL/100 g; P = .002) and that in the poorly differentiated group (33.96 ± 24.81 vs. 18.05 ± 6.01 mL/100 g; P = .009). The time to peak in the poorly differentiated group was significantly longer than that in the well-differentiated group (27.81 ± 11.95 vs. 17.60 ± 8.53 seconds; P = .016) and that in the moderately differentiated group (27.81 ± 11.95 vs. 18.94 ± 7.47 seconds; P = .028). There was no significant difference in the MVD among well, moderately, and poorly differentiated groups (33.47 ± 14.69, 28.89 ± 11.82, and 29.89 ± 11.02, respectively; P > .05). There was no significant correlation between CT perfusion parameters and MVD (r = 0.201, 0.295, and -0.178, respectively; P = .233, .076, and .292, respectively).

CONCLUSIONS

CT whole-volume perfusion technology has the potential to evaluate pathologic differentiation grade of CRC before surgery. However, preoperative perfusion CT parameters do not reflect the MVD of CRC.

State of the art: Response assessment in lung cancer in the era of genomic medicine

Tumor response assessment has been a foundation for advances in cancer therapy. Recent discoveries of effective targeted therapy for specific genomic abnormalities in lung cancer and their clinical application have brought revolutionary advances in lung cancer therapy and transformed the oncologist's approach to patients with lung cancer. Because imaging is a major method of response assessment in lung cancer both in clinical trials and practice, radiologists must understand the genomic alterations in lung cancer and the rapidly evolving therapeutic approaches to effectively communicate with oncology colleagues and maintain the key role in lung cancer care. This article describes the origin and importance of tumor response assessment, presents the recent genomic discoveries in lung cancer and therapies directed against these genomic changes, and describes how these discoveries affect the radiology community. The authors then summarize the conventional Response Evaluation Criteria in Solid Tumors and World Health Organization guidelines, which continue to be the major determinants of trial endpoints, and describe their limitations particularly in an era of genomic-based therapy. More advanced imaging techniques for lung cancer response assessment are presented, including computed tomography tumor volume and perfusion, dynamic contrast material-enhanced and diffusion-weighted magnetic resonance imaging, and positron emission tomography with fluorine 18 fluorodeoxyglucose and novel tracers. State-of-art knowledge of lung cancer biology, treatment, and imaging will help the radiology community to remain effective contributors to the personalized care of lung cancer patients.

Integrated ¹⁸F-FDG PET/perfusion CT for the monitoring of neoadjuvant chemoradiotherapy in rectal carcinoma: correlation with histopathology

PURPOSE

The aim of this study was to prospectively monitor changes in the flow-metabolic phenotype (ΔFMP) of rectal carcinoma (RC) after neoadjuvant chemoradiotherapy (CRT) and to evaluate whether ΔFMP of RC correlate with histopathological prognostic factors including response to CRT.

METHODS

Sixteen patients with RC (12 men, mean age 60.7 ± 12.8 years) underwent integrated (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/perfusion CT (PET/PCT), followed by neoadjuvant CRT and surgery. In 13 patients, PET/PCT was repeated after CRT. Perfusion [blood flow (BF), blood volume (BV), mean transit time (MTT)] and metabolic [maximum and mean standardized uptake values (SUVmax, SUVmean)] parameters as well as the FMP (BF × SUVmax) were determined before and after CRT by two independent readers and correlated to histopathological prognostic factors of RC (microvessel density, necrosis index, regression index, vascular invasion) derived from resected specimens. The diagnostic performance of ΔFMP for prediction of treatment response was determined.

RESULTS

FMP significantly decreased after CRT (p < 0.001), exploiting higher changes after CRT as compared to changes of perfusion and metabolic parameters alone. Before CRT, no significant correlations were found between integrated PET/PCT and any of the histopathological parameters (all p > 0.05). After CRT, BV and SUVmax correlated positively with the necrosis index (r = 0.67/0.70), SUVmax with the invasion of blood vessels (r = 0.62) and ΔFMP with the regression index (r = 0.88; all p < 0.05). ΔFMP showed high accuracy for prediction of histopathological response to CRT (AUC 0.955, 95 % confidence interval 0.833-1.000, p < 0.01) using a cut-off value of -75%.

CONCLUSION

In RC, ΔFMP derived from integrated (18)F-FDG PET/PCT is useful for monitoring the effects of neoadjuvant CRT and allows prediction of histopathological response to CRT.

Simulation Evaluation of Quantitative Myocardial Perfusion Assessment from Cardiac CT

Contrast enhancement on cardiac CT provides valuable information about myocardial perfusion and methods have been proposed to assess perfusion with static and dynamic acquisitions. There is a lack of knowledge and consensus on the appropriate approach to ensure 1) sufficient diagnostic accuracy for clinical decisions and 2) low radiation doses for patient safety. This work developed a thorough dynamic CT simulation and several accepted blood flow estimation techniques to evaluate the performance of perfusion assessment across a range of acquisition and estimation scenarios. Cardiac CT acquisitions were simulated for a range of flow states (Flow = 0.5, 1, 2, 3 ml/g/min, cardiac output = 3,5,8 L/min). CT acquisitions were simulated with a validated CT simulator incorporating polyenergetic data acquisition and realistic x-ray flux levels for dynamic acquisitions with a range of scenarios including 1, 2, 3 sec sampling for 30 sec with 25, 70, 140 mAs. Images were generated using conventional image reconstruction with additional image-based beam hardening correction to account for iodine content. Time attenuation curves were extracted for multiple regions around the myocardium and used to estimate flow. In total, 2,700 independent realizations of dynamic sequences were generated and multiple MBF estimation methods were applied to each of these. Evaluation of quantitative kinetic modeling yielded blood flow estimates with an root mean square error (RMSE) of ∼0.6 ml/g/min averaged across multiple scenarios. Semi-quantitative modeling and qualitative static imaging resulted in significantly more error (RMSE = ∼1.2 and ∼1.2 ml/min/g respectively). For quantitative methods, dose reduction through reduced temporal sampling or reduced tube current had comparable impact on the MBF estimate fidelity. On average, half dose acquisitions increased the RMSE of estimates by only 18% suggesting that substantial dose reductions can be employed in the context of quantitative myocardial blood flow estimation. In conclusion, quantitative model-based dynamic cardiac CT perfusion assessment is capable of accurately estimating MBF across a range of cardiac outputs and tissue perfusion states, outperforms comparable static perfusion estimates, and is relatively robust to noise and temporal subsampling.

Comparison of blood flow models and acquisitions for quantitative myocardial perfusion estimation from dynamic CT

Myocardial blood flow (MBF) can be estimated from dynamic contrast enhanced (DCE) cardiac CT acquisitions, leading to quantitative assessment of regional perfusion. The need for low radiation dose and the lack of consensus on MBF estimation methods motivates this study to refine the selection of acquisition protocols and models for CT-derived MBF. DCE cardiac CT acquisitions were simulated for a range of flow states (MBF = 0.5, 1, 2, 3 ml (min g)(-1), cardiac output = 3, 5, 8 L min(-1)). Patient kinetics were generated by a mathematical model of iodine exchange incorporating numerous physiological features including heterogenenous microvascular flow, permeability and capillary contrast gradients. CT acquisitions were simulated for multiple realizations of realistic x-ray flux levels. CT acquisitions that reduce radiation exposure were implemented by varying both temporal sampling (1, 2, and 3 s sampling intervals) and tube currents (140, 70, and 25 mAs). For all acquisitions, we compared three quantitative MBF estimation methods (two-compartment model, an axially-distributed model, and the adiabatic approximation to the tissue homogeneous model) and a qualitative slope-based method. In total, over 11 000 time attenuation curves were used to evaluate MBF estimation in multiple patient and imaging scenarios. After iodine-based beam hardening correction, the slope method consistently underestimated flow by on average 47.5% and the quantitative models provided estimates with less than 6.5% average bias and increasing variance with increasing dose reductions. The three quantitative models performed equally well, offering estimates with essentially identical root mean squared error (RMSE) for matched acquisitions. MBF estimates using the qualitative slope method were inferior in terms of bias and RMSE compared to the quantitative methods. MBF estimate error was equal at matched dose reductions for all quantitative methods and range of techniques evaluated. This suggests that there is no particular advantage between quantitative estimation methods nor to performing dose reduction via tube current reduction compared to temporal sampling reduction. These data are important for optimizing implementation of cardiac dynamic CT in clinical practice and in prospective CT MBF trials.

CT-perfusion versus [(15)O]H2O PET in lung tumors: effects of CT-perfusion methodology

PURPOSE

Nowadays, PET and dynamic contrast enhanced CT or MRI are used to assess tumor blood perfusion. Although [(15)O]H2O PET is the gold standard, it is hardly available for routine clinical practice, due to the short half-life of (15)O. However, the lack of uniformity in scanning and analytic methods limits the use of CT perfusion (CTP) in clinical trials and practice. This study compares [(15)O]H2O PET with CT based perfusion in lung tumors and assesses the effects of various CTP postprocessing and analytical methods on the CTP results using [(15)O]H2O PET as the reference technique.

METHODS

Various CTP analysis and image postprocessing methods were assessed. Furthermore, parametric images were obtained using the Slope method. Volumes of interests were defined using several different segmentation methods including Hounsfield unit based contouring thresholds, both with and without framewise application of dynamic contouring thresholds to exclude lung tissue or intravascular contrast. A head-to-head comparison of tumor perfusion obtained by CTP and [(15)O]H2O PET was performed using linear regressions, Bland-Altman plots, and an intraclass correlation coefficient (ICC). In addition, the different postprocessing methods were compared reciprocally.

RESULTS

In six lung cancer patients, perfusion assessed using CTP studies combined with the Slope method correlated best with [(15)O]H2O PET (ICC = 0.88; R(2) = 0.89; Y = 0.80). The Mullani-Gould method showed best correlation with the Slope method (ICC ≥ 0.71; R(2) ≥ 0.80; Y = 0.71-1.35). These correlations were obtained using dynamic contouring thresholds and show the influence of CTP postprocessing methods.

CONCLUSIONS

Tumor perfusion assessed by CTP in combination with dynamic contouring thresholds using the Slope method correlates well with [(15)O]H2O PET. This suggests that CTP can be used as a method to evaluate tumor perfusion in lung cancer.