Usefulness of intratumoral perfusion analysis for assessing biological features of non-functional pancreatic neuroendocrine neoplasm

PURPOSE

Here, we evaluated the usefulness of intratumoral perfusion analysis using preoperative contrast-enhanced CT (E-CT) to assess biological features of non-functional pancreatic neuroendocrine neoplasms (NF-PanNENs).

METHODS

We retrospectively studied 44 patients who underwent curative surgery for NF-PanNENs. We used preoperative E-CT with compartment model analysis to calculate the tumor perfusion parameters K1 (inflow rate constant), 1/k2 (mean transit time), and K1/k2 (distribution volume). We assessed the association between perfusion parameters and biological features of NF-PanNENs, including the WHO classification tumor histopathological grade and prognosis after surgery.

RESULTS

Patients in this study had a neuroendocrine tumor (NET) G1 (n = 32) or NET G2 (n = 12). Neither NET G3 or NEC tumors were observed. Among perfusion parameters, K1 was the most accurate predictor of the high-grade tumor (AUC: 0.726). K1-low (< 0.028 s-1) was significantly associated with large tumors (≥ 20 mm) (p = 0.022), high mitotic index (p = 0.017), high Ki-67 index (p = 0.004), and lymphatic invasion (p = 0.025). Synchronous extra-pancreatic metastasis, including lymph node metastasis or liver metastasis, more frequently developed in K1-low patients than in K1-high patients (29% vs 4%, p = 0.025). Disease-free survival of patients with a K1-low tumor was poorer than that of patients with a K1-high tumor (p = 0.005). Furthermore, no patient with a K1-high tumor developed recurrence after initial surgery.

CONCLUSION

The perfusion parameters obtained using E-CT were significantly associated with biological features and prognosis of NF-PanNENs.

Comparison of CT- and MRI-Based Quantification of Tumor Heterogeneity and Vascularity for Correlations with Prognostic Biomarkers and Survival Outcomes: A Single-Center Prospective Cohort Study

BACKGROUND

Tumor heterogeneity and vascularity can be noninvasively quantified using histogram and perfusion analyses on computed tomography (CT) and magnetic resonance imaging (MRI). We compared the association of histogram and perfusion features with histological prognostic factors and progression-free survival (PFS) in breast cancer patients on low-dose CT and MRI.

METHODS

This prospective study enrolled 147 women diagnosed with invasive breast cancer who simultaneously underwent contrast-enhanced MRI and CT before treatment. We extracted histogram and perfusion parameters from each tumor on MRI and CT, assessed associations between imaging features and histological biomarkers, and estimated PFS using the Kaplan-Meier analysis.

RESULTS

Out of 54 histogram and perfusion parameters, entropy on T2- and postcontrast T1-weighted MRI and postcontrast CT, and perfusion (blood flow) on CT were significantly associated with the status of subtypes, hormone receptors, and human epidermal growth factor receptor 2 (p < 0.05). Patients with high entropy on postcontrast CT showed worse PFS than patients with low entropy (p = 0.053) and high entropy on postcontrast CT negatively affected PFS in the Ki67-positive group (p = 0.046).

CONCLUSIONS

Low-dose CT histogram and perfusion analysis were comparable to MRI, and the entropy of postcontrast CT could be a feasible parameter to predict PFS in breast cancer patients.

Machine Learning Models That Integrate Tumor Texture and Perfusion Characteristics Using Low-Dose Breast Computed Tomography Are Promising for Predicting Histological Biomarkers and Treatment Failure in Breast Cancer Patients

Simple Summary

Tumor angiogenesis and heterogeneity are associated with poor prognosis for breast cancer. Advances in computer technology have made it possible to noninvasively quantify tumor angiogenesis and heterogeneity appearing in imaging data. We investigated whether low-dose CT could be used as a method for functional oncology imaging to assess tumor heterogeneity and angiogenesis in breast cancer and to predict noninvasively histological biomarkers and molecular subtypes of breast cancer. Low-dose breast CT has advantages in terms of radiation safety and patient convenience. Our study produced promising results for the use of machine learning with low-dose breast CT to identify histological prognostic factors including hormone receptor and human epidermal growth factor receptor 2 status, grade, and molecular subtype in patients with invasive breast cancer. Machine learning that integrates texture and perfusion features of breast cancer with low-dose CT can provide valuable information for the realization of precision medicine.

Abstract

This prospective study enrolled 147 women with invasive breast cancer who underwent low-dose breast CT (80 kVp, 25 mAs, 1.01–1.38 mSv) before treatment. From each tumor, we extracted eight perfusion parameters using the maximum slope algorithm and 36 texture parameters using the filtered histogram technique. Relationships between CT parameters and histological factors were analyzed using five machine learning algorithms. Performance was compared using the area under the receiver-operating characteristic curve (AUC) with the DeLong test. The AUCs of the machine learning models increased when using both features instead of the perfusion or texture features alone. The random forest model that integrated texture and perfusion features was the best model for prediction (AUC = 0.76). In the integrated random forest model, the AUCs for predicting human epidermal growth factor receptor 2 positivity, estrogen receptor positivity, progesterone receptor positivity, ki67 positivity, high tumor grade, and molecular subtype were 0.86, 0.76, 0.69, 0.65, 0.75, and 0.79, respectively. Entropy of pre- and postcontrast images and perfusion, time to peak, and peak enhancement intensity of hot spots are the five most important CT parameters for prediction. In conclusion, machine learning using texture and perfusion characteristics of breast cancer with low-dose CT has potential value for predicting prognostic factors and risk stratification in breast cancer patients.

Current Development and Applications of Super-Resolution Ultrasound Imaging

Abnormal changes of the microvasculature are reported to be key evidence of the development of several critical diseases, including cancer, progressive kidney disease, and atherosclerotic plaque. Super-resolution ultrasound imaging is an emerging technology that can identify the microvasculature noninvasively, with unprecedented spatial resolution beyond the acoustic diffraction limit. Therefore, it is a promising approach for diagnosing and monitoring the development of diseases. In this review, we introduce current super-resolution ultrasound imaging approaches and their preclinical applications on different animals and disease models. Future directions and challenges to overcome for clinical translations are also discussed.

Quantitative Imaging Parameters of Contrast-Enhanced Micro-Computed Tomography Correlate with Angiogenesis and Necrosis in a Subcutaneous C6 Glioma Model

The aim of this work was to systematically obtain quantitative imaging parameters with static and dynamic contrast-enhanced (CE) X-ray imaging techniques and to evaluate their correlation with histological biomarkers of angiogenesis in a subcutaneous C6 glioma model. Enhancement (E), iodine concentration (CI), and relative blood volume (rBV) were quantified from single- and dual-energy (SE and DE, respectively) micro-computed tomography (micro-CT) images, while rBV and volume transfer constant (Ktrans) were quantified from dynamic contrast-enhanced (DCE) planar images. CI and rBV allowed a better discernment of tumor regions from muscle than E in SE and DE images, while no significant differences were found for rBV and Ktrans in DCE images. An agreement was found in rBV for muscle quantified with the different imaging protocols, and in CI and E quantified with SE and DE protocols. Significant strong correlations (Pearson r > 0.7, p < 0.05) were found between a set of imaging parameters in SE images and histological biomarkers: E and CI in tumor periphery were associated with microvessel density (MVD) and necrosis, E and CI in the complete tumor with MVD, and rBV in the tumor periphery with MVD. In conclusion, quantitative imaging parameters obtained in SE micro-CT images could be used to characterize angiogenesis and necrosis in the subcutaneous C6 glioma model.

Low-Dose Perfusion Computed Tomography for Breast Cancer to Quantify Tumor Vascularity: Correlation With Prognostic Biomarkers

OBJECTIVES

The aim of this study was to investigate the feasibility of using low-dose perfusion computed tomography (CT) in breast cancers for quantification of tumor vascularity and to correlate perfusion indexes with prognostic biomarkers.

MATERIALS AND METHODS

This preliminary study was approved by our institutional review board. Signed informed consent was obtained from all 70 enrolled patients with invasive breast cancers. Low-dose perfusion CT was performed with the patient in the prone position using a spectral CT device set at 80 kVp and 30 mAs (1.30-1.40 mSv). Images were analyzed using commercial software applying the maximum slope algorithm. On CT perfusion maps, perfusion (mL/min per 100 mL), blood volume (mL/100 g), time-to-peak enhancement (second), and peak enhancement intensity (HU) were measured in the tumor, normal breast glandular tissues, and fat. Tumor grade, estrogen receptor (ER), human epidermal growth factor receptor 2 (HER2), and Ki67 level were evaluated using histopathology. Statistically, CT perfusion indexes of the tumor and normal glandular tissues or fat were compared using the Wilcoxon signed-rank test, and CT indexes were correlated with histological characteristics using the Mann-Whitney U or Kruskal-Wallis tests. We also correlated CT indexes with magnetic resonance imaging enhancement characteristics.

RESULTS

In breast cancers, perfusion, blood volume, and peak enhancement intensity values were significantly higher, and time to peak was shorter than in normal glandular tissues and fat (P < 0.001). Perfusion increased significantly in high-grade, ER-, or HER2+ cancers (P < 0.05). Time to peak decreased in ER-, HER2+, and high-grade cancers or in those with high Ki67 levels (P < 0.05). Peak enhancement intensity significantly increased in high-grade cancers (P < 0.05). HER2 overexpressing cancers showed significantly higher perfusion and shorter time to peak than luminal-type cancers (P < 0.05). Perfusion increased and time to peak decreased significantly in cancers with washout enhancement patterns on magnetic resonance imaging.

CONCLUSIONS

Low-dose perfusion CT in the prone position is feasible to quantify tumor vascularity in breast cancers, and CT perfusion indexes are significantly correlated with prognostic biomarkers and molecular subtypes of breast cancer.

Clinical Pilot Application of Super-Resolution US Imaging in Breast Cancer

Recently, we proved in the first measurements of breast carcinomas the feasibility of super-resolution ultrasound (US) imaging by motion-model ultrasound localization microscopy in a clinical setup. Nevertheless, pronounced in-plane and out-of-plane motions, a nonoptimized microbubble injection scheme, the lower frame rate and the larger slice thickness made the processing more complex than in preclinical investigations. Here, we compare the results of state-of-the-art contrast-enhanced to super-resolution US imaging and systematically analyze the measurements to get indications for the improvement of image acquisition and processing in the future clinical studies. In this regard, the application of a saturation model to the reconstructed vessels is shown to be a valuable tool not only to estimate the measurement times necessary to adequately reconstruct the microvasculature but also for the validation of the measurements. The parameters from this model can also serve to optimize contrast agent concentration and injection protocols. Finally, for the measurements of well-perfused tumors, we observed between 28% and 50% filling for 90-s examination times.

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.

Accumulating nanoparticles by EPR: A route of no return

Nanoparticle-based drug delivery to ease anticancer therapy relies primarily on the enhanced permeability and retention effect (EPR). The leaky vascular structure in tumors allows extravasation of nanoparticles, often termed passive targeting. Long term retention of nanoparticles is attributed to the lack of lymphatic drainage, and unidirectional extravasation has been implied. Fluorescent liposomes with a plasma half-life of 29h were injected into tumor-bearing rats, and biodistribution in tumor, skin, paws and ears was monitored via in vivo fluorescence measurements. To calculate tissue accumulation, an algorithm was developed to subtract the blood signal from the total fluorescence recorded. Accumulation in tumor tissue was much higher than that in other tissues monitored, initially exhibiting very rapid accumulation followed by a long plateau phase with little change. Discontinuous plasmapheresis was established that was as effective as highly sophisticated clinical plasmapheresis. We observed no difference in the tumor tissue's accumulation when plasmapheresis was performed 22h after liposome injection. In contrast, plasmapheresis led to a significant inhibition of further accumulation in other tissues. When the liposomes' blood concentration was rapidly lowered, we detected no drop in tumor fluorescence. Thus extravasation via EPR is most likely a route of no return. These data support the emerging view of a more dynamic model of EPR, where gaps or entire vessels may open and close over time, or accumulated liposomes become entangled within the pores, hampering further accumulation.

Correlation of volumetric perfusion CT parameters with hypoxia inducible factor-1 alpha expression in a rabbit VX2 tumor model

BACKGROUND

Hypoxia inducible factor-1 alpha (HIF-1α) plays a critical role in tumoral angiogenesis and HIF-1α overexpression is associated with an increased risk of patient mortality in many cancers. A number of studies have introduced perfusion computed tomography (CT) as a monitoring modality for antiangiogenic therapy.

PURPOSE

To investigate significance of volumetric perfusion CT parameters in relationship to HIF-1α expression in VX2 tumor rabbit models.

MATERIAL AND METHODS

Twenty VX2 carcinoma tumors of bilateral back muscles of 10 rabbits were evaluated with serial volumetric perfusion CT in 7, 10, and 14 days after tumor implantation. CT perfusion data were analyzed to calculate blood flow (BF), blood volume (BV), and permeability surface area product (PS) of whole tumor and non-necrotic peripheral area (periphery). Immunohistochemical analysis of HIF-1α expression and microvessel density (MVD) was performed.

RESULTS

HIF-1α was expressed in 12 tumors; two, three, and seven tumors classified as scores 1, 2 and 3, respectively. Mean MVD was 24.85 ± 13.7. PS of both the whole tumor and periphery showed positive correlations with HIF-1α score (r = 0.41, P = 0.046; r = 0.43, P = 0.002, respectively). BV of periphery showed a negative correlation with HIF-1α (r = -0.48, P = 0.040). There was strong positive correlation between HIF-1α expression and MVD (r = 0.82, P < 0.001).

CONCLUSION

In VX2 tumors, volumetric perfusion CT parameters were of limited value for the prediction of HIF-1α activity although HIF-1α expression was found to be weakly positively correlated with PS and negatively correlated with BV.

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.

A bioimage informatics based reconstruction of breast tumor microvasculature with computational blood flow predictions

Induction of tumor angiogenesis is among the hallmarks of cancer and a driver of metastatic cascade initiation. Recent advances in high-resolution imaging enable highly detailed three-dimensional geometrical representation of the whole-tumor microvascular architecture. This enormous increase in complexity of image-based data necessitates the application of informatics methods for the analysis, mining and reconstruction of these spatial graph data structures. We present a novel methodology that combines ex-vivo high-resolution micro-computed tomography imaging data with a bioimage informatics algorithm to track and reconstruct the whole-tumor vasculature of a human breast cancer model. The reconstructed tumor vascular network is used as an input of a computational model that estimates blood flow in each segment of the tumor microvascular network. This formulation involves a well-established biophysical model and an optimization algorithm that ensures mass balance and detailed monitoring of all the vessels that feed and drain blood from the tumor microvascular network. Perfusion maps for the whole-tumor microvascular network are computed. Morphological and hemodynamic indices from different regions are compared to infer their role in overall tumor perfusion.

Micro-CT imaging of tumor angiogenesis: quantitative measures describing micromorphology and vascularization

Angiogenesis is a hallmark of cancer, and its noninvasive visualization and quantification are key factors for facilitating translational anticancer research. Using four tumor models characterized by different degrees of aggressiveness and angiogenesis, we show that the combination of functional in vivo and anatomical ex vivo X-ray micro-computed tomography (μCT) allows highly accurate quantification of relative blood volume (rBV) and highly detailed three-dimensional analysis of the vascular network in tumors. Depending on the tumor model, rBV values determined using in vivo μCT ranged from 2.6% to 6.0%, and corresponds well with the values assessed using IHC. Using ultra-high-resolution ex vivo μCT, blood vessels as small as 3.4 μm and vessel branches up to the seventh order could be visualized, enabling a highly detailed and quantitative analysis of the three-dimensional micromorphology of tumor vessels. Microvascular parameters such as vessel size and vessel branching correlated very well with tumor aggressiveness and angiogenesis. In rapidly growing and highly angiogenic A431 tumors, the majority of vessels were small and branched only once or twice, whereas in slowly growing A549 tumors, the vessels were much larger and branched four to seven times. Thus, we consider that combining highly accurate functional with highly detailed anatomical μCT is a useful tool for facilitating high-throughput, quantitative, and translational (anti-) angiogenesis and antiangiogenesis research.

Mounting a strategic offense: fighting tumor vasculature with oncolytic viruses

Blood supply within a tumor drives progression and ultimately allows for metastasis. Many anticancer therapies target tumor vasculature, but their individual effectiveness is limited because they induce indirect cell death. Agents that disrupt nascent and/or established tumor vasculature while simultaneously killing cancer cells would certainly have a greater impact. Oncolytic virotherapy utilizes attenuated viruses that replicate specifically within a tumor. They induce cytotoxicity through a combination of direct cell lysis, antitumor immune stimulation, and recently identified antitumor vascular effects. This review summarizes the novel preclinical and clinical evidence regarding the antitumor vascular effects of oncolytic viruses, which include infection and lysis of tumor endothelial cells, natural or genetically engineered antiangiogenic properties, and combination therapy with clinically approved antivascular agents.

Antiangiogenic and radiation therapy: early effects on in vivo computed tomography perfusion parameters in human colon cancer xenografts in mice

OBJECTIVES

To assess early treatment effects on computed tomography (CT) perfusion parameters after antiangiogenic and radiation therapy in subcutaneously implanted, human colon cancer xenografts in mice and to correlate in vivo CT perfusion parameters with ex vivo assays of tumor vascularity and hypoxia.

MATERIALS AND METHODS

Dynamic contrast-enhanced CT (perfusion CT, 129 mAs, 80 kV, 12 slices × 2.4 mm; 150 μL iodinated contrast agent injected at a rate of 1 mL/min intravenously) was performed in 100 subcutaneous human colon cancer xenografts on baseline day 0. Mice in group 1 (n=32) received a single dose of the antiangiogenic agent bevacizumab (10 mg/kg body weight), mice in group 2 (n=32) underwent a single radiation treatment (12 Gy), and mice in group 3 (n=32) remained untreated. On days 1, 3, 5, and 7 after treatment, 8 mice from each group underwent a second CT perfusion scan, respectively, after which tumors were excised for ex vivo analysis. Four mice were killed after baseline scanning on day 0 for ex vivo analysis. Blood flow (BF), blood volume (BV), and flow extraction product were calculated using the left ventricle as an arterial input function. Correlation of in vivo CT perfusion parameters with ex vivo microvessel density and extent of tumor hypoxia were assessed by immunofluorescence. Reproducibility of CT perfusion parameter measurements was calculated in an additional 8 tumor-bearing mice scanned twice within 5 hours with the same CT perfusion imaging protocol.

RESULTS

The intraclass correlation coefficients for BF, BV, and flow extraction product from repeated CT perfusion scans were 0.93 (95% confidence interval: 0.78, 0.97), 0.88 (0.66, 0.95), and 0.88 (0.56, 0.95), respectively. Changes in perfusion parameters and tumor volumes over time were different between treatments. After bevacizumab treatment, all 3 perfusion parameters significantly decreased from day 1 (P ≤ 0.006) and remained significantly decreased until day 7 (P ≤ 0.008); tumor volume increased significantly only on day 7 (P=0.04). After radiation treatment, all 3 perfusion parameters decreased significantly on day 1 (P < 0.001); BF and flow extraction product increased again on day 3 and 5, although without reaching statistically significant difference; and tumor volumes did not change significantly at all time points (P ≥ 0.3). In the control group, all 3 perfusion parameters did not change significantly, whereas tumor volume increased significantly at all the time points, compared with baseline (P ≤ 0.04). Ex vivo immunofluorescent staining showed good correlation between all 3 perfusion parameters and microvessel density (ρ=0.71, 0.66, and 0.69 for BF, BV, and flow extraction product, respectively; P < 0.001). There was a trend toward negative correlation between extent of hypoxia and all 3 perfusion parameters (ρ=-0.53, -0.47, and -0.40 for BF, BV, and flow extraction product, respectively; P ≥ 0.05).

CONCLUSIONS

CT perfusion allows a reproducible, noninvasive assessment of tumor vascularity in human colon cancer xenografts in mice. After antiangiogenic and radiation therapy, BF, BV, and flow extraction product significantly decrease and change faster than the tumor volume.

CT color mapping of the arterial enhancement fraction of VX2 carcinoma implanted in rabbit liver: comparison with perfusion CT

OBJECTIVE

The purpose of this study was to compare the arterial enhancement fraction (AEF) calculated at multiphasic liver CT with the hepatic perfusion index (HPI) measured with cine mode perfusion CT.

MATERIALS AND METHODS

Cine mode perfusion CT was performed after VX2 tumor implantation in the livers of 10 rabbits. HPI and its color map were obtained with a computer application. With raw data from cine mode perfusion CT, images were extracted in the unenhanced, arterial, and portal venous phases to simulate multiphasic liver CT. On the basis of simulated multiphasic CT images, the AEF color map was obtained with prototype software. HPI and AEF were compared for the same regions of interest in the liver parenchyma, whole liver tumor, and viable tumor portion.

RESULTS

In the liver parenchyma, the mean HPI was 23.3% ± 2.6% (SD) and the AEF 24.4% ± 2.8%; in whole liver tumor, 73.4% ± 9.5% and 78.4% ± 10.5%; and in the viable tumor portion, 78.0% ± 7.7% and 78.3% ± 7.5%. The differences were not statistically significant (p > 0.05, Wilcoxon's signed rank test). Measurement agreement between the two parameters was moderate (Bland-Altman 95% limits of agreement, -14.9% and 19.2%), but there was a strong positive correlation between AEF and HPI (within-subject r = 0.91, p < 0.001). Functional maps of HPI and AEF correlated with the histologic findings.

CONCLUSION

AEF calculated from simulated multiphasic liver CT images correlates strongly with HPI obtained at cine mode perfusion CT. Further study of the AEF is warranted to explore its value in providing hepatic perfusion information without additional radiation exposure.

The role of perfusion CT as a follow-up modality after transcatheter arterial chemoembolization: an experimental study in a rabbit model

OBJECTIVES

To prospectively evaluate the feasibility of perfusion CT as a follow-up modality after transcatheter arterial chemoembolization (TACE) and to compare these findings with those of histopathology as the reference standard in a VX2 tumor rabbit model.

MATERIALS AND METHODS

VX2 carcinoma tumors were implanted into the liver of 20 rabbits 3 weeks prior to TACE. Perfusion CT was performed prior to TACE and 1- and 4-week after TACE. After obtaining perfusion index maps on perfusion CT, 2 radiologists measured the parametric perfusion indices of blood flow (BF), blood volume (BV), mean transit time (MTT), permeability of the capillary vessel surface (PS), and hepatic arterial fraction (HAF) of primary tumors on pre-TACE perfusion CT, chemoembolized primary tumors on 1-week perfusion CT, and recurred tumors on 4-week perfusion CT. The normal liver parenchyma indices were also recorded. In addition, the radiologists investigated the presence of a recurred tumor adjacent to the chemoembolized area on perfusion index maps of 4-week CT images. The areas of higher hepatic blood flow (HBF), hepatic blood volume (HBV), PS, and HAF, and lower MTT on 4-week perfusion CT than the normal liver parenchyma and the identical area on 1-week perfusion CT were considered as recurred tumors. Histopathology revealed the presence of a recurred tumor, and mean vessel density (MVD) was determined by immunochemical staining for CD31. CT perfusion indices were compared by use of the t test. Comparisons were made for the primary tumor versus normal liver parenchyma on pre-TACE CT, the primary tumor on pre-TACE CT versus the chemoembolized tumor on 1-week CT, the recurred tumor on 4-week CT versus the identical area on 1-week CT, and the primary tumor on pre-TACE CT versus the recurred tumor on 4-week CT. For the detection of recurred tumors, the sensitivity and specificity for 4-week perfusion CT were calculated. Correlation analysis between the recurred tumor perfusion indices and the MVD of the corresponding tumor region was performed. Among 20 rabbits, 6 were excluded from the analysis, and results were based on 14 rabbits.

RESULTS

Recurred tumors were histologically proven in 8 of 14 rabbits (57.1%). The BF, BV, PS, and HAF indices of primary tumors were significantly higher, whereas the MTT was significantly lower than that of the normal liver parenchyma on pre-TACE perfusion CT and that of chemoembolized areas on 1-week perfusion CT (P < 0.05). In addition, recurred tumors also showed significantly higher BF, BV, PS, and HAF, and lower MTT indices than the identical areas on 1-week perfusion CT (P < 0.05). The perfusion indices of recurred tumors were not significantly different from the indices of primary tumors (P > 0.05). Both sensitivity and specificity were 100% for 4-week perfusion CT. There were significant positive correlations between BF (r = 0.947), BV (r = 0.758), PS (r = 0.759), HAF (r = 0.955), and MVD in recurred tumors, and a significant inverse correlation between MTT (r = -0.782) and MVD was observed (P < 0.05).

CONCLUSIONS

We believe that perfusion CT is a feasible alternative modality for the successful early response assessment and early detection of a marginally recurred tumor after TACE. However, perfusion CT has limitations for the prediction of tumor recurrence after TACE.