Technical prerequisites and imaging protocols for CT perfusion imaging in oncology

Pancreatic CT perfusion: quantitative meta-analysis of disease discrimination, protocol development, and effect of CT parameters

BACKGROUND

This study provides a quantitative meta-analysis of pancreatic CT perfusion studies, investigating choice of study parameters, ability for quantitative discrimination of pancreatic diseases, and influence of acquisition and reconstruction parameters on reported results.

METHODS

Based on a PubMed search with key terms 'pancreas' or 'pancreatic,' 'dynamic' or 'perfusion,' and 'computed tomography' or 'CT,' 491 articles published between 1982 and 2020 were screened for inclusion in the study. Inclusion criteria were: reported original data, human subjects, five or more datasets, measurements of pancreas or pancreatic pathologies, and reported quantitative perfusion parameters. Study parameters and reported quantitative measurements were extracted, and heterogeneity of study parameters and trends over time are analyzed. Pooled data were tested with weighted ANOVA and ANCOVA models for differences in perfusion results between normal pancreas, pancreatitis, PDAC (pancreatic ductal adenocarcinoma), and non-PDAC (e.g., neuroendocrine tumors, insulinomas) and based on study parameters.

RESULTS

Reported acquisition parameters were heterogeneous, except for contrast agent amount and injection rate. Tube potential and slice thickness decreased, whereas tube current time product and scan coverage increased over time. Blood flow and blood volume showed significant differences between pathologies (both p < 0.001), unlike permeability (p = 0.11). Study parameters showed a significant effect on reported quantitative measurements (p < 0.05).

CONCLUSIONS

Significant differences in perfusion measurements between pathologies could be shown for pooled data despite observed heterogeneity in study parameters. Statistical analysis indicates most influential parameters for future optimization and standardization of acquisition protocols.

CRITICAL RELEVANCE STATEMENT

Quantitative CT perfusion enables differentiation of pancreatic pathologies despite the heterogeneity of study parameters in current clinical practice.

Current Imaging Diagnosis of Hepatocellular Carcinoma

Simple Summary

The role of imaging in the management of hepatocellular carcinoma (HCC) has significantly evolved and expanded beyond the plain radiological confirmation of the tumor based on the typical appearance in a multiphase contrast-enhanced CT or MRI examination. The introduction of hepatobiliary contrast agents has enabled the diagnosis of hepatocarcinogenesis at earlier stages, while the application of ultrasound contrast agents has drastically upgraded the role of ultrasound in the diagnostic algorithms. Newer quantitative techniques assessing blood perfusion on CT and MRI not only allow earlier diagnosis and confident differentiation from other lesions, but they also provide biomarkers for the evaluation of treatment response. As distinct HCC subtypes are identified, their correlation with specific imaging features holds great promise for estimating tumor aggressiveness and prognosis. This review presents the current role of imaging and underlines its critical role in the successful management of patients with HCC.

Abstract

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer related death worldwide. Radiology has traditionally played a central role in HCC management, ranging from screening of high-risk patients to non-invasive diagnosis, as well as the evaluation of treatment response and post-treatment follow-up. From liver ultrasonography with or without contrast to dynamic multiple phased CT and dynamic MRI with diffusion protocols, great progress has been achieved in the last decade. Throughout the last few years, pathological, biological, genetic, and immune-chemical analyses have revealed several tumoral subtypes with diverse biological behavior, highlighting the need for the re-evaluation of established radiological methods. Considering these changes, novel methods that provide functional and quantitative parameters in addition to morphological information are increasingly incorporated into modern diagnostic protocols for HCC. In this way, differential diagnosis became even more challenging throughout the last few years. Use of liver specific contrast agents, as well as CT/MRI perfusion techniques, seem to not only allow earlier detection and more accurate characterization of HCC lesions, but also make it possible to predict response to treatment and survival. Nevertheless, several limitations and technical considerations still exist. This review will describe and discuss all these imaging modalities and their advances in the imaging of HCC lesions in cirrhotic and non-cirrhotic livers. Sensitivity and specificity rates, method limitations, and technical considerations will be discussed.

Artificial Intelligence-Based Feature Analysis of Ultrasound Images of Liver Fibrosis

Liver fibrosis is a common liver disease that seriously endangers human health. Liver biopsy is the gold standard for diagnosing liver fibrosis, but its clinical use is limited due to its invasive nature. Ultrasound image examination is a widely used liver fibrosis examination method. Clinicians can diagnose the severity of liver fibrosis according to their own experience by observing the roughness of the texture of the ultrasound image, and this method is highly subjective. Under the premise that artificial intelligence technology is widely used in medical image analysis, this paper uses convolutional neural network analysis to extract the characteristics of ultrasound images of liver fibrosis and then classify the degree of liver fibrosis. Using neural network for image classification can avoid the subjectivity of manual classification and improve the accuracy of judging the degree of liver fibrosis, so as to complete the prevention and treatment of liver fibrosis. Therefore, the following work is done in this paper: (1) the research background, research significance, research status at home and abroad, and the impact of the development of medical imaging on the diagnosis of liver fibrosis are introduced; (2) the related technologies of deep learning and deep convolutional network are introduced, and the indicators of liver fibrosis degree assessment are constructed by using ultrasonic image extraction features; (3) using the collected liver fibrosis dataset to conduct model evaluation experiments, four classic CNN models are selected to compare and analyze the recognition rate. The experiments show that the GoogLeNet model has the best classification and recognition effect.

Feasibility of wide detector CT perfusion imaging performed during routine staging and restaging of pancreatic ductal adenocarcinoma

PURPOSE

To evaluate the feasibility of CT perfusion performed during routine multiphase contrast-enhanced CT on a 160 mm wide-coverage 256-slice scanner in patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

Fifty-seven patients had a CT perfusion acquisition during their routine multiphase CT. Perfusion was performed 5 to 42.5 s (15 passes at 2.5 s intervals) after intravenous contrast administration (4.2-5 ml/s), followed by pancreatic parenchymal and portal venous phases for clinical interpretation. Perfusion maps were generated and blood flow (BF), blood volume (BV), and permeability surface area product (PS) for tumor and uninvolved pancreas were calculated using deconvolution algorithms and compared to existing similar publications. Radiation dose information was recorded and size-specific dose estimate (SSDE) was calculated using body dimensions.

RESULTS

Diagnostic quality of standard images was unaffected by performing the perfusion acquisition. Average tumor center BF was 20.8 ± 12.1 ml/100 g/min, BV 2.5 ± 2.1 ml/100 g and PS 15.5 ± 39.4 ml/100 g/min. Average pancreas BF was 90.8 ± 50.2 ml/100 g/min, BV 11.9 ± 4.3 ml/100 g and PS 33.6 ± 27.7 ml/100 g/min. For the perfusion acquisition, mean SSDE was 57 ± 11 mGy, CTDI_vol 43 ± 6 mGy and DLP 685 ± 100 mGy-cm.

CONCLUSION

Adding a perfusion CT acquisition to standard pancreatic CT protocol is feasible using a wide-detector 256-slice CT scanner and adds quantitative information while maintaining diagnostic quality of the standard of care examination. This novel protocol adds no time or cost to the examination and yields perfusion parameters that are comparable to existing literature using a separate dedicated perfusion protocol.

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.

CT liver perfusion in patients with hepatocellular carcinoma: can we modify acquisition protocol to reduce patient exposure?

OBJECTIVES

To investigate the potential of decreasing the number of scans and associated radiation exposure involved in CT liver perfusion (CTLP) dynamic studies for hepatocellular carcinoma (HCC) assessment.

METHODS

Twenty-four CTLP image datasets of patients with HCC were retrospectively analyzed. All examinations were performed on a modern CT system using a standard acquisition protocol involving 35 scans with 1.7 s interval. A deconvolution-based or a standard algorithm was employed to compute ten perfusion parametric maps. 3D ROIs were positioned on 33 confirmed HCCs and non-malignant parenchyma. Analysis was repeated for two subsampled datasets generated from the original dataset by including only the (a) 18 odd-numbered scans with 3.4 s interval and (b) 18 first scans with 1.7 s interval. Standard and modified datasets were compared regarding the (a) accuracy of calculated perfusion parameters, (b) power of parametric maps to discriminate HCCs from liver parenchyma, and (c) associated radiation exposure.

RESULTS

When the time interval between successive scans was doubled, perfusion parameters of HCCs were found unaffected (p > 0.05) and the discriminating efficiency of parametric maps was preserved (p < 0.05). In contrast, significant differences were found for all perfusion parameters of HCCs when acquisition duration was reduced to half (p < 0.05), while the discriminating efficiency of four parametric maps was significantly deteriorated (p < 0.05). Modified CTLP acquisition protocols were found to involve 48.5% less patient exposure.

CONCLUSIONS

Doubling the interscan time interval may considerably reduce radiation exposure from CTLP studies performed for HCC evaluation without affecting the diagnostic efficiency of perfusion maps generated with either standard or deconvolution-based mathematical model.

KEY POINTS

• CT liver perfusion for HCC diagnosis/assessment is not routinely used in clinical practice mainly due to the associated high radiation exposure. • Two alternative acquisition protocols involving 18 scans of the liver were compared with the standard 35-scan protocol. • Increasing the time interval between successive scans to 3.4 s was found to preserve the accuracy of computed perfusion parameters derived with a standard or a deconvolution-based model and to reduce radiation exposure by 48.5%.

Iterative reconstruction algorithm improves the image quality without affecting quantitative measurements of computed tomography perfusion in the upper abdomen

•

Iterative image-reconstruction algorithm (ADMIRE) did not affect the quantitative measurements in CT perfusion.

•

Iterative image-reconstruction algorithm (ADMIRE) did not affect the time attenuation curves in CT perfusion.

•

Image noise was lower, but the SNR was higher, for iterative reconstructions in CT perfusion examinations with higher strength of noise reduction.

Objective

To investigate differences between reconstruction algorithms in quantitative perfusion values and time-attenuation curves in computed tomography perfusion (CTP) examinations of the upper abdomen.

Methods

Twenty-six CTP examinations were reconstructed with filtered back projection and an iterative reconstruction algorithm, advanced modeled iterative reconstruction (ADMIRE), with different levels of noise-reduction strength. Using the maximum-slope model, quantitative measurements were obtained: blood flow (mL/min/100 mL), blood volume (mL/100 mL), time to peak (s), arterial liver perfusion (mL/100 mL/min), portal venous liver perfusion (mL/100 mL/min), hepatic perfusion index (%), temporal maximum intensity projection (Hounsfield units (HU)) and temporal average HU. Time-attenuation curves for seven sites (left liver lobe, right liver lobe, hepatocellular carcinoma, spleen, gastric wall, pancreas, portal vein) were obtained. Mixed-model analysis was used for statistical evaluation. Image noise and the signal:noise ratio (SNR) were compared between four reconstructions, and statistical analysis of these reconstructions was made with a related-samples Friedman’s two-way analysis of variance by ranks test.

Results

There were no significant differences for quantitative measurements between the four reconstructions for all tissues. There were no significant differences between the AUC values of the time-attenuation curves between the four reconstructions for all tissues, including three automatic measurements (portal vein, aorta, spleen). There was a significant difference in image noise and SNR between the four reconstructions.

Conclusions

ADMIRE did not affect the quantitative measurements or time-attenuation curves of tissues in the upper abdomen. The image noise was lower, and the SNR higher, for iterative reconstructions with higher noise-reduction strengths.

A modified two-compartment model for measurement of renal function using dynamic contrast-enhanced computed tomography

Objectives

To validate and adapt a modified two-compartment model, originally developed for magnetic resonance imaging, for measuring human single-kidney glomerular filtration rate (GFR) and perfusion using dynamic contrast-enhanced computed tomography (DCE-CT).

Methods

This prospective study was approved by the institutional review board, and written informed consent was obtained from all patients. Thirty-eight patients with essential hypertension (EH, n = 13) or atherosclerotic renal artery stenosis (ARAS, n = 25) underwent renal DCE-CT for GFR and perfusion measurement using a modified two-compartment model. Iothalamate clearance was used to measure reference total GFR, which was apportioned into single-kidney GFR by renal blood flow. Renal perfusion was also calculated using a conventional deconvolution algorithm. Validation of GFR and perfusion and inter-observer reproducibility, were conducted by using the Pearson correlation and Bland-Altman analysis.

Results

Both the two-compartment model and iothalamate clearance detected in ARAS patients lower GFR in the stenotic compared to the contralateral and EH kidneys. GFRs measured by DCE-CT and iothalamate clearance showed a close match (r = 0.94, P<0.001, and mean difference 2.5±12.2mL/min). Inter-observer bias and variation in model-derived GFR (r = 0.97, P<0.001; mean difference, 0.3±7.7mL/min) were minimal. Renal perfusion by deconvolution agreed well with that by the compartment model when the blood transit delay from abdominal aorta to kidney was negligible.

Conclusion

The proposed two-compartment model faithfully depicts contrast dynamics using DCE-CT and may provide a reliable tool for measuring human single-kidney GFR and perfusion.

Weight-adapted ultra-low-dose pancreatic perfusion CT: radiation dose, image quality, and perfusion parameters

PURPOSE

We evaluate the reliability and feasibility of weight-adapted ultra-low-dose pancreatic perfusion CT.

METHODS

A total of 100 (47 men, 53 women) patients were enrolled prospectively and were assigned to five groups (A, B, C, D, and E) with different combination of tube voltage and tube current according to their body weight. Radiation dose parameters including volume CT dose index (CTDI) and dose-length product (DLP) were recorded. Image quality was evaluated both subjectively and objectively (noise, signal-to-noise ratio, contrast-to-noise ratio). Perfusion parameters including blood flow (BF), blood volume (BV), and permeability (PMB) were measured. The dose, image quality measurements, and perfusion parameters were compared between the five groups using one-way analysis of variance (ANOVA).

RESULTS

Radiation dose reached 8.7 mSv in patients under 50 kg and was 18.9 mSv in patients above 80 kg. The mean subjective image quality score was above 4.45 on a 5-point scale with good agreement between two radiologists. Groups A-D had equivalent performance on objective image quality (P > 0.05), while Group E performed even better (P < 0.05). No significant differences emerged in comparison with perfusion parameters (BF, BV, PMB) of normal pancreas parenchyma between the five groups.

CONCLUSION

Weight-adapted ultra-low-dose pancreatic perfusion CT can effectively reduce radiation dose without prejudice to image quality, and the perfusion parameters of normal parenchyma are accurate and reliable.

Is There a Direct Correlation Between Microvascular Wall Structure and k-Trans Values Obtained From Perfusion CT Measurements in Lymphomas?

RATIONALE AND OBJECTIVES

This study aimed to test the hypothesis that ultrastructural wall abnormalities of lymphoma vessels correlate with perfusion computed tomography (PCT) kinetics.

MATERIALS AND METHODS

Our local institutional review board approved this prospective study. Between February 2013 and June 2016, we included 23 consecutive subjects with newly diagnosed lymphoma, who were referred for computed tomography-guided biopsy (6 women, 17 men; mean age, 60.61 ± 12.43 years; range, 28-74 years) and additionally agreed to undergo PCT of the target lymphoma tissues. PCT was obtained for 40 seconds using 80 kV, 120 mAs, 64 × 0.6-mm collimation, 6.9-cm z-axis coverage, and 26 volume measurements. Mean and maximum k-trans (mL/100 mL/min), blood flow (BF; mL/100 mL/min) and blood volume (BV) were quantified using the deconvolution and the maximum slope + Patlak calculation models. Immunohistochemical staining was performed for microvessel density quantification (vessels/m²), and electron microscopy was used to determine the presence or absence of tight junctions, endothelial fenestration, basement membrane, and pericytes, and to measure extracellular matrix thickness.

RESULTS

Extracellular matrix thickness as well as the presence or absence of tight junctions, basal lamina, and pericytes did not correlate with computed tomography perfusion parameters. Endothelial fenestrations correlated significantly with mean BF_{deconvolution} (P = .047, r = 0.418) and additionally was significantly associated with higher mean BV_{deconvolution} (P < .005). Mean k-trans_Patlak correlated strongly with mean k-trans_{deconvolution} (r = 0.939, P = .001), and both correlated with mean BF_{deconvolution} (P = .001, r = 0.748), max BF_{deconvolution} (P = .028, r = 0.564), mean BV_{deconvolution} (P = .001, r = 0.752), and max BV_{deconvolution} (P = .001, r = 0.771). Microvessel density correlated with max k-trans_{deconvolution} (r = 0.564, P = .023). Vascular endothelial growth factor receptor-3 expression (receptor specific for lymphatics) correlated significantly with max k-trans_Patlak (P = .041, r = 0.686) and mean BF_{deconvolution} (P = .038, r = 0.695).

CONCLUSION

k-Trans values of PCT do not correlate with ultrastructural microvessel features, whereas endothelial fenestrations correlate with increased intra-tumoral BVs.

Correlation between acoustic radiation force impulse (ARFI)-based tissue elasticity measurements and perfusion parameters acquired by perfusion CT in cirrhotic livers: a proof of principle

PURPOSE

To investigate whether liver stiffness measured by acoustic radiation force impulse (ARFI) sonoelastography always correlates with the liver perfusion parameters quantified by perfusion CT in patients with known liver cirrhosis.

METHODS

Sonoelastography and perfusion CT were performed in 50 patients (mean age 65.5; range 45-87 years) with liver cirrhosis, who were classified according to Child-Pugh into class A (30/50, 60%), B (17/50, 34%), and C (3/50, 6%). For standardized ARFI measurements in the left liver lobe at a depth of 4 cm, a convex 6-MHz probe was used. CT examinations were performed using 80 kV, 100 mAs, and 50 ml of iodinated contrast agent injected at 5 ml/s. Using standardized region-of-interest measurements, we quantified arterial, portal venous, and total liver perfusion.

RESULTS

There was a significant linear correlation between tissue stiffness and arterial liver perfusion (p = 0.015), and also when limiting the analysis to patients with histology (p = 0.019). In addition, there was a positive correlation between the total blood supply (arterial + portal-venous liver perfusion) to the liver and tissue stiffness (p = 0.001; with histology, p = 0.027). Shear wave velocity increased with higher Child-Pugh stages (p = 0.013).

CONCLUSION

The degree of tissue stiffness in cirrhotic livers correlates expectedly-even if only moderately-with the magnitude of arterial liver perfusion and total liver perfusion. As such, liver elastography remains the leading imaging tool in assessing liver fibrosis.

Variability and Reproducibility of 3rd-generation dual-source dynamic volume perfusion CT Parameters in Comparison to MR-perfusion Parameters in Rectal Cancer

To compare in patients with untreated rectal cancer quantitative perfusion parameters calculated from 3^rd-generation dual-source dynamic volume perfusion CT (dVPCT) with 3-Tesla-MR-perfusion with regard to data variability and tumour differentiation. In MR-perfusion, plasma flow (PF), plasma volume (PV) and mean transit time (MTT) were assessed in two measurements (M1 and M2) by the same reader. In dVPCT, blood flow (BF), blood volume (BV), MTT and permeability (PERM) were assessed respectively. CT dose values were calculated. 20 patients (60 ± 13 years) were analysed. Intra-individual and intra-reader variability of duplicate MR-perfusion measurements was higher compared to duplicate dVPCT measurements. dVPCT-derived BF, BV and PERM could differentiate between tumour and normal rectal wall (significance level for M1 and M2, respectively, regarding BF: p < 0.0001*/0.0001*; BV: p < 0.0001*/0.0001*; MTT: p = 0.93/0.39; PERM: p < 0.0001*/0.0001*), with MR-perfusion this was true for PF and PV (p-values M1/M2 for PF: p = 0.04*/0.01*; PV: p = 0.002*/0.003*; MTT: p = 0.70/0.27*). Mean effective dose of CT-staging incl. dVPCT was 29 ± 6 mSv (20 ± 5 mSv for dVPCT alone). In conclusion, dVPCT has a lower data variability than MR-perfusion while both dVPCT and MR-perfusion could differentiate tumour tissue from normal rectal wall. With 3^rd-generation dual-source CT dVPCT could be included in a standard CT-staging without exceeding national dose reference values.

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.

Relationship between low tube voltage (70 kV) and the iodine delivery rate (IDR) in CT angiography: An experimental in-vivo study

Objective

Very short acquisition times and the use of low-kV protocols in CTA demand modifications in the contrast media (CM) injection regimen. The aim of this study was to optimize the use of CM delivery parameters in thoraco-abdominal CTA in a porcine model.

Materials and methods

Six pigs (55–68 kg) were examined with a dynamic CTA protocol (454 mm scan length, 2.5 s temporal resolution, 70 s total acquisition time). Four CM injection protocols were applied in a randomized order. 120 kV CTA protocol: (A) 300 mg iodine/kg bodyweight (bw), IDR = 1.5 g/s (flow = 5 mL/s), injection time (t_i) 12 s (60 kg bw). 70 kV CTA protocols: 150 mg iodine/kg bw: (B) IDR = 0.75 g/s (flow = 2.5 mL/s), t_i = 12 s (60 kg bw); (C) IDR = 1.5 g/s (flow = 5 mL/s), t_i = 12 s (60 kg bw); (D) IDR = 3.0 g/s (flow = 10 mL/s), t_i = 3 s (60 kg bw). The complete CM bolus shape was monitored by creating time attenuation curves (TAC) in different vascular territories. Based on the TAC, the time to peak (TTP) and the peak enhancement were determined. The diagnostic window (relative enhancement > 300 HU), was calculated and compared to visual inspection of the corresponding CTA data sets.

Results

The average relative arterial peak enhancements after baseline correction were 358.6 HU (A), 356.6 HU (B), 464.0 HU (C), and 477.6 HU (D). The TTP decreased with increasing IDR and decreasing t_i, protocols A and B did not differ significantly (systemic arteries, p = 0.843; pulmonary arteries, p = 0.183). The delay time for bolus tracking (trigger level 100 HU; target enhancement 300 HU) for single-phase CTA was comparable for protocol A and B (3.9, 4.3 s) and C and D (2.4, 2.0 s). The scan window time frame was comparable for the different protocols by visual inspection of the different CTA data sets and by analyzing the TAC.

Conclusions

All protocols provided sufficient arterial enhancement. The use of a 70 kV CTA protocol is recommended because of a 50% reduction of total CM volume and a 50% reduced flow rate while maintaining the bolus profile. In contrast to pulmonary arterial enhancement, the systemic arterial enhancement improved only slightly increasing the IDR from 1.5 g/s to 3 g/s because of bolus dispersion of the very short bolus (3s) in the lungs.

Comparison between acoustic radiation force impulse quantification data and perfusion-CT parameters in hepatocellular carcinoma

OBJECTIVE

To find out, if ultrasound elastography of hepatocellular carcinoma (HCC) can predict patterns of tumor perfusion in volume perfusion computed tomography (VPCT).

MATERIAL AND METHODS

25 consecutive patients (mean age, 68.9; range, 51-85 years) with liver cirrhosis suspected of HCC underwent VPCT and acoustic radiation force impulse (ARFI) elastography the same day. Quantitative elasticity values were registered, while blood flow (BF), blood volume (BV) and hepatic perfusion index (HPI) of the HCC lesions were calculated. Additionally, we identified histologic WHO grading, lesion size and localization. The Siemens Acuson S 3000 HELX-System with Virtual Touch™-Software and Siemens Somatom Definition Flash with Syngo^® software were used.

RESULTS

A total of 43 HCC lesions were assessed. Mean shear wave velocity was 2.6m/s (range, 1.1-4.3m/s). There was no significant linear correlation between the elasticity values and BF (p=0.751), BV (p=0.426) and HPI (p=0.437). However, elasticity values were higher, the larger the tumor was (p=0.008). Shear wave velocity declined with increasing distance of the HCC to the skin surface (p=0.028) and depending on liver segment. In addition, elasticity values were higher in less differentiated HCCs. This trend was not statistically significant (p=0.842).

CONCLUSION

Tissue elasticity in HCC does not correlate with the degree of tumor vascularization, but calculated values are influenced both by the tumor size and localization inside the liver.

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.

Spectral optimization of iodine-enhanced CT: Quantifying the effect of tube voltage on image quality and radiation exposure determined at an anthropomorphic phantom

PURPOSE

To provide an experimental basis for spectral optimization of iodine-enhanced CT by a quantitative analysis of image quality and radiation dose characteristics consistently measured for a large variety of scan settings at an anthropomorphic phantom.

METHODS

CT imaging and thermoluminescent dosimetry were performed at an anthropomorphic whole-body phantom with iodine inserts for different tube voltages (U, 70-140kV) and current-time products (Q, 60-300mAs). For all U-Q combinations, the iodine contrast (C), the noise level (N) and, from these, the contrast-to-noise ratio (CNR) of reconstructed CT images were determined and parameterized as a function of U, Q or the measured absorbed dose (D). Finally, two characteristic curves were derived that give the relative increase of CNR at constant D and the relative decrease of D at constant CNR when lowering U.

RESULTS

Lowering U affects the measured CNR only slightly but markedly reduces D. For example, reducing U from 120kV to 70kV increases the CNR at constant D by a factor of nearly 1.8 or, alternatively, reduces D at constant CNR by a factor of nearly 5.

CONCLUSION

Spectral optimization by lowering U is an effective approach to attain the necessary CNR for a specific diagnostic task at hand while at the same time reducing radiation exposure as far as practically achievable. The characteristic curves derived in this study from extensive measurements at a reference 'person' can support CT users in an easy-to-use manner to select an appropriate voltage for various clinical scenarios.

Comparison of organ-specific-radiation dose levels between 70 kVp perfusion CT and standard tri-phasic liver CT in patients with hepatocellular carcinoma using a Monte-Carlo-Simulation-based analysis platform

Purpose

The aim of this study was to systematically compare organ-specific-radiation dose levels between a radiation dose optimized perfusion CT (dVPCT) protocol of the liver and a tri-phasic standard CT protocol of the liver using a Monte-Carlo-Simulation-based analysis platform.

Methods and materials

The complete CT data of 52 patients (41 males; mean age 65 ± 12) with suspected HCC that underwent dVPCT examinations on a 3rd generation dual-source CT (Somatom Force, Siemens) with a dose optimized tube voltage of 70 kVp or 80 kVp were exported to an analysis platform (Radimetrics, Bayer). The dVPCT studies were matched with a reference group of 50 patients (35 males; mean age 65 ± 14) that underwent standard tri-phasic CT (sCT) examinations of the liver with 130 kVp using the calculated water-equivalent-diameter of the patients. The analysis platform was used for the calculation of the organ-specific effective dose (ED) as well as global radiation-dose parameters (ICRP103).

Results

The organ-specific ED of the dVPCT protocol was statistically significantly lower when compared to the sCT in 14 of 21, and noninferior in a total of 18 of 21 examined items (all p < 0.05). The EDs of the dVPCT examinations were especially in the dose sensitive organs such as the red marrow (17.3 mSv vs 24.6 mSv, p = < 0.0001) and the liver (33.3 mSv vs 46.9 mSv, p = 0.0003) lower when compared to the sCT.

Conclusion

Our results suggest that dVPCT performed at 70 or 80 kVp compares favorably to sCT performed with 130 kVp with regard to effective organ dose levels, especially in dose sensitive organs, while providing additional functional information which is of paramount importance in patients undergoing novel targeted therapies.

Multiparametric imaging of patient and tumour heterogeneity in non-small-cell lung cancer: quantification of tumour hypoxia, metabolism and perfusion

Purpose

Multiple imaging techniques are nowadays available for clinical in-vivo visualization of tumour biology. FDG PET/CT identifies increased tumour metabolism, hypoxia PET visualizes tumour oxygenation and dynamic contrast-enhanced (DCE) CT characterizes vasculature and morphology. We explored the relationships among these biological features in patients with non-small-cell lung cancer (NSCLC) at both the patient level and the tumour subvolume level.

Methods

A group of 14 NSCLC patients from two ongoing clinical trials (NCT01024829 and NCT01210378) were scanned using FDG PET/CT, HX4 PET/CT and DCE CT prior to chemoradiotherapy. Standardized uptake values (SUV) in the primary tumour were calculated for the FDG and hypoxia HX4 PET/CT scans. For hypoxia imaging, the hypoxic volume, fraction and tumour-to-blood ratio (TBR) were also defined. Blood flow and blood volume were obtained from DCE CT imaging. A tumour subvolume analysis was used to quantify the spatial overlap between subvolumes.

Results

At the patient level, negative correlations were observed between blood flow and the hypoxia parameters (TBR >1.2): hypoxic volume (−0.65, p = 0.014), hypoxic fraction (−0.60, p = 0.025) and TBR (−0.56, p = 0.042). At the tumour subvolume level, hypoxic and metabolically active subvolumes showed an overlap of 53 ± 36 %. Overlap between hypoxic sub-volumes and those with high blood flow and blood volume was smaller: 15 ± 17 % and 28 ± 28 %, respectively. Half of the patients showed a spatial mismatch (overlap <5 %) between increased blood flow and hypoxia.

Conclusion

The biological imaging features defined in NSCLC tumours showed large interpatient and intratumour variability. There was overlap between hypoxic and metabolically active subvolumes in the majority of tumours, there was spatial mismatch between regions with high blood flow and those with increased hypoxia.

Electronic supplementary material

The online version of this article (doi:10.1007/s00259-015-3169-4) contains supplementary material, which is available to authorized users.