Quantitative contrast-enhanced computed tomography: is there a need for system calibration?

A Metric for Quantification of Iodine Contrast Enhancement (Q-ICE) in Computed Tomography

BACKGROUND

Poor contrast enhancement is related to issues with examination execution, contrast prescription, computed tomography (CT) protocols, and patient conditions. Currently, our community has no metric to monitor true enhancement on routine single-phase examinations because this requires knowledge of both pre- and postcontrast CT number.

PURPOSE

We propose an automatable solution to quantifying contrast enhancement without requiring a dedicated noncontrast series.

METHODS

The difference in CT number between a target region in an enhanced and unenhanced image defines the metric "quantification of iodine contrast enhancement" (Q-ICE). Quantification of iodine contrast enhancement uses the noncontrast bolus tracking baseline image from routine abdominal examinations, which mitigates the need for a dedicated noncontrast series. We applied this method retrospectively to 312 patient livers from 2 sites between 2017 and 2020. Each site used a weight-based contrast injection protocol for weights 60 to 113 kg and a constant volume less than 60 kg and greater than 113 kg. Hypothesis testing was performed to compare Q-ICE between sites and detect Q-ICE dependence on weight and kilovoltage (kV).

RESULTS

Mean Q-ICE differed between sites (P = 0.004) by 4.96 Hounsfield unit with 95% confidence interval (1.63-8.28), albeit this difference was roughly 2 times smaller than the SD in Q-ICE across patients at a single site. For patients between 60 and 113 kg, we did not observe evidence of Q-ICE varying with patient weight (P = 0.920 and 0.064 for 120 and 140 kV, respectively). The Q-ICE did vary with patient weight for patients less than 60 kg (P = 0.003) and greater than 113 kg (P = 0.04). We observed a roughly 10 Hounsfield unit reduction in Q-ICE liver for patients scanned with 140 versus 120 kV. We observed several underenhancing examinations with an arterial phase appearance motivating our CT protocol optimization team to consider increasing the delay for slowly enhancing patients.

CONCLUSIONS

A quality metric for quantifying CT contrast enhancement was developed and suggested tangible opportunities for quality improvement and potential financial savings.

Contrast Bolus Interference in a Multimodal CT Stroke Protocol

BACKGROUND AND PURPOSE

Whether CTP is performed before or after CTA varies within multimodal CT stroke protocols. CTA after CTP might show venous filling, and CTP metrics might be disturbed by prior CTA. Therefore, we compared CTP metrics conducted before and after CTA in a large cohort of patients with stroke and analyzed interferences of the CTA bolus with the CTP measurement.

MATERIALS AND METHODS

We analyzed 1980 patients (368 patients with CTP performed before CTA [group A] versus 1612 patients with CTP performed after [group B]) in a retrospective study. Mean curves, histograms of CTP baseline Hounsfield units, CBF, CBV, time-to-maximum, hypoperfusion, and core volumes were calculated using the software VEOcore. CTA and CTP interferences were analyzed, and a detection and correction method was proposed.

RESULTS

Mean CTP baseline values were significantly different in both groups (41 versus 45 HU within the groups A and B, respectively). However, perfusion metrics, hypoperfusion, and core volumes yielded no significant differences. In 49 patients, the descending flank of the CTA bolus interfered with the baseline of the CTP measurement, leading to erroneously low CBV values. These errors vanished when a correction method was applied.

CONCLUSIONS

CTP can be reliably performed after CTA without a relevant net effect on perfusion metrics. However, when measuring CTP after CTA, either a short pause on the order of 30 seconds should be observed or an appropriate correction method should be applied. It may help to avoid excluding patients from mechanical thrombectomy by overestimating infarct cores.

Quantification accuracy for dynamic contrast enhanced (DCE) CT imaging: phantom and quality assurance framework

PURPOSE

Standardization and protocol optimization is essential for quantification of Dynamic Contrast Enhanced CT as an imaging biomarker. Currently, no commercially available quality assurance (QA) phantoms can provide for testing a complete set of imaging parameters pertaining to routine quality control for contrast-enhanced (CE) CT, as well as spatiotemporal accuracy. The purpose of this work was, therefore: (a) developing a solid calibration phantom for routine CE CT quality assurance; (b) investigating the sensitivity of CECT to organ motion, and (c) characterizing a volumetric CT scanner for CECT.

METHODS

CECT calibration phantom consisting of an acrylic uniform cylinder containing multiple capsules of varying diameters and orientations was designed and built. The capsules contain different solid density materials mimicking iodine contrast enhancement. Sensitivity and accuracy of CECT measurements on all capsules was performed using a 320-slice CT scanner for a range of scan parameters both with and without phantom motion along the transaxial axis of the scanner.

RESULTS

Routine commissioning tests such as uniformity, spatial resolution and image noise were successfully determined using the CECT phantom. Partial volume effect and motion blurring both contribute to a general decrease in contrast enhancement and this was further dependent on capsule orientation (least pronounced for the transaxial orientation). Scanning with a rotation time of less than 0.5 s, the effect of blurring is less than 3% for all orientations and phantom speeds.

CONCLUSION

A new robust contrast calibration phantom was developed and used to evaluate the performance of a 320-slice volumetric CT scanner for DCE-CT.

Comparison of arterial input functions measured from ultra-fast dynamic contrast enhanced MRI and dynamic contrast enhanced computed tomography in prostate cancer patients

The purpose of this study was to evaluate the accuracy of arterial input functions (AIFs) measured from dynamic contrast enhanced (DCE) MRI following a low dose of contrast media injection. The AIFs measured from DCE computed tomography (CT) were used as 'gold standard'. A total of twenty patients received CT and MRI scans on the same day. Patients received 120 ml Iohexol in DCE-CT and a low dose of (0.015 mM kg^-1) of gadobenate dimeglumine in DCE-MRI. The AIFs were measured in the iliac artery and normalized to the CT and MRI contrast agent doses. To correct for different temporal resolution and sampling periods of CT and MRI, an empirical mathematical model (EMM) was used to fit the AIFs first. Then numerical AIFs (AIF_CT and AIF_MRI) were calculated based on fitting parameters. The AIF_MRI was convolved with a 'contrast agent injection' function ([Formula: see text]) to correct for the difference between MRI and CT contrast agent injection times (~1.5 s versus 30 s). The results show that the EMMs accurately fitted AIFs measured from CT and MRI. There was no significant difference (p  >  0.05) between the maximum peak amplitude of AIFs from CT (22.1  ±  4.1 mM/dose) and MRI after convolution (22.3  ±  5.2 mM/dose). The shapes of the AIF_CT and [Formula: see text] were very similar. Our results demonstrated that AIFs can be accurately measured by MRI following low dose contrast agent injection.

Development and validation of a segmentation-free polyenergetic algorithm for dynamic perfusion computed tomography

Dynamic perfusion imaging can provide the morphologic details of the scanned organs as well as the dynamic information of blood perfusion. However, due to the polyenergetic property of the x-ray spectra, beam hardening effect results in undesirable artifacts and inaccurate CT values. To address this problem, this study proposes a segmentation-free polyenergetic dynamic perfusion imaging algorithm (pDP) to provide superior perfusion imaging. Dynamic perfusion usually is composed of two phases, i.e., a precontrast phase and a postcontrast phase. In the precontrast phase, the attenuation properties of diverse base materials (e.g., in a thorax perfusion exam, base materials can include lung, fat, breast, soft tissue, bone, and metal implants) can be incorporated to reconstruct artifact-free precontrast images. If patient motions are negligible or can be corrected by registration, the precontrast images can then be employed as a priori information to derive linearized iodine projections from the postcontrast images. With the linearized iodine projections, iodine perfusion maps can be reconstructed directly without the influence of various influential factors, such as iodine location, patient size, x-ray spectrum, and background tissue type. A series of simulations were conducted on a dynamic iodine calibration phantom and a dynamic anthropomorphic thorax phantom to validate the proposed algorithm. The simulations with the dynamic iodine calibration phantom showed that the proposed algorithm could effectively eliminate the beam hardening effect and enable quantitative iodine map reconstruction across various influential factors. The error range of the iodine concentration factors ([Formula: see text]) was reduced from [Formula: see text] for filtered back-projection (FBP) to [Formula: see text] for pDP. The quantitative results of the simulations with the dynamic anthropomorphic thorax phantom indicated that the maximum error of iodine concentrations can be reduced from [Formula: see text] for FBP to less than [Formula: see text] for pDP, which suggested that the proposed algorithm could not only effectively eliminate beam hardening artifacts but also significantly reduce the influence of the metal artifacts and accurately reconstruct the iodine map regardless of the influential factors. A segmentation-free polyenergetic dynamic perfusion imaging algorithm was proposed and validated via simulations. This method can accurately reconstruct artifact-free iodine maps for quantitative analyses.

Evaluation of Tumor-associated Stroma and Its Relationship with Tumor Hypoxia Using Dynamic Contrast-enhanced CT and (18)F Misonidazole PET in Murine Tumor Models

PURPOSE

To determine the relationship between the fractional interstitial volume (Fis), as calculated at dynamic contrast material-enhanced (DCE) computed tomography (CT), and tumor-associated stroma and to analyze its spatial relationship with tumor hypoxia in several xenograft tumor models.

MATERIALS AND METHODS

All animal experiments were approved by the animal research committee. Mice with three different xenograft tumors (U251, CFPAC-1, and BxPC-3; n = 6, n = 8, and n = 6, respectively) underwent DCE CT then hypoxia imaging with fluorine 18 ((18)F) fluoromisonidazole (FMISO) positron emission tomography (PET) within 24 hours. Immunohistochemical analysis was performed in harvested tumors to detect hypoxia markers and to quantify microvascular and stromal density. Two DCE CT parameters (amount of interstitial space associated with the amount of stroma [Fis] and flow velocity [Fv]) were identified and quantitatively validated by using immunohistochemistry. FMISO uptake within the tumor was also assessed in relation to DCE CT parameters. Imaging and immunohistochemical parameters were assessed by using the Kruskal-Wallis test, Wilcoxon rank-sum test with Bonferroni correction, and Pearson correlation coefficient.

RESULTS

Almost no α-smooth muscle actin-positive cells were found in the U251 xenograft, while abundant stroma was found in the entire BxPC-3 xenograft and in the periphery of the CFPAC-1 xenograft. Quantitative analysis showed a significant correlation (R = 0.83, P < .0001) between Fis and stromal density. FMISO uptake had a negative correlation with Fis (R = -0.58, P < .0001) and Fv (R = -0.53, P < .0001).

CONCLUSION

DCE CT can be used to quantify parameters associated with tumor-associated stroma. Tumor hypoxia was Complementarily localized in tumor-associated stroma in these models.

Quality control within the multicentre perfusion CT study of primary colorectal cancer (PROSPeCT): results of an iodine density phantom study

OBJECTIVES

To assess the cross-centre consistency of iodine enhancement, contrast-to-noise ratio and radiation dose in a multicentre perfusion CT trial of colorectal cancer.

MATERIALS AND METHODS

A cylindrical water phantom containing different iodine inserts was examined on seven CT models in 13 hospitals. The relationship between CT number (Hounsfield units, HU) and iodine concentration (milligrams per millilitre) was established and contrast-to-noise ratios (CNRs) calculated. Radiation doses (CTDIvol, DLP) were compared across all sites.

RESULTS

There was a linear relationship between CT number and iodine density. Iodine enhancement varied by a factor of at most 1.10, and image noise by at most 1.5 across the study sites. At an iodine concentration of 1 mg ml(-1) and 100 kV, CNRs ranged from 3.6 to 4.8 in the 220-mm phantom and from 1.4 to 1.9 in the 300-mm phantom. Doses varied by a factor of at most 2.4, but remained within study dose constraints. Iterative reconstruction algorithms did not alter iodine enhancement but resulted in reduced image noise by a factor of at most 2.2, allowing a potential dose decrease of at most 80% compared to filtered back projection (FBP).

CONCLUSIONS

Quality control of CT performance across centres indicates that CNR values remain relatively consistent across all sites, giving acceptable image quality within the agreed dose constraints.

KEY POINTS

Quality control is essential in a multicentre setting to enable CT quantification. CNRs in a body-sized phantom had the recommended value of at least 1.5. CTDIs and DLPs varied by factors of 1.8 and 2.4 respectively.

Voxelwise comparison of perfusion parameters estimated using dynamic contrast enhanced (DCE) computed tomography and DCE-magnetic resonance imaging in locally advanced cervical cancer

PURPOSE

Dynamic contrast enhanced (DCE) imaging has gained interest as an imaging modality for assessment of tumor characteristics and response to cancer treatment. However, for DCE-magnetic resonance imaging (MRI) tissue contrast enhancement may vary depending on imaging sequence and temporal resolution. The aim of this study is to compare DCE-MRI to DCE-computed tomography (DCE-CT) as the gold standard.

MATERIAL AND METHODS

Thirteen patients with advanced cervical cancer were scanned once prior to chemo-radiation and during chemo-radiation with DCE-CT and -MRI in immediate succession. A total of 22 paired DCE-CT and -MRI scans were acquired for comparison. Kinetic modeling using the extended Tofts model was applied to both image series. Furthermore the similarity of the spatial distribution was evaluated using a Γ analysis. The correlation between the two imaging techniques was evaluated using Pearson's correlation and the parameter means were compared using a Student's t-test (p < 0.05).

RESULTS

A significant positive correlation between DCE-CT and -MRI was found for all kinetic parameters. The results showing the best correlation with the DCE-CT-derived parameters were obtained using a population-based input function for MRI. The median Pearson's correlations were: volume transfer constant K(trans) (r = 0.9), flux rate constant kep (r = 0.77), extracellular volume fraction ve (r = 0.58) and blood plasma volume fraction vp (r = 0.83). All quantitative parameters were found to be significantly different as estimated by DCE-CT and -MRI. The Γ analysis in normalized maps revealed that 45% of the voxels failed to find a voxel with the corresponding value allowing for an uncertainty of 3 mm in position and 3% in value (Γ3,3). By reducing the criteria, the Γ-failure rates were: Γ3,5 (37% failure), Γ3,10 (26% failure) and at Γ3,15 (19% failure).

CONCLUSION

Good to excellent correlations but significant bias was found between DCE-CT and -MRI. Both the Pearson's correlation and the Γ analysis proved that the spatial information was similar when analyzing the two sets of DCE data using the extended Tofts model. Improvement of input function sampling is needed to improve kinetic quantification using DCE-MRI.

Quantitative analysis of microscopic X-ray computed tomography imaging: Japanese quail embryonic soft tissues with iodine staining

Rapid three-dimensional imaging of embryos to better understand the complex process of morphogenesis has been challenging. Recently introduced iodine staining protocols (I2 KI and alcoholic iodine stains) combined with microscopic X-ray computed tomography allows visualization of soft tissues in diverse small organisms and tissue specimens. I2 KI protocols have been developed specifically for small animals, with a limited number of quantitative studies of soft tissue contrasts. To take full advantage of the low X-ray attenuation of ethanol and retain bound iodine while dehydrating the specimen in ethanol, we developed an ethanol I2 KI protocol. We present comparative microscopic X-ray computed tomography analyses of ethanol I2 KI and I2 KI staining protocols to assess the performance of this new protocol to visualize soft tissue anatomy in late stage Japanese quail embryos using quantitative measurements of soft tissue contrasts and sample shrinkage. Both protocols had only 5% shrinkage compared with the original harvested specimen, supporting the use of whole mounts to minimize tissue shrinkage effects. Discrimination within and among the selected organs with each staining protocol and microscopic X-ray computed tomography imaging were comparable to those of a gray scale histological section. Tissue discrimination was assessed using calibrated computed tomography values and a new discrimination index to quantify the degree of computed tomography value overlaps between selected soft tissue regions. Tissue contrasts were dependent on the depth of the tissue within the embryos before the embryos were saturated with each stain solution, and optimal stain saturations for the entire embryo were achieved at 14 and 28 days staining for I2 KI and ethanol I2 KI, respectively. Ethanol I2 KI provided superior soft tissue contrasts by reducing overstaining of fluid-filled spaces and differentially modulating staining of some tissues, such as bronchial and esophageal walls and spinal cord. Delineating the selected soft tissues using optimal threshold ranges derived from the quantitative analyses of the contrast enhancement in optimally stained embryos is possible. The protocols presented here are expected to be applicable to other organisms with modifications to staining time and contribute toward rapid and more efficient segmentation of soft tissues for three-dimensional visualization.

Towards a nanoscale mammographic contrast agent: development of a modular pre-clinical dual optical/x-ray agent

Contrast-enhanced digital mammography (CEDM) can provide improved breast cancer detection and characterization compared to conventional mammography by imaging the effects of tumour angiogenesis. Current small-molecule contrast agents used for CEDM are limited by a short plasma half-life and rapid extravasation into tissue interstitial space. To address these limitations, nanoscale agents that can remain intravascular except at sites of tumour angiogenesis can be used. For CEDM, this agent must be both biocompatible and strongly attenuate mammographic energy x-rays. Nanoscale perfluorooctylbromide (PFOB) droplets have good x-ray attenuation and have been used in patients for other applications. However, the macroscopic scale of x-ray imaging (50-100 µm) is inadequate for direct verification that PFOB droplets localize at sites of breast tumour angiogenesis. For efficient pre-clinical optimization for CEDM, we integrated an optical marker into PFOB droplets for microscopic assessment (≪50 µm). To develop PFOB droplets as a new nanoscale mammographic contrast agent, PFOB droplets were labelled with fluorescent quantum dots (QDs). The droplets had mean diameters of 160 nm, fluoresced at 635 nm and attenuated x-ray spectra at 30.5 keV mean energy with a relative attenuation of 5.6 ± 0.3 Hounsfield units (HU) mg(-1) mL(-1) QD-PFOB. With the agent loaded into tissue phantoms, good correlation between x-ray attenuation and optical fluorescence was found (R(2) = 0.96), confirming co-localization of the QDs with PFOB for quantitative assessment using x-ray or optical methods. Furthermore, the QDs can be removed from the PFOB agent without affecting its x-ray attenuation or structural properties for expedited translation of optimized PFOB droplet formulations into patients.

Dynamic contrast-enhanced imaging techniques: CT and MRI

Over the last few decades there has been considerable research into quantifying the cerebral microvasculature with imaging, for use in studies of the human brain and various pathologies including cerebral tumours. This review highlights key issues in dynamic contrast-enhanced CT, dynamic contrast-enhanced MRI and arterial spin labelling, the various applications of which are considered elsewhere in this special issue of the British Journal of Radiology.

Correlation between dynamic CT findings and pathological prognostic factors of small lung adenocarcinoma

PURPOSE

To compare pathological prognostic factors of small lung adenocarcinomas with findings of contrast-enhanced dynamic computed tomography (CT) scans.

MATERIALS AND METHODS

We evaluated 108 patients with lung adenocarcinomas ≤ 30 mm in diameter who underwent dynamic CT scans (80-96 ml of contrast material, 2.5-3 ml/s injection) and tumor resections. Attenuation values of both the early phase (20-36 s after injection) and delayed phase (91-95 s) of enhanced CT minus baseline plain CT attenuation were defined as ΔEarly and ΔDelay. The early enhancement ratio was defined as ΔEarly/ΔDelay×100 (%). We statistically compared the early enhancement ratios between the presence and absence of each pathological finding (lymph node metastasis, lymphatic permeation, vascular invasion, and pleural involvement). Patients were divided into 2 groups based on early enhancement ratios: ratio ≥50% (n = 41) and ratio <50% (n = 67) and we statistically compared these 2 groups.

RESULTS

The early enhancement ratios in the group with lymph node metastasis, lymphatic permeation, and vascular invasion were significantly lower than in the group without these findings (24.9% vs 48.6%; P < 0.001, 30.0% vs 47.5%; P = 0.002, and 26.5% vs 47.0%; P = 0.002, respectively). Lymph node metastasis, lymphatic permeation, and vascular invasion were significantly more frequent in tumors with a ratio <50% than in tumors with ratio ≥50% (P < 0.001, P = 0.008, and P = 0.005, respectively).

CONCLUSIONS

There was a significant correlation between the early enhancement ratio of enhanced dynamic CT and the pathological prognostic factors in small lung adenocarcinomas.

Current status and guidelines for the assessment of tumour vascular support with dynamic contrast-enhanced computed tomography

Dynamic contrast-enhanced computed tomography (DCE-CT) assesses the vascular support of tumours through analysis of temporal changes in attenuation in blood vessels and tissues during a rapid series of images acquired with intravenous administration of iodinated contrast material. Commercial software for DCE-CT analysis allows pixel-by-pixel calculation of a range of validated physiological parameters and depiction as parametric maps. Clinical studies support the use of DCE-CT parameters as surrogates for physiological and molecular processes underlying tumour angiogenesis. DCE-CT has been used to provide biomarkers of drug action in early phase trials for the treatment of a range of cancers. DCE-CT can be appended to current imaging assessments of tumour response with the benefits of wide availability and low cost. This paper sets out guidelines for the use of DCE-CT in assessing tumour vascular support that were developed using a Delphi process. Recommendations encompass CT system requirements and quality assurance, radiation dosimetry, patient preparation, administration of contrast material, CT acquisition parameters, terminology and units, data processing and reporting. DCE-CT has reached technical maturity for use in therapeutic trials in oncology. The development of these consensus guidelines may promote broader application of DCE-CT for the evaluation of tumour vascularity. Key Points • DCE-CT can robustly assess tumour vascular support • DCE-CT has reached technical maturity for use in therapeutic trials in oncology • This paper presents consensus guidelines for using DCE-CT in assessing tumour vascularity.

Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details

Deconvolution-based analysis of CT and MR brain perfusion data is widely used in clinical practice and it is still a topic of ongoing research activities. In this paper, we present a comprehensive derivation and explanation of the underlying physiological model for intravascular tracer systems. We also discuss practical details that are needed to properly implement algorithms for perfusion analysis. Our description of the practical computer implementation is focused on the most frequently employed algebraic deconvolution methods based on the singular value decomposition. In particular, we further discuss the need for regularization in order to obtain physiologically reasonable results. We include an overview of relevant preprocessing steps and provide numerous references to the literature. We cover both CT and MR brain perfusion imaging in this paper because they share many common aspects. The combination of both the theoretical as well as the practical aspects of perfusion analysis explicitly emphasizes the simplifications to the underlying physiological model that are necessary in order to apply it to measured data acquired with current CT and MR scanners.

Neoadjuvant treatment of colorectal liver metastases is associated with altered contrast enhancement on computed tomography

Neoadjuvant systemic therapy may induce steatosis or sinusoid obstruction syndrome in the liver. The aim of this study was to investigate the influence of systemic therapy with irinotecan, oxaliplatin and cetuximab on conspicuity of liver metastases on computed tomography (CT). CT scans of 48 patients with initial unresectable colorectal liver metastases which were treated in a Europe-wide, opened, randomized phase II trial receiving oxaliplatin or irinotecan combined with folinic acid and cetuximab were analysed. The density of the metastases and the liver parenchyma before and after systemic therapy were analysed by region-of-interest technique and the tumour-to-liver difference (dHU TLD). The mean density of liver parenchyma and liver metastases did not vary significantly before and after neoadjuvant therapy on plain (56.3 ± 8.1 HU, 54.8 ± 13.5 HU) and arterial enhanced CT (76.0 ± 15.7 HU, 70.5 ± 20.4 HU). There was a significant reduction (105.6 ± 17.3 HU, 93.3 ± 18.2 HU) in the density of liver parenchyma on portal venous scans after systemic therapy (p < 0.0001) and a reduction of dHU TLD, consecutively. In patients with colorectal liver metastases, neoadjuvant chemotherapy may have a toxic impact on liver parenchyma resulting in reduced tumour-to-liver contrast in contrast-enhanced CT. This may lead to underestimation of real lesion size.

Translational imaging endpoints to predict treatment response to novel targeted anticancer agents

Response Evaluation Criteria in Solid Tumors (RECIST) and World Health Organization (WHO) Criteria have been traditionally used for the evaluation of therapeutic response to chemotherapeutic treatment regimens. They determine anatomic criteria for patients response to anti-cancer therapy based on morphological measurements of each target lesion. While this assessment is justified for cytotoxic (chemotherapeutic) drugs, it is now recognized that morphological imaging protocols are poorly suited to the evaluation of the efficacy of novel signal transduction inhibitors (STIs) which exhibit cytostatic rather than cytotoxic properties. New imaging technologies are now designed to evaluate, in a functional manner, modifications in tumor metabolic activity, cellularity, and vascularization before a reduction in tumor volume can be detected. Introduction of physiological imaging end-points, derived from dynamic contrast-enhanced (DCE) imaging protocols--including magnetic resonance imaging (MRI), computed tomography (CT) and ultrasound (US)--allow for early assessment of disruption in tumor perfusion and permeability for targeted anti-angiogenic agents. Diffusion-weighted MRI (DWI) provides another physiological imaging end-point since tumor necrosis and cellularity are seen early in response to anti-angiogenic treatment. Changes in glucose and phospholipid turnover, based on metabolic MRI and positron emission tomography (PET), provide reliable markers for therapeutic response to novel receptor-targeting agents. Finally, novel molecular imaging techniques of protein and gene expression have been developed in animal models followed by a successful human application for gene therapy-based protocols.

Dynamic contrast-enhanced texture analysis of the liver: initial assessment in colorectal cancer

PURPOSE

To undertake an initial assessment of the potential utility of dynamic contrast-enhanced texture analysis (DCE-TA) of the liver in patients with colorectal cancer.

MATERIALS AND METHODS

TA comprised measurement of mean gray-level intensity, entropy, and uniformity with and without selective-scale filtration using a band-pass filter to highlight different spatial frequencies reflecting fine, medium, and coarse textures. An initial phantom study assessed the sensitivity of each texture qualifier to computed tomography (CT) acquisition parameters. Texture was analyzed in DCE-CT series from 27 colorectal cancer patients having apparently normal hepatic morphology (node-negative: n = 8, node-positive: n = 19). Averaged changes in hepatic texture induced by contrast material were assessed qualitatively and quantitatively by using kinetic modeling to calculate hepatic perfusion indices following fine, medium, and coarse image filtration.

RESULTS

All texture qualifiers were less sensitive to changes in CT acquisition parameters than measurement of CT attenuation. Temporal changes in hepatic texture were qualitatively different from changes in enhancement. Statistically significant differences between node-negative and node-positive patients were observed for at least 1 time period for measurements of hepatic enhancement and for all texture parameters. The differences were most statistically significant and occurred over the greatest number of time periods for fine texture quantified as mean gray-level intensity (5 time periods, minimum P value: 0.006) followed by fine texture quantified as entropy (4 time points, minimum P value: 0.006). There was no difference in hepatic perfusion indices for the 2 groups.

CONCLUSIONS

DCE-TA is a potentially useful adjunct to DCE-CT warranting further investigation.

Whole tumour quantitative measurement of first-pass perfusion of oesophageal squamous cell carcinoma using 64-row multidetector computed tomography: correlation with microvessel density

PURPOSE

To assess correlations between whole tumour first-pass perfusion parameters obtained with 64-row multidetector computed tomography (MDCT), and microvessel density (MVD) in oesophageal squamous cell carcinoma.

MATERIALS AND METHODS

Thirty-one consecutive patients with surgically confirmed oesophageal squamous cell carcinomas were enrolled into our study. All the patients underwent whole tumour first-pass perfusion scan with 64-row MDCT. Perfusion parameters, including perfusion (PF), peak enhanced density (PED), blood volume (BV), and time to peak (TTP) were measured using Philips perfusion software. Postoperative tumour specimens were assessed for MVD. Pearson correlation coefficient tests were performed to determine correlations between each perfusion parameter and MVD.

RESULTS

Mean values for PF, PED, BV and TTP of the whole tumour were 28.85 ± 20.29 ml/min/ml, 23.16 ± 8.09 HU, 12.13 ± 5.21 ml/100g, and 35.05 ± 13.85 s, respectively. Mean MVD in whole tumour at magnification (×200) was 15.75 ± 4.34 microvessel/tumour sample (vessels/0.723 mm(2)). PED and BV were correlated with MVD (r=0.651 and r=0.977, respectively, all p<0.05). However, PF and TTP were not correlated with MVD (r=0.070 and r=0.100, respectively, all p>0.05).

CONCLUSION

The BV value of first-pass perfusion CT could reflect MVD in oesophageal squamous cell carcinoma, and can be an indicator for evaluating the tumour angiogenesis.

Advances in imaging diagnosis of pancreatic cancer

Early diagnosis of pancreatic carcinoma is very important for effective management of the disease. The imaging techniques traditionally used for diagnosis of pancreatic carcinoma include computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound imaging. In recent years, some new imaging techniques, such as Positron emission tomography (PET)-CT fusion and magnetic resonance spectroscopy (MRS), have been developed. These new imaging techniques play a crucial role in the early diagnosis of pancreatic carcinoma.

Toxicity of MRI and CT contrast agents

Anatomical and physiological imaging using CT and MRI are playing a critical role in patients' diagnosis, disease characterization and treatment planning. CT- and MRI-based protocols increasingly require an injection of iodinated CT and gadolinium (Gd)-based MRI contrast media. Although routinely used in clinical practice, iodinated and to a less extent Gd-based contrast media possess side effects: life-threatening contrast-induced nephropathy (CIN) is associated with CT and nephrogenic systemic fibrosis (NSF) with MRI contrast agents. CIN is defined as an acute decline in renal functions (serum creatinine increase > 0.5 mg/dl) after administration of iodinated contrast media. Patients with moderate-to-severe chronic kidney disease are considered the highest risk group for development of CIN. CIN is more common with ionic high-osmolar contrast CT media. NSF is a rare condition characterized by the formation of connective tissue in the skin and systemically in the lung, liver, heart and kidney. Patients with end stage kidney disease, acute kidney injury and stage 4-5 chronic kidney disease are at a high risk for NSF. The nonionic linear Gd-chelates are associated with the highest risk of NSF. This review summarizes the incidence, symptoms, safety profile of various CT and MRI contrast agents based on their physiochemical properties.

Enhancement patterns of pancreatic adenocarcinoma on conventional dynamic multi-detector row CT: correlation with angiogenesis and fibrosis

AIM

To evaluate retrospectively the correlation between enhancement patterns on dynamic computed tomography (CT) and angiogenesis and fibrosis in pancreatic adenocarcinoma.

METHODS

Twenty-three patients with pancreatic adenocarcinoma underwent dynamic CT and tumor resection. In addition to the absolute and relative enhanced value that was calculated by subtracting the attenuation value on pre-contrast from those on contrast-enhanced CT in each phase, we defined one parameter, "tumor-aorta enhancement ratio", which was calculated by dividing enhancement of pancreatic cancer by enhancement of abdominal aorta in each phase. These enhancement patterns were correlated with the level of vascular endothelial growth factor (VEGF), microvessel density (MVD), and extent of fibrosis.

RESULTS

The absolute enhanced value in the arterial phase correlated with the level of VEGF and MVD (P = 0.047, P = 0.001). The relative enhanced value in arterial phase and tumor-aorta enhancement ratio (arterial) correlated with MVD (P = 0.003, P = 0.022). Tumor-aorta enhancement ratio (arterial) correlated negatively with the extent of fibrosis (P = 0.004). The tumors with greater MVD and higher expression of VEGF tended to show high enhancement in the arterial dominant phase. On the other hand, the tumors with a larger amount of fibrosis showed a negative correlation with the grade of enhancement during the arterial phase.

CONCLUSION

Enhancement patterns on dynamic CT correlated with angiogenesis and may be modified by the extent of fibrosis.

Enhancement patterns of pancreatic adenocarcinoma on conventional dynamic multi-detector row CT: Correlation with angiogenesis and fibrosis

AIM: To evaluate retrospectively the correlation between enhancement patterns on dynamic computed tomography (CT) and angiogenesis and fibrosis in pancreatic adenocarcinoma.

METHODS: Twenty-three patients with pancreatic adenocarcinoma underwent dynamic CT and tumor resection. In addition to the absolute and relative enhanced value that was calculated by subtracting the attenuation value on pre-contrast from those on contrast-enhanced CT in each phase, we defined one parameter, “tumor-aorta enhancement ratio”, which was calculated by dividing enhancement of pancreatic cancer by enhancement of abdominal aorta in each phase. These enhancement patterns were correlated with the level of vascular endothelial growth factor (VEGF), microvessel density (MVD), and extent of fibrosis.

RESULTS: The absolute enhanced value in the arterial phase correlated with the level of VEGF and MVD (P = 0.047, P = 0.001). The relative enhanced value in arterial phase and tumor-aorta enhancement ratio (arterial) correlated with MVD (P = 0.003, P = 0.022). Tumor-aorta enhancement ratio (arterial) correlated negatively with the extent of fibrosis (P = 0.004). The tumors with greater MVD and higher expression of VEGF tended to show high enhancement in the arterial dominant phase. On the other hand, the tumors with a larger amount of fibrosis showed a negative correlation with the grade of enhancement during the arterial phase.

CONCLUSION: Enhancement patterns on dynamic CT correlated with angiogenesis and may be modified by the extent of fibrosis.

Colorectal cancer: texture analysis of portal phase hepatic CT images as a potential marker of survival

PURPOSE

To assess the utility of texture analysis of liver computed tomographic (CT) images by determining the effect of acquisition parameters on texture and by comparing the abilities of texture analysis and hepatic perfusion CT to help predict survival for patients with colorectal cancer.

MATERIALS AND METHODS

The study comprised a phantom test and a clinical evaluation of 48 patients with colorectal cancer who had consented to retrospective analysis of hepatic perfusion CT data acquired during a research study approved by the institutional review board. Both components involved texture analysis to quantify the relative contribution of CT features between 2 and 12 pixels wide to overall image brightness and uniformity. The effect of acquisition factors on texture was assessed on CT images of a cylindric phantom filled with water obtained by using tube currents between 100 and 250 mAs and voltages between 80 and 140 kVp. Texture on apparently normal portal phase CT images of the liver and hepatic perfusion parameters were related to patient survival by using Kaplan-Meier survival analysis.

RESULTS

A texture parameter that compared the uniformity of distribution of CT image features 10 and 12 pixels wide exhibited the least variability with CT acquisition parameters (maximum coefficient of variation, 2.6%) and was the best predictor of patient survival (P < .005). There was no significant association between survival and hepatic perfusion parameters.

CONCLUSION

The study provides preliminary evidence that analysis of liver texture on portal phase CT images is potentially a superior predictor of survival for patients with colorectal cancer than CT perfusion imaging.

SUPPLEMENTAL MATERIAL

http://radiology.rsnajnls.org/cgi/content/full/2502071879/DC1.

Quantitative imaging biomarkers in the clinical development of targeted therapeutics: current and future perspectives

Targeted therapeutics have challenged how imaging techniques assess tumour response to treatment because many new agents are thought to cause cytostasis rather than cytotoxicity. Advanced tracer development, image acquisition, and image analysis have been used to produce quantitative biomarkers of pathophysiology, with particular focus on measurement of tumour vascular characteristics. Here, we critically appraise strategies available to generate imaging biomarkers for use in development of targeted therapeutics. We consider important practical and technical features of data acquisition and analysis because these factors determine the precise physiological meaning of every biomarker. We discuss the merits of volume-based and other size-based metrics for assessment of targeted therapeutics, and we examine the strengths and weaknesses of CT, MRI, and PET biomarkers derived from conventional clinical data. We review imaging biomarkers of tumour microvasculature and discuss imaging strategies that probe other physiological processes including cell proliferation, apoptosis, and tumour invasion. We conclude on the need to develop comprehensive compound-specific imaging biomarkers that are appropriate for every class of targeted therapeutics, and to investigate the complementary information given in multimodality imaging studies of targeted therapeutics.

Validation of the use of calibration factors between the iodine concentration and the computed tomography number measured outside the objects for estimation of iodine concentration inside the objects: phantom experiment

PURPOSE

The aim of this study was to validate the use of a calibration factor measured outside the object for estimating the iodine concentration inside the object to improve the accuracy of the quantitative contrast-enhanced computed tomography (CT).

MATERIALS AND METHODS

Several known concentrations (0, 6, 9, and 12 mg I/ml) of iodine contrast material (CM) samples were placed inside and outside cylindrical acrylic phantoms of two sizes and were imaged under various combinations of the tube voltages and currents (kV/mAs-80/200, 100/200, 120/200, 140/200) to obtain K factors. The K factors were compared between the phantoms and among the tube voltages. Each CM concentration was estimated from the CT number using the K factor measured outside the phantom.

RESULTS

The K factors varied between the phantoms or among the tube voltages (P < 0.05). Although there were statistically significant variations in K factors among the different regions in a phantom, the mean variation coefficient was 3%-4%. The mean error of the estimated concentration was -5.5%.

CONCLUSION

The CM concentration should be accurately estimated at the region within a patient's body using the K factor measured at the surface of the body regardless of body size and tube voltage.

Accuracy of computed tomography perfusion in assessing metastatic involvement of enlarged axillary lymph nodes in patients with breast cancer

INTRODUCTION

The purpose of this study was to evaluate the diagnostic accuracy of computed tomography (CT) perfusion in differentiating metastatic from inflammatory enlarged axillary lymph nodes in patients with breast cancer.

METHODS

Twenty-five patients with 26 locally advanced breast tumors and clinically palpable axillary lymph nodes underwent dynamic multi-detector CT (LightSpeed 16; General Electric Company) at one scan per second for 150 seconds at the same table position after 40 ml intravenous contrast injection at 4.0 ml/second. Semi-automatic calculation of values of perfusion parameters - blood flow (BF), blood volume (BV), mean transit time (MTT), and permeability surface (PS) - was performed. Results were compared with pathology and with Her-2/neu and Ki-67 levels in a surgical specimen of the primary tumor.

RESULTS

Examined lymph nodes were inflammatory in 8 cases and metastatic in 18. Mean values of perfusion parameters in inflammatory and metastatic nodes, respectively, were BF of 76.18 (confidence interval [CI], 31.53) and 161.60 (CI, 40.94) ml/100 mg per minute (p < 0.05), BV of 5.81 (CI, 2.50) and 9.15 (CI, 3.02) ml/100 mg (not significant [n.s.]), MTT of 6.80 (CI, 1.55) and 5.50 (CI, 1.84) seconds (p = 0.07), and PS of 25.82 (CI, 4.62) and 25.96 (CI, 7.47) ml/100 mg per minute (n.s.). Size of nodes, stage of breast cancer, Ki-67 and Her-2/neu levels in breast cancer, and expression of primary tumor activity were not correlated to any perfusion parameter in metastatic nodes.

CONCLUSION

CT perfusion might be an effective tool for studying enlarged axillary lymph nodes in patients with breast cancer. It gives information on vascularization of lymph nodes, helping to understand the changes occurring when neoplastic cells implant in lymph nodes.

Delineation and segmentation of cerebral tumors by mapping blood-brain barrier disruption with dynamic contrast-enhanced CT and tracer kinetics modeling-a feasibility study

Dynamic contrast-enhanced (DCE) imaging is a promising approach for in vivo assessment of tissue microcirculation. Twenty patients with clinical and routine computed tomography (CT) evidence of intracerebral neoplasm were examined with DCE-CT imaging. Using a distributed-parameter model for tracer kinetics modeling of DCE-CT data, voxel-level maps of cerebral blood flow (F), intravascular blood volume (vi) and intravascular mean transit time (t1) were generated. Permeability-surface area product (PS), extravascular extracellular blood volume (ve) and extraction ratio (E) maps were also calculated to reveal pathologic locations of tracer extravasation, which are indicative of disruptions in the blood-brain barrier (BBB). All maps were visually assessed for quality of tumor delineation and measurement of tumor extent by two radiologists. Kappa (kappa) coefficients and their 95% confidence intervals (CI) were calculated to determine the interobserver agreement for each DCE-CT map. There was a substantial agreement for the tumor delineation quality in the F, ve and t1 maps. The agreement for the quality of the tumor delineation was excellent for the vi, PS and E maps. Concerning the measurement of tumor extent, excellent and nearly excellent agreement was achieved only for E and PS maps, respectively. According to these results, we performed a segmentation of the cerebral tumors on the base of the E maps. The interobserver agreement for the tumor extent quantification based on manual segmentation of tumor in the E maps vs. the computer-assisted segmentation was excellent (kappa = 0.96, CI: 0.93-0.99). The interobserver agreement for the tumor extent quantification based on computer segmentation in the mean images and the E maps was substantial (kappa = 0.52, CI: 0.42-0.59). This study illustrates the diagnostic usefulness of parametric maps associated with BBB disruption on a physiology-based approach and highlights the feasibility for automatic segmentation of cerebral tumors.