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

Miles, Kenneth A.; Young, Helen; Chica, Sandra L.; Esser, Peter D.

doi:10.1007/s00330-006-0424-x

Cited by 38 publications

(40 citation statements)

References 22 publications

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“…The efficient attenuation of X-rays by iodine increases CT image intensity, which is linearly proportional to the iodine concentration [3]. The basis of PCT is to track the delivery of iodine by measuring changes in image intensity after the arrival of contrast bolus.…”

Section: Basic Principles Of Pctmentioning

confidence: 99%

Dynamic perfusion CT in brain tumors

Yeung

Yartsev

Fainardi

et al. 2015

European Journal of Radiology

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Section: Basic Principles Of Pctmentioning

confidence: 99%

Dynamic perfusion CT in brain tumors

Yeung

Yartsev

Fainardi

et al. 2015

European Journal of Radiology

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“…This normalisation is an advantage because it inherently corrects for individual variations in cardiovascular function that might otherwise alter tumour perfusion despite no change in microvessel density. However, when using semi-quantitative parameters, it is also important to calibrate the CT system because significant variations in iodine sensitivity can exist between CT systems or on the same CT system over time [7].…”

Section: Semi-quantitative Parametersmentioning

confidence: 99%

Dynamic contrast-enhanced imaging techniques: CT and MRI

O’Connor¹,

Tofts²,

Miles³

et al. 2011

BJR

175

121

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ABSTRACT. 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. The tumour microvasculature can readily be imaged using X-ray, CT and MRI techniques. This review concentrates on three main methods. Dynamic contrast-enhanced CT (DCE-CT) and dynamic contrastenhanced MRI (DCE-MRI) are well-established techniques, where data acquisition and analysis are comparable despite inherent differences in signal production and mechanism of tissue contrast enhancement (reviewed in [1,2]). Although they can be performed on conventional clinical scanners, they require specialist image analysis to extract biomarkers of tumour vascular function. In distinction, arterial spin labelling (ASL) offers a highly specific method of measuring cerebral perfusion without exogenous contrast agent (CA) administration, but is at present a research technique. The practical applications of these techniques are considered elsewhere in this special issue. Basic principles of dynamic contrast-enhanced imagingDCE imaging describes the acquisition of a baseline image(s) without contrast enhancement followed by a series of images acquired over time after an intravenous bolus of conventional CA. The presence of CA within cerebral blood vessels and tissues affects measured X-ray attenuation on CT in a linear fashion and the calculated signal intensity on MRI in a non-linear manner. Thus, the temporal changes in contrast enhancement effectively provide a time-concentration curve, which can be analysed to quantify a range of physiological parameters that indicate the functional status of the vascular system within tumours and adjacent tissues. These parameters reflect the two-compartment pharmacokinetics exhibited by CA, comprising intravascular and extravascular components. During the first-pass of the CA through the circulation (typically 45-60 s after injection), CA is predominantly intravascular allowing evaluation of perfusion (i.e. blood flow per unit volume or mass of tissue), relative blood volume (rBV) and mean transit time. During the subsequent 2-10 min, there is increasing passage of CA into the extravascular space, and imaging during this delayed phase enables measurement of vascular permeability and relative extravascular volume. DCE-CT image acquisition protocolsA number of distinct DCE-CT techniques have been developed, reflecting the different analysis methodologies adopted by commercial software packages for perfusion CT. The main acquisition factors to be considered are summarised in Table 1. For DCE-CT, the need to keep the radiation burden as low as practicable is a constraint on the total number of images acquired and the X-ray exposure ...

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“…K factor is defined as the slope of the plot of attenuation in HU vs different contrast agent concentrations (in milligrams per millimetre) [17]. Therefore, the calibration procedure aims to deter- re the concentration of contrast agent [20].…”

Section: Calibration Of the Ct Systemmentioning

confidence: 99%

“…We performed our calibrat ethod similar to others reported in literature [17,20,24], with a cylindrical acrylic phantom (Fluke Biomedical) with five holes. The thickness of the phantom is 15 cm with diameter of 32 cm and contains five pipettes holes (A, B, C, D, E, see Figure 2), one in the centre and four around the perimeter, 90˚ apart and 1 cm from the edge.…”

Section: Calibration Of the Ct Systemmentioning

confidence: 99%

“…As reported in literature [17], calculation of SPV includes the value of a calibration factor that converts iodine concentration to CT attenuation in Hounsfield units (HU); but calibration factor is specific for each CT system and changes over time [20], so, a calibration procedure has to be carried out before computing SPV tumour index. A calibration procedure was carried out to examine dependence of K factor by the position within the gantry.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Sources of Variability in the Use of Standardized Perfusion Value for HCC Studies

D’Antò¹,

Cesarelli²,

Fiore³

et al. 2012

OJMI

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Hepatocellular carcinoma (HCC) is one of the world's most common malignant tumours. As it is known, liver tumour tissue is characterised by an increased blood supply related to neoangionesis which causes an increased arterial vascularisation. CT Perfusion Imaging is an important, non invasive, technique for qualitative assessment of tissue perfusion after contrast agent administration. Nevertheless, being able to reliably quantifying angiogenesis is increasingly important to both the evaluation of the disease progression and monitoring of the therapeutic response of HCC. With this in mind, we believe that could be helpful to employ Standardised Perfusion Value (SPV), which has the potential to be a useful non-invasive marker of HCC angiogenesis. However, before using SPV in clinical practice, we need to verify its reliability. There are different causes of variability in applying the SPV index, e.g., the technical specifications of the CT system employed and the image processing system. In this paper the authors will analyse the variability of the BF a estimates and the variability due to the calibration procedure of the CT system, this with the objective of verifying how these factors affects SPV values. In our case, perfusion MDCT images of seventeen HCC patients were analysed. A software application, based on maximum slope method, was developed to compute BF a and SPV values. Four radiologists were involved in images processing evaluating variability related to ROI selection; each radiologist repeated the ROI drawing four times on the same image set. We computed the K calibration factor in order to evaluate SPV variability due to calibration protocol of CT systems. Results show that calibration factor variance, due to the position in the gantry, is less than BF a variability. So, we conclude that, when daily calibration is preferred, a simplified protocol, which neglects the dependence of K factor from the position, may be utilised; at least until the intrinsic variability of perfusion parameter computation operator-dependent will be reduced.

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

Cited by 38 publications

References 22 publications

Dynamic perfusion CT in brain tumors

Dynamic perfusion CT in brain tumors

Dynamic contrast-enhanced imaging techniques: CT and MRI

Sources of Variability in the Use of Standardized Perfusion Value for HCC Studies

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