BackgroundPerfusion CT is a technology which allows functional evaluation of tissue vascularity. Due to this potential, it is finding increasing utility in oncology. Although since its introduction continuous advances have interested CT technique, some issues have to be still defined, concerning both clinical and technical aspects. In this study, we dealt with the comparison of two widely employed mathematical models (dual input one compartment model – DOCM - and maximum slope – SM -) analyzing their robustness to the noise.MethodsWe carried out a computer simulation process to quantify effect of noise on the evaluation of an important perfusion parameter (Arterial Blood Flow – BFa) in liver tumours. A total of 4500 liver TAC, corresponding to 3 fixed BFa values, were simulated using different arterial and portal TAC (computed from 5 real CT images) at 10 values of signal to noise ratio (SNR). BFa values were calculated by applying four different algorithms, specifically developed, to these noisy simulated curves. Three algorithms were developed to implement SM (one semiautomatic, one automatic and one automatic with filtering) and the last for the DOCM method.ResultsIn all the simulations, DOCM provided the best results, i.e., those with the lowest percentage error compared to the reference value of BFa. Concerning SM, the results are variable. Results obtained with the automatic algorithm with filtering are close to the reference value, but only if SNR is higher than 50. Vice versa, results obtained by means of the semiautomatic algorithm gave, in all simulations, the lowest results with the lowest standard deviation of the percentage error.ConclusionsSince the use of DOCM is limited by the necessity that portal vein is visible in CT scans, significant restriction for patients’ follow-up, we concluded that SM can be reliably employed. However, a proper software has to be used and an estimation of SNR would be carried out.
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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