|Year : 2018 | Volume
| Issue : 3 | Page : 277-281
The role of dynamic contrast-enhanced MRI analysis of perfusion changes in hepatocellular carcinoma
Ahmed M Elzeneini, Mohamed I Yousef, Medhat M Refaat
Radiology Department, Benha University, Egypt
|Date of Submission||18-Mar-2018|
|Date of Acceptance||18-Apr-2018|
|Date of Web Publication||07-Jan-2019|
Dr. Ahmed M Elzeneini
Radiology and PET.CT Departments, Nasser Institute for Research and Treatment, 1351 Nile Corniche, Cairo
Source of Support: None, Conflict of Interest: None
Background Dynamic contrast-enhanced (DCE)-MRI functional imaging is primarily focused on quantitative evaluation of tumoral perfusion and permeability, thus enabling an insight into the pathophysiology of tissue and serving as early noninvasive biologic markers of tumorigenesis.
Aim The aim was to evaluate the functional role of DCE-MRI analysis of perfusion changes in hepatocellular carcinoma (HCC).
Patients and methods A total of 43 patients with liver cirrhosis having 65 HCCs all underwent 3 T multiphase DCE-MRI assessment. Maximum relative enhancement, area under curve, wash-in ratio, wash-out ratio, time to arrival, and time to peak semiquantitative measurements were analytically compared between the hepatocellular carcinogenic lesions and the adjacent lesion-free liver cirrhosis.
Results Comparison of different perfusion metrics across hepatocellular carcinogenic lesions and adjacent lesion-free liver cirrhosis revealed exceling statistical significance. Diagnostic accuracies were highest when using wash-out ratio (86.2%) to detect HCC from background cirrhosis, whereas they were lowest using area under the curve (67.7%). Implementing wash-in ratio (81.9%), as a first-pass perfusion metric, surpassed its counterpart, maximum relative enhancement (73.4%), in diagnostic reliability. Regarding the timing of flow dynamics, time to arrival (84.1%) was more important than time to peak (78.1%) as a diagnostic indicator of hepatocarcinogenesis.
Conclusion Multiphase DCE-MRI perfusion analyses provide quantitative hemodynamic metrics that promise potential usefulness as noninvasive biomarkers in the detection of HCC.
Keywords: 3T dynamic contrast-enhanced MRI, hepatocellular carcinoma, liver cirrhosis, multiphase enhancement, semiquantitative analysis
|How to cite this article:|
Elzeneini AM, Yousef MI, Refaat MM. The role of dynamic contrast-enhanced MRI analysis of perfusion changes in hepatocellular carcinoma. Benha Med J 2018;35:277-81
|How to cite this URL:|
Elzeneini AM, Yousef MI, Refaat MM. The role of dynamic contrast-enhanced MRI analysis of perfusion changes in hepatocellular carcinoma. Benha Med J [serial online] 2018 [cited 2020 Mar 30];35:277-81. Available from: http://www.bmfj.eg.net/text.asp?2018/35/3/277/249428
| Introduction|| |
Hepatocellular carcinoma (HCC) is considered one of the most aggressive cancers worldwide, affecting principally developing countries. In Egypt, it ranks second in the most common cancers affecting men, whereas fifth in those affecting women. Despite different treatment regimens, prognosis of HCC remains very poor with an overall 5-year survival rate less than 5%. Proper HCC management is hindered by lack of biomarkers for the early diagnosis, prognosis, and therapy monitoring of HCC. Therefore, it is necessary to identify novel molecular markers .
MRI plays an increasingly important role in screening and posttreatment follow-up of hepatic malignancies, because of its elite contrast resolution, lack of ionizing radiation, and functional imaging ability. The anatomical-based role of conventional MRI in the posttherapeutic evaluation and detection of malignant cirrhotic HCC nodules relies on the identification of gross morphological tumoral changes. Failure of conventional imaging measures to detect early tumoral micro-changes renders them insufficient in the early detection of HCC and post-treatment surveillance .
Carcinogenesis in liver cirrhosis is specifically associated with microstructural hypercellular changes that are characteristic to HCC as opposed to being insignificant in cirrhotic background tissue as well as regenerative and dysplastic nodules. Hepatic carcinogenesis hemodynamic alterations occur along the timeline of the multistep differentiation from low-grade to high-grade dysplastic nodules and from early to progressive HCC. Functional imaging findings can be used to depict these changes correlating with the histological differentiation of the nodules and predicting their outcomes .
Angiogenesis with characteristic dense arterial neovascularization is distinctively critical for the growth and progression of smaller well-differentiated regenerative or dysplastic nodules to larger poorly differentiated HCC masses. Assessment of tumoral vascular and microvascular pathophysiology can be enabled through dynamic contrast-enhanced (DCE)-MRI. The dynamics and pattern of contrast enhancement within tumoral tissue are directly influenced by angiogenesis and correlated with microcirculatory density .
Perfusion imaging offers quantitative distinction between progressive delayed enhancement of granulation tissue and early arterial tumoral tissue enhancement with rapid washout. The characteristic hypervascular nature of HCC with early arterial intake and rapid washout allows for its conventional diagnosis through the qualitative visual assessment of postcontrast series, regardless of the need for tissue pathological verification .
There are two major mathematical approaches to studying liver perfusion: model-free signal to time curve methods and pharmacokinetic models. There is no current consensus as to which kinetic model is to be implemented to evaluate the liver. According to the mathematical model utilized and the based physiological assumptions, many quantitative parameters can be obtained. The data obtained are dependent upon the model used .
The use of model-free semiquantitative analysis is widely encouraged because of its simplicity with no need for sophisticated kinetic modeling based on varying theoretical postulations. These approaches rely on computing measurable parameters from the tissue concentration-time curves. Such parameters include area under the curve (AUC), peak enhancement ratio, wash-in and wash-out slopes, and mean transit time .
| Patients and methods|| |
The study was designed to enroll a random group of patients with HCC on a background of cirrhosis. The entire study was conducted at Nasser Institute for Research and Treatment. The cohort of the study included 43 patients having 65 HCCs, 31 males and 12 females, and their ages ranged from 45 to 63 years. The patients were referred to the Radiology Department over a period of 18 months from July 2017 until January 2017 from the Institute’s Outpatient Clinics, Tropical Medicine Department, and Vascular Intervention Unit. Written informed consent was obtained from all individual participants included in the study. The study was approved by the Institutional Review Board.
MRI was conducted on a 3.0 T MR scanner (Philips Achieva; Philips Medical Systems, The Netherlands) equipped with a phased array torso surface coil.
Conventional unenhanced MRI sequences were obtained in axial plane utilizing respiratory-triggered techniques, with the following parameters: T1-weighted imaging including in-phase and opposed phase (TR/TE=10/4.6 ms, flip angle=15°, section thickness=7 mm, intersection gap=2 mm, and field of vision (FOV)=300–350 mm), T2-weighted imaging (TR/TE=1000/80 ms, flip angle=90°, section thickness=7 mm, intersection gap=2 mm, and FOV=300–350 mm); T2 fat-suppression (SPAIR) (TR/TE=1000/80 ms, flip angle=90°, section thickness=7 mm, intersection gap=2 mm, and FOV=300–350 mm); And diffusion-weighted imaging, including b values of 0, 200, and 1000 (TR/TE=1700/76 ms, section thickness=7 mm, intersection gap=2 mm, and FOV=300–350 mm).
Dynamic contrast-enhanced MRI
Dynamic MRI was then performed in axial plane utilizing breath-hold techniques. A series of 3D fat-suppressed T1-weighted spoiled gradient echo sequences (THRIVE) were acquired using the following parameters: TR/TE=4.6/2.3 ms, flip angle=15°, breath-hold=20 s, number of slices=130–140, section thickness=3 mm, intersection gap=1.5 mm, and FOV=300–350 mm. Unenhanced data set was first acquired before contrast administration. Intravenous bolus injection of 0.1 mmol/kg body weight of Gadolinium-DTPA (Magnavist; Schering, Berlin, Germany) was administered at a rate of 2 ml/s using an automatic injector. Four successive imaging, data sets were acquired. Dynamic data sets were timed to start after the arrival of the contrast bolus to the aortic arch, according to the following: arterial phase 20–30 s, portal phase 50–60 s, late venous phase 80–90 s, and delayed phase 150–180 s.
Standard of reference
All HCC lesions were confirmed by histopathology.
The review of all conventional and dynamic MRI was performed on the 3T MR Unit workstation, utilizing the commercially available software (Philips Medical Systems) by a clinical radiologist with 5 years of experience in cross-sectional MRI. Conventional MR images were thoroughly assessed, and lesions were located and characterized according to their number, size, shape, signal criteria, and restriction pattern. Dynamic series with color maps and subtraction data sets were analyzed for lesion-enhancement patterns and heterogeneity. Three user-defined regions of interest (ROIs) were placed on areas of maximum hypervascularity in each of the identified lesions. Three ROIs were also randomly placed in the lesion-free or lesion-bordering liver parenchyma in each patient. ROIs were standardized to 2.1 mm2. Maximum relative enhancement (MRE), AUC, wash-in ratio (WIR), wash-out ratio, time to arrival, and time to peak (TTP) measurements were generated.
All data were expressed as mean±SD. Paired Student’s t tests were used to compare different, normally distributed, hemodynamic parameters between the HCC lesions and adjacent lesion-free liver cirrhosis. A two-sided P value of less than 0.05 was required for statistical significance. Receiver operating characteristic curves were constructed and the diagnostic performances extracted. Data analyses were performed using GraphPad Prism version 6.00 for Windows (GraphPad Software, La Jolla, California, USA).
| Results|| |
Data analyses are tabulated as mean±SD in [Table 1]. Receiver operating characteristic curves are illustrated in [Figure 1] and DCE-MRI case analyses are presented in [Figure 2].
|Figure 1 Combined receiver operating characteristic curves of different analyzed semiquantitative hemodynamic metrics.|
Click here to view
| Discussion|| |
Established guidelines embark on the importance of transforming cross-sectional imaging to quantitative tools, as well as standardizing data acquisition and analyses methods across the clinical practice to reduce variability and ensure reliability . Multistep hepatocarcinogenesis is a widely established process involving a progressive sequence of cytological abnormalities and architectural changes .
Liver cirrhosis is presented with a continuum of hepatocellular lesions that range from hyperplastic regenerative nodules and benign low-grade dysplastic nodules to premalignant adenomatous high-grade dysplastic nodules . These premalignant dysplastic nodules may evolve into early hypovascular carcinogenesis and proceed to less differentiated, progressed HCC .
HCC evolution involves stepwise pathological arterialization and sinusoidal capillarization of the blood supply . Pathological hepatonodular inflows demonstrate bitonic fluctuations in the arterial supply with preceding decrease in the preexisting paired (accompanied by bile ducts) hepatic arteries and succeeding increase in pathological unpaired neoarteries . However, portal supply undergoes an earlier monotonic decrease mounting to late reversed outflow . Newly formed deranged unpaired arteries are excessively tortuous and increasingly porous. Thus, tumoral progression leads to increased tumoral permeability and raised oncotic interstitial pressure . Concurrent capillarization of the normally fenestrated sinusoidal endothelium occurs during carcinogenic evolution. This involves endothelial thickening, basement membrane formation, and fenestral loss, together with extracellular space matrix deposition . The malignant transformation of a premalignant nodule and its progression necessitates the initiation of neovascularization to provide the required nutrients for cancerous growth; this process is known as the angiogenic switch. This angiogenic switch is induced by tissue hypoxia and proangiogenic tumor-host reaction factors, such as vascular endothelial growth factor and other growth factors .
DCE-MRI functional imaging is primarily focused on quantitative evaluation of tumoral perfusion and permeability, thus enabling an insight into the pathophysiology of tissue. Physiologic changes that precede morphologic changes serve as early biologic markers of tumorigenesis . DCE-MR semiquantitated imaging analyses ([Figure 1] and [Figure 2]) have shown favorable results in our study ([Table 1]) that promise useful potential in the field of liver oncologic imaging, pertaining to the assessment and early detection of carcinogenesis.
In the present study, we found that wash-out kinetics (86.2% accuracy) surpassed wash-in kinetics (81.9% accuracy) in their diagnostic capacity to detect HCC from background cirrhosis. Regarding first-pass perfusion metrics, WIR proved to be more valuable than MRE (73.4% accuracy). Regarding the timing of contrast dynamics, time to arrival (84.1%) exceeded in performance than time to peak (78.1% accuracy). Least performance was scored by AUC (67.7% accuracy). These results are in agreement with previous studies which showed that perfusion metrics such as WIR and MRE comparably performed as reliable indicators for hepatocarcinogenic angiogenesis and tumoral microvessel density, respectively ,. In contrast to our results, several studies reported that selective first-pass perfusion metrics such as relative arterial enhancement and initial AUC surpassed, in diagnostic performance, other nonselective metrics such as MRE and AUC, respectively ,.
| Conclusion|| |
Multiphase DCE-MRI perfusion analyses provide quantitative metrics that promise potential usefulness as noninvasive biomarkers in the detection of HCC.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]