Focal nodular hyperplasia of the liver: diffusion and perfusion MRI characteristics

Focal nodular hyperplasia of the liver: diffusion and perfusion MRI characteristics

Available online at www.sciencedirect.com Magnetic Resonance Imaging 31 (2013) 10 – 16 Focal nodular hyperplasia of the liver: diffusion and perfusi...

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Available online at www.sciencedirect.com

Magnetic Resonance Imaging 31 (2013) 10 – 16

Focal nodular hyperplasia of the liver: diffusion and perfusion MRI characteristics Francescamaria Donatia,⁎, Piero Boraschia , Roberto Gigonia , Simonetta Salemia , Fabio Falaschi a , Carlo Bartolozzi b a

Department of Diagnostic Radiology, Vascular and Interventional Radiology and Nuclear Medicine, 2nd Unit of Radiology, Pisa University Hospital, 56124 Pisa, Italy b Diagnostic and Interventional Radiology of the Department of Oncology, Transplants and Advanced Technologies in Medicine, University of Pisa, 56124 Pisa, Italy Received 19 December 2011; revised 8 June 2012; accepted 26 June 2012

Abstract Purpose: To present diffusion and perfusion magnetic resonance imaging (MRI) characteristics of focal nodular hyperplasia (FNH) of the liver. Materials and Methods: Thirty-five patients with 52 FNHs (21 were pathologically-confirmed) underwent MRI at 1.5-T device. MR diffusion [diffusion-weighted imaging (DWI)] was performed using a free-breathing single-shot, spin-echo, echo-planar sequence with b gradient factor value of 500 s/mm². MR perfusion [perfusion-weighted imaging (PWI)] consisted of a 3D free-breathing LAVA sequence repeated up to 5 minutes after injection of 7 mL Gd-BOPTA (MultiHance, Bracco, Italy) and 20 mL saline flush at a flow rate of 4 mL/s. Apparent diffusion coefficient (ADC) and time-signal intensity curve (TSIC) were obtained for both normal liver and each FNH by two reviewers in conference; maximum enhancement (ME) percentage, time to peak enhancement (TTP), and maximal slope (MS) were also calculated. Results: On DWI mean ADC value was 1.624×10 −3 mm 2/s for normal liver and 1.629×10 −3 mm 2/s for FNH. ADC value for each FNH and the normal liver was not statistically different (P=.936). On PWI, TSIC-Type 1 (quick and marked enhancement and quick decay followed by slowly decaying) was observed in all 52 FNHs, and TSIC-Type 2 (fast enhancement followed by slowly decaying plateau) in all normal livers. The mean ME, TTP and MS values were significantly different for FNH and normal liver (P=.005). Conclusion: FNHs of the liver showed typical diffusion and perfusion MRI characteristics in all cases. On the ADC map, we could get similar value between the FNHs and the background parenchyma. On the perfusion imaging, FNHs showed a different pattern distinguished from the background liver. © 2013 Elsevier Inc. All rights reserved. Keywords: Diffusion-weighted MR imaging; Perfusion-weighted MR imaging; Liver MR; Focal nodular hyperplasia; Liver

1. Introduction Focal nodular hyperplasia (FNH) is the second most common (prevalence of 0.9%) benign liver tumor after hemangioma. FNH is asymptomatic in most of patients, and in such cases no treatment is necessary. Therefore, differentiation between FNH and other hypervascular lesions

⁎ Corresponding author. Tel.: +39 050 996782; fax: +39 1782211474. E-mail addresses: [email protected], [email protected] (F. Donati). 0730-725X/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.mri.2012.06.031

(hepatocellular adenoma, hepatocellular carcinoma and hypervascular metastases) is crucial to choice proper treatment [1]. Magnetic resonance imaging (MRI) has higher sensitivity and specificity than does ultrasonography or computed tomography in the diagnosis of FNH. To date, the use of gadolinium-based liver-specific contrast agents (Gd-BOPTA and Gd-EOB-DTPA), with both dynamic and hepatobiliary study, has provided the greatest diagnostic sensitivity among the various imaging techniques [2,3]. Recently, diffusion-weighted imaging (DWI), and perfusion-weighted imaging (PWI) of the liver have shown the

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potential of supplying additional tools to assess liver function, providing information concerning both the softtissue characteristics and the vascularity (perfusion and angiogenetic activity) of the lesions [4]. The purpose of our study was to present diffusion and perfusion MRI characteristics of FNH of the liver.

2. Materials and methods 2.1. Patients Our institutional review board approved this study, and written informed consent was taken after explanation of the complete examination procedure from all enrolled subjects. According to a local protocol, both diffusion- and perfusionweighted magnetic resonance imaging (MRI) was routinely performed in patients with a known or suspected focal solid liver lesion at ultrasound and/or multi-detector computed tomography (CT). Among these, a series of thirty-five patients (27 women and 8 men; age range: 21–52 years; mean age, 36.02±9.62 years) with 52 FNHs of at least 1 cm in size (mean diameter: 51.23±24.63 mm; range:15–102 mm) were retrospectively included in our study group. None of these subjects had concomitant hepatitis or other diffuse liver diseases. In 21 out of 52 FNHs, diagnosis was pathologically verified; histopathologic specimens were obtained on open surgery (14 lesions in eight patients) and with percutaneous biopsy (seven lesions in six patients) within 4 weeks from MR examination. Eight of these subjects were symptomatic and presented pain in the upper abdomen and six showed elevated values of gamma-glutamiltranspeptidasi (GT). In the remaining 31 focal lesions in 21 patients, the final diagnosis of FNH was rendered on the basis of different data including typical radiologic findings from contrast-enhanced ultrasonography, CT and MRI including hepatobiliary phase; all these patients were asymptomatic and underwent imaging follow-up (ultrasound at 6 and 18 months and MRI at 12 and 24 months) for at least 12 months. 2.2. Imaging technique All patients underwent MR examination performed with a superconductive system operating at 1.5 T (Signa HDx, GE Healthcare). The 12-channel phased-array body coil was used for both excitation and signal reception. The MR study began with our routine liver imaging protocol including axial T1-weighted in and out of phase breath-hold spoiled gradient-echo sequence (repetition time, 110–130 ms; echo time 1, 2.0 ms; echo time 2, 4.3 ms; flip angle, 90°; section thickness, 5 mm; interslice gap, 0.5 mm; matrix size, 256×160 pixels; signal averaged, 1; acquisition time, 28–35 s), axial T2-weighted, respiratory-triggered, fat-suppressed, fast spin-echo sequence (repetition time automatically adapted to the patient's breathing pattern, 6000–18000 ms; echo time, 95.5 ms; echo train length, 16;

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section thickness, 5 mm; interslice gap, 0.5 mm; signals averaged, 3–4; acquisition time, 3–4 min) and/or axial single-shot T2-weighted, with and without fat-suppressed, fast spin-echo sequence (repetition time, minimum; echo time, 80 ms; section thickness, 5 mm; interslice gap, 0.5 mm; signal averaged, 0.5–0.6; acquisition time, 23–24 s). Diffusion-weighted MRI was performed to cover the entire liver using axial free-breathing single-shot spin-echo echo-planar (SS-EPI) sequence (repetition time, 3000–4500 ms; echo time, 64–80 ms; section thickness, 5 mm; interslice gap, 1 mm; field of view, 35–45 cm; matrix size, 160×160 pixels; signal averaged, 2; parallel imaging factor, 2; acquisition time, 30–40 s). Diffusion-weighted gradients were applied in all the three orthogonal directions and we used a b value of 500 s/mm² as an optimal compromise between image quality (signal-to-noise ratio) and true diffusion characteristics. Perfusion-weighted MRI consisted of a 3D free-breathing LAVA sequence (repetition time, 2.28 ms; echo time, 1.05 ms; section thickness, 10.0 mm; interslice gap, 0.0 mm; field-of-view, 35–42 cm; matrix size,128×128 pixels; signal averaged, 0.75; parallel imaging factor, 2; acquisition time, 1 s), covering the entire liver, repeated up to 5 min after injection of a fixed dose of 7mL Gd-BOPTA (MultiHance, Bracco, Italy) with a 20-mL saline flush, injected with a flow rate of 4 mL/s. In each patient, the total number of acquired sequences is 300 without interval. 2.3. Image analysis DW and PW images were analyzed by different experienced observers (with the consensus of two radiologists for each technique) that perform at least 150 hepatic MR examinations per year and who were blinded to patient identification, previous imaging findings and final diagnoses. Apparent diffusion coefficient (ADC) and time-signal intensity curve (TSIC) were obtained on a dedicated workstation (Advantage Windows 4.3, GE Healthcare), which supports with dedicated softwares for semi-automated images post-processing. All ADC measurements were obtained from the images with a b value of 500 s/mm². The signal intensities for ADC calculation were measured by using circular operatordefined region of interest (ROI) placed on both normal liver parenchyma and each focal liver lesion to cover the largest possible area. MR perfusion postprocessing provides a plotted corrected graph which demonstrates the stepwise changes in enhancement over time in different vascular phase after contrast administration. To create TSIC, the signal intensity measurements at the level of both normal liver parenchyma and each FNH were recorded by ROIs, placed in a homogenous region of the liver or lesion, avoiding vessels. Maximum enhancement percentage (ME%), time to peak enhancement (TTP) and maximal slope (MS) were also calculated.

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2.4. Statistical analysis Statistical analyses were performed by using commercially available statistical software (MedCalc; Version 8.0.1.0). The distribution of the qualitative variables was expressed as the relative frequency of the various modalities under observation. The distribution of the quantitative variables was expressed as the mean, standard deviation, minimum, maximum and number of observations. ADC and quantitative perfusion data (ME%, TTP and MS) were analyzed by using the median and inter-quartile range, unless otherwise stated. Mean values were calculated by using the independent-samples t test. Comparison of the ADC and ME%, TTP and MS values between and within the liver and FNH groups was performed by using analysis of variance test (F ratio) and their differences were tested for statistical significance using Kruskal-Wallis test for all pair wise comparisons (P value of less than .05 was considered statistically significant).

3. Results All patients well tolerated the examination, and no side effect was reported after contrast agent administration. All MR studies included in the study group were considered diagnostic by the reviewers. On DWI, mean ADC value was 1.624×10 −3 mm 2/s for normal liver and 1.629×10 −3 mm 2/s for FNH. ADC value for each FNH and the surrounding normal liver was not statistically different (P=.936) (Fig. 1). On PWI, two different time-signal intensity curve shapes, classified according to the schemes described in the literature [5,6], were observed: type 1, showing quick and marked enhancement (Fig. 2) and quick decay, followed by a slowly decaying plateau, and type 2, characterized by fast enhancement followed by slowly decaying plateau.

Fig. 1. Diagram. Multiple variables graph illustrates ADC values of all 52 FNHs and the corresponding normal liver parenchyma.

“Quick” and “slow” decay during the perfusion imaging are based on degree of slope of the curve over time. TSIC-type 1 was recognized in all 52 FNHs, whereas TSIC-type 2 was observed in all normal livers (Figs. 3 and 4). The mean values of PWI quantitative parameters were significantly different for FNHs and normal liver, resulting respectively: ME% 290.952±30.806 and 208.571±7.606; TTP 20.333±1.906 and 39.619±3.024; MS 31.142±3.439 and 19.380±3.748 (Pb.005).

4. Discussion Focal nodular hyperplasia is a benign tumor-like hepatic lesion that is classified into two types: classic (80% of cases) and non-classic (20%). The gross appearance of classic FNH consists of lobulated contours and parenchyma that is composed of nodules surrounded by radiating fibrous septa originating from a central scar. Among classic FNH lesions, one or more macroscopic central scars are present in most cases. The cellular structure of FNH is similar to that of normal hepatic parenchyma, apart from the presence of abnormal both biliary system and angio-architecture. Typically, FNH contains one or more large arteries that run in the lesion divided into numerous capillaries, connected to the sinusoids; besides, FNH does not contain portal veins and large draining veins running off the lesion from the sinusoids toward the hepatic vein have been demonstrated in some limited cases. The gross appearance of non-classic FNH is heterogeneous and globally resembles that of adenomas in most cases, with vaguely lobulated contours and lack of a macroscopic central scar in almost all cases. Classic FNH contains all of the components, including an abnormal nodular architecture, malformed vessels, and cholangiolar proliferation. The non-classic type contains two of the three components but always shows bile ductular proliferation. Since FNH is not associated with any malignant potential and has only a minimal tendency for complications, this lesion is almost always managed conservatively [2,3]. On the other hand, other hypervascular lesions (hepatocellular adenoma, hepatocellular carcinoma, and hypervascular metastases) frequently are candidate for surgical resection or other interventional treatments [1]. The clinical need is therefore to differentiate these lesions accurately at noninvasive diagnostic imaging without recourse to lesion biopsy [3]. Distinction of FNH from other hypervascular lesions at ultrasonography and CT may be difficult because these modalities, unlike MRI, do not provide information concerning the tissue characteristics of the lesions. The ability of MRI to detect intrinsic tissue components, is particularly improved in the last years. Particularly, the use of gadolinium-based liver-specific contrast agents (GdBOPTA and Gd-EOB-DTPA), with both dynamic and hepatobiliary study, has allowed to obtain both vascular and hepatocellular information regarding normal liver parenchyma and focal liver lesions [7,8]. Therefore,

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Fig. 2. PW sequence. These images, obtained during 1 second and acquired 19 s after contrast injection, cover both focal nodular hyperplasia and normal surrounding liver parenchyma. During this phase FNH well demonstrates the signs of arterialization.

information about lesion vascularity is obtained during the dynamic phase, and information about lesion cellularity is obtained during the delayed phase of imaging. To date, gadolinium-based liver-specific contrast MRI is considered the gold standard in the diagnosis of FNH, and especially in the differential diagnosis between FNH and hepatic adenoma [3,7,8]. Recently, DWI and PWI of the liver have supplied additional tools to assess liver function, providing both morphologic and metabolic information in a one-stop imaging protocol [4,9]. Diffusion-weighted MRI is an MRI technique used to show thermally induced molecular diffusion, which is the Brownian motion of the spins in biologic tissues. The ADC is a quantitative parameter calculated from the DW-MR images, that combines the effects of capillary perfusion and water diffusion in the extracellular extravascular space. DWI can be used to differentiate normal and abnormal tissues, and it might help in the characterization of various abnormalities [7]. Several studies have reported that ADC can contribute to the differential diagnosis of benign and malignant focal lesions in the liver [9–15]. Nevertheless, there are many

discrepancies in the reported ADC values; this is often associated with the choice of b-values and other technical parameters. However, some authors demonstrated that the ADC of malignant lesions was significantly lower than that of the surrounding hepatic tissue, whereas the ADC of benign lesions (particularly hemangiomas and cysts) was higher than that of the surrounding hepatic tissue. Nevertheless, the benign hepatocellular lesions (such as focal nodular hyperplasia and adenoma) presented intermediate ADC values, which were not different from those of normal liver parenchyma, in according to our results [10–15]. In our study, ADC value for each FNH and the surrounding normal liver was not statistically different and mean ADC value was about 1.6×10 −3 mm 2/s for both normal liver and FNH. These findings perfectly correlated with the pathologic structure of the FNH, that is defined by the International Working Party as “a nodule composed of benign-appearing hepatocytes occurring in a liver that is otherwise histologically normal” [16]. Perfusion imaging provides the ability to detect regional and global alterations in organ blood flow. The utility of hepatic perfusion characterization relies on the resolution of each component of its dual blood supply, the portal vein and

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Fig. 3. (A-D) A 34-year-old woman with abdominal pain and elevated values of gamma-GT. MR diffusion shows diffusion-weighted image (A) and ADC map (B). ADC value of both the normal liver and the hepatic lesion was calculated by using a circular ROI, resulting 1.59×10−3 mm2/s and 1.62×10−3 mm2/s, respectively. MR perfusion shows a contrast-enhanced LAVA image (C) obtained at the maximum enhancement, that demonstrates the arterialization of the lesion; a circular ROI was placed at the level of both the normal liver and the lesion. The perfusion graph (D) shows two TSIC-types: TSIC-type 1 (red) for the FNH and TSIC-type 2 (green) for the normal liver. The final diagnosis of FNH was obtained by histopathologic specimen.

the hepatic artery, because contributions from each are altered predictably in many diseases [17]. Because most pathologic entities of the liver affect blood flow, MR perfusion can improve the sensitivity and specificity of diagnostic liver imaging, providing information concerning the intratumoral distribution of vessels (vascular density) as well as the nature of the vascular wall (intact or immature and leaky blood vessels) [6,18]. This shows potential for better understanding of tumor enhancement patterns and angiogenesis; therefore, MR perfusion can be utilized for the detection and characterization of focal liver lesions and the quantification of blood flow parameters [6,19–21]. Recently, Wang et al [6] reported that the TSIC for FNH showed signs of “arterialization” (steep enhancement) in the first part of the curve and subsequently signs of “hepatization” (curve running slightly above but parallel to the curve of the liver), in according to our results. In fact, in our study, all FNHs presented a curve of Type 1, showing quick and marked enhancement and quick decay followed by slowly decaying, related to the predominant

arterial support, with mean TTP=20.333, mean ME%= 290.952 and mean MS=31.142. This kind of curve was markedly different from that of normal surrounding liver parenchyma, which presented a curve of Type 2, characterized by fast enhancement followed by slowly decaying plateau, with mean TTP=39.619, mean ME%= 208.571 and mean MS=19.380. The combination of diffusion and perfusion MRI may supply additional tools to diagnose FNH, providing information concerning the soft-tissue characteristics and the vascularity (perfusion and angio-genetic activity) of the lesion, respectively [4,9]. These findings may be particularly important for the diagnosis of non-classic FNH (about 20% of cases, that lack almost one of the typical features) [1]. In our study, we observed five non-classic lesions in the 21 pathologically verified FNHs and we did identify no significant difference between the classic and non-classic FNHs at diffusion and perfusion MRI. This study has several limitations. First, our study group is relatively small, so further studies with a larger

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Fig. 4. (A-D) A 28-year-old woman with incidental focal liver lesion identified (in the right hepatic dome) at abdominal ultrasound. MR study demonstrates two hepatic lesions, as showed on diffusion- weighted image (A). ADC value of the normal liver and both FNHs was calculated on ADC map (B), resulting 1.52×10−3 mm2/s, 1.57×10−3 mm2/s and 1.53×10−3 mm2/s, respectively. MR perfusion shows a contrast-enhanced LAVA image (C) obtained at the maximum enhancement and demonstrating two hypervascular lesions, both presenting on perfusion graph (D) the same shape curve: TSIC-type 1 (red and green), typical for FNH. The final diagnosis of FNH was rendered on the basis of different data including typical radiologic findings and imaging follow-up for 24 months.

sample size of pathologically-proven FNHs are needed to confirm our conclusions. Second, standardization of imaging acquisition and analysis techniques need to be addressed for the widely application of these techniques. Moreover, heavy data loading and time consuming for perfusion imaging data processing could not be ignored in most of the clinical facilities. The last but not the least limitation is the absence of a blinded comparison with other hypervascular lesions and, in particular, hepatocellular adenoma. Work is ongoing to determine the sensitivity and specificity of combined DWI and PWI in this differential diagnosis. In conclusion, FNHs of the liver showed typical diffusion and perfusion MRI characteristics in all cases. On the ADC map, we could get similar value between the FNHs and the background parenchyma; on the perfusion imaging, FNHs showed a different pattern distinguished from the background liver. However, further studies are needed to establish the potential role of combined DWI and PWI in

differentiating FNH from other avidly arterially enhancing lesions such as adenoma, hepatocellular carcinoma, and hypervascular metastases.

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