Reliable diagnosis of liver focal nodular hyperplasia by a combination of T2 weighted signal and three diffusion magnetic resonance metrics of diffusion-derived ‘vessel density’, slow diffusion coefficient, and apparent diffusion coefficient: a validation study of two centers’ data

Introduction

Liver focal nodular hyperplasia (FNH) is a nodule composed of benign-appearing hepatocytes commonly occurring in a liver that is otherwise histologically normal or nearly normal (1). Edmondson (1) introduced the term FNH in 1958. In 1995, the International Working Party classified FNH as regenerative lesion, in contrast to adenoma which is known as a neoplastic lesion (2). Histologically, FNH is hyperplastic growth of morphologically normal hepatocytes, without normal development of the portal tract. A central fibrovascular scar and radiating fibrous septa contain large malformed feeder arteries and branches (3). Vascular malformation and vascular injury have been suggested as the underlying mechanism (4). FNH is the second most common benign liver tumor after hemangioma and has a reported prevalence of 0.9%. The male-to-female ratio is 1:8, and the tumors occur in relatively young patients. Approximately 20% of the patients have multiple FNH lesions (5). FNH lesions have no malignant potential, and hemorrhage and rupture are rare. Asymptomatic FNH requires no treatment or imaging follow-up in patients with no known malignancy or underlying liver disease. In symptomatic cases, transarterial embolization may be considered. Distinction between FNH and other hypervascular liver lesions, such as hepatocellular carcinoma (HCC), metastases (Mets), and hepatocellular adenoma (HCA), is critical to ensure proper treatment.

On magnetic resonance imaging (MRI), typically, FNH is iso- or hypointense on T1-weighted images (T1WIs), slightly hyper- or isointense on T2-weighted images (T2WIs), and has a hyperintense central stellate scar on T2WI. FNH demonstrates intense enhancement during the arterial phase of gadolinium-enhanced imaging, with decay in the subsequent phases, becoming isointense to the adjacent liver parenchyma, and enhancement of the central scar during later phases. Currently, the standard of diagnosis for FNH is based on the application of hepatobiliary contrast agents, including gadoxetic acid (Gd-EOB-DTPA-Primovist; Bayer, Berlin, Germany) or gadobenate dimeglumine (Gd-BOPTA-MultiHance; Bracco, Milan, Italy). Hepatobiliary phase imaging is typically performed at 20 minutes after administration of Gd-EOB-DTPA or 120 minutes after administration of Gd-BOPTA. FNH, as a hyperplastic growth of hepatocytes, almost always shows hepatobiliary phase uptake, whereas lesions of nonhepatocellular origin, such as Mets, do not take up hepatobiliary contrast agents and appear hypointense during the hepatobiliary phase. Other lesions of hepatocellular origin, such as HCC and HCA, are also usually hypointense during the hepatobiliary phase (3,6-12). FNH presents greater density of functioning hepatocytes than a healthy liver parenchyma, in association with abnormal bile ducts which do not communicate with greater bile ducts, with consequential slower biliary excretion as compared with the surrounding liver. Therefore, FNH presents contrast uptake greater or equal to the adjacent liver parenchyma in the hepatobiliary phase (7).

Recently, we introduced two new diffusion-weighted imaging (DWI) metrics. Liver micro-vessels, including sub-pixel vessels, show high-signal when there are no motion probing gradient (b=0 s/mm²) and low-signal when even very low b-values (such as b=2 s/mm²) are applied. Thus, the signal difference between images when the motion probing gradient is ‘off’ and ‘on’ reflects the extent of tissue vessel density in the physiological sense, and we term this as diffusion-derived ‘vessel density’ (DDVD) (13,14). Slow diffusion coefficient (SDC) was proposed to measure tissue slow diffusion (15). In its basic form, SDC is derived from a high b-value DWI image (typically with b-value of 400–600 s/mm²) and a higher b-value DWI image (typically with b-value of 700–900 s/mm²). SDC was initially tested with its application for the liver and spleen. With the conventional apparent diffusion coefficient (ADC) approach, the spleen has been reported to have a much lower ADC than liver, HCCs have a lower ADC than liver parenchyma, and simple liver cysts have a higher ADC than liver hemangiomas. On the other hand, with SDC analysis, Xu et al. (15) reported that the spleen has faster diffusion than liver, HCCs have faster diffusion than liver parenchyma, and liver hemangiomas have faster diffusion than simple liver cysts. The liver and spleen have a similar amount of blood perfusion, the spleen is waterier than the liver, and the spleen tissue has a higher contrast-enhanced computed tomography (CT) extracellular volume fraction than the liver (16,17). HCCs are mostly associated with increased blood supply and increased proportion of arterial blood supply and with edema. Perfusion CT also shows that HCCs have a shorter mean transit time (MTT) than adjacent liver parenchyma. It is more reasonable with SDC results that spleen and HCC have faster diffusion than liver parenchyma. Due to the ‘flushing’ of blood flow inside the hemangioma, it is also more reasonable with SDC results that the diffusion of hemangioma liquid is faster than the more ’static’ liquid of the cysts.

If we apply four b-values (e.g., b-values of 0, 10, 500, 800 s/mm²) for DWI, then three diffusion metrics, namely, DDVD (e.g., using b-values of 0, 10 s/mm²), and SDC (e.g., using b-values of 500, 800 s/mm²), and ADC (e.g., using b-values of 0, 800 s/mm²), can be generated. In its principle, the scan time of the four b-values scheme will be similar to the conventional ADC protocol scanned twice, though a higher number-of-excitation (NEX) is often desirable so to increase the signal-to-noise ratio. A combination of these three DWI metrics may offer clinically meaningful classification for many diseases. For example, in a recent study of 63 patients with diffuse gliomas [30 isocitrate dehydrogenase (IDH)-mutant and 33 IDH-wildtype], SDC separated IDH-mutant and IDH-wildtype tumors with an area under the receiver operating characteristic curve (AUROC) of 0.828. A combination of SDC, DDVD, and ADC separated IDH-mutant and IDH-wildtype tumors with an AUROC of 0.897 (18). Yao et al. (19) studied 24 pleomorphic adenomas, 16 Warthin’s tumors, and 14 malignant tumors (MTs). The ratio of a tumor diffusion metric measure to a contra-lateral tumor-free parotid gland tissue diffusion metric measure was obtained, resulting in ADC ratio, SDC ratio, and DDVD ratio. Separation of benign tumors (pleomorphic adenomas and Warthin’s tumors) against MT by ADC ratio alone, by a combination of ADC ratio and SDC ratio, and by a combination of ADC ratio, SDC ratio, and DDVD ratio had an AUROC of 0.7393, 0.8018, and 0.8054, respectively. Hu et al. reported that a combination of DDVD and SDC offers an accuracy of >95% in separating liver hemangioma and liver solid mass-forming lesions (20).

We have recently reported that liver FNH quantitatively has a lower DDVD value than liver MT (21). Moreover, in a study of 13 cases of FNH and 56 liver MT cases [HCC n=40, Met n=12, intrahepatic cholangiocarcinoma (ICC) n=4], a score scheme termed ‘LiverMss-FNH’ (shortened as LiverMss in the following texts) was proposed to evaluate liver mass (22). LiverMss integrates features of T2WI signal, DDVD signal, SDC signal, ADC signal, and the existence of lesion stellate scar on T2WI (22). Liver FNHs tend to have a lower SDC signal than liver MT. FNH had a median LiverMss of 4.0, while liver MT had a median LiverMss of 0.75. In total, 69.2% (9/13) of the FNH had LiverMss ≥4.0, and 89.3% (50/56) of the MT had LiverMss ≤1.5. A LiverMss ≥4.0 can strongly suggest the diagnosis of FNH (Figure 1) (22). By additional data acquired from two different hospitals [The Second Hospital of Nanjing and (center 1) and The Fifth Affiliated Hospital of Anhui Medical University (center 2)], the current study aims to validate these earlier results (22).

Figure 1 Separation of 13 lesions of FNH and 56 MT cases (HCC n=40, Met n=12, ICC n=4) by LiverMss. Cases 1, 3, and 5 (marked dark blue) had apparent liver cirrhosis signs. Cases 2–6 had signs suggesting the possibility of malignancy, while cases 7–9 all had signs suggesting FNH. Case 6 (blue thin arrow) was a case of ICC with biliary duct dilation. Cases 4 and 10 had a degree of respiration motion artifact (yellow thin arrow). Blue dots denote cases with liver cirrhosis signs visible on MRI or a combination of apparent splenomegaly and ascites seen on MRI. Reused with permission from (22). FNH, focal nodular hyperplasia; HCC, hepatocellular carcinoma; ICC, intrahepatic cholangiocarcinoma; Met, metastasis; MRI, magnetic resonance imaging; MT, malignant tumor.

Methods

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. All imaging data were prospectively acquired with institutional ethical approvals and with informed consent obtained from individual participants. The liver DWI was based on a single-shot spin-echo type echo-planar sequence with free breathing, and the patients were instructed to adopt shallow regular free breathing (23,24). The default spectral pre-saturation technique was used for fat suppression. In center 1, liver imaging was performed with a 3.0-T magnet (General Electric, GE Healthcare, Milwaukee, WI, USA). DWI images with b-values of 0, 10, 600, 800 s/mm² (all NEX =6) were acquired for this study. The time of repetition (TR) was 2,700 ms, and the time of echo (TE) was 82 ms. Other parameters included slice thickness =6 mm, inter-slice gap =1 mm, and pixel size =3 mm × 3 mm. In center 2, liver imaging was performed with a 3.0-T magnet (Vida Magnetom, Siemens Healthineers, Erlangen, Germany). DWI images with b-values of 0 (NEX =2), 10 (NEX =2), 400 (NEX =4), 600 (NEX =4) s/mm² were acquired for this study. The TR was 5,500 ms, and the TE was 80 ms. Other parameters included slice thickness =6 mm, inter-slice gap =1.2 mm, and pixel size =3 mm × 3 mm. Initially, 72 patients were enrolled, and among them, two patients had unacceptable images thus excluded (one with severe motion artifacts and one with a very small lesion; see the “Results” section). In total, 12 FNH cases, 39 HCC cases, 10 ICC cases, and 9 Mets were included and analyzed (Figure 2). Origins of Mets included: two cases from the lung, two cases from the pancreas, one case from the uterus, two cases from the stomach, one case from the rectum, and one case from the gallbladder. Two FNH lesions had histopathological diagnosis, and the remaining 10 lesions were diagnosed with typical findings of hepatobiliary contrast agent-enhanced MRI and follow-up. All HCC and ICC cases had histopathological diagnosis. The diagnosis of Mets was based on histopathology or a combination of complete patient history and typical imaging features.

Figure 2 Patient enrollment chart. After exclusion of two FNH cases, 12 FNH cases and 58 MT cases were analyzed. Ages are presented as median (range). Center 1: The Second Hospital of Nanjing; center 2: The Fifth Affiliated Hospital of Anhui Medical University. F, female; FNH, focal nodular hyperplasia; HCC, hepatocellular carcinoma; ICC, intrahepatic cholangiocarcinoma; M, male; Met, metastasis; MT, malignant tumor; yrs, years.

DDVD weighted image was calculated from b=0 and b=10 s/mm² images, and derived from the equation (13,14):

DDVD=S(b0)ROIarea0−S(b10)ROIarea10(unit:au/pixel)[1]

where ROIarea0 and ROIarea10 refer to the number of pixels in the selected region-of-interest (ROI) on b=0 and b=10 s/mm² DWI, respectively. Sb0 refers to the measured sum signal intensity within the ROI when b=0, and Sb10 refers to the measured sum signal intensity within the ROI when b=10 s/mm². The unit au/pixel refers to an arbitrary unit/pixel. If we consider a pixel to be an individual ROI, the DDVD map can be constructed pixel-by-pixel with this same principle.

SDC was derived from equation (15):

SDC=S(b1)−S(b2)b2−b1(unit:au/s)[2]

where b₁ and b₂ refer to a high b-value and a higher b-value, respectively; S(b₁) and S(b₂) denote the image signal intensity acquired at the high b-value and the higher b-value, respectively. For center 1 data, SDC was calculated with b=600 and b=800 s/mm² images. For center 2 data, SDC was calculated with b=400 and b=600 s/mm² images.

ADC was calculated according to:

ADC=ln[S(b1)/S(b2)]b2−b1(unit:mm2/s)[3]

where b₂ and b₁ refer to the high b-value (i.e., 600 or 800 mm²/s in this study) and low b-value, respectively (i.e., 0 mm²/s in this study), where S(b₂) and S(b₁) denote the image signal intensity acquired at the high b-value and low b-value, respectively.

The scoring and image analysis were conducted by three readers in consensus (a specialist radiologist and two senior radiology trainees). As described earlier (22), a liver semi-quantitative (SQ) scoring was conducted on: (I) T2WI; (II) DDVD map; (III) SDC map; and (IV) ADC map. Relative to the adjacent liver signal, a liver lesion signal was to five SQ categories: low-signal (scored as ‘0’), iso-signal (scored as ‘1’), slightly high-signal (scored as ‘1.5’), high-signal (scored as ‘2’), or markedly high-signal (scored as ‘3’). With reference to the background liver signal, ‘high-signal’ was generally the expected spleen signal on T2WI and SDC map; ‘markedly high-signal’ was usually close to the liquid or blood vessel signal. When it was difficult to sign a score of ‘2’ or ‘3’, an additional score of ‘2.5’ (higher-signal) was assigned (which may be slightly higher than the kidney signal). On T2WI, absolute iso-signal of a lesion rarely exists; thus, being consistent with the literature, faintly higher signal is assigned a score of ‘1’. The scoring was based on the dominant solid part of the lesion. In cases of multiple Mets, the largest lesion was scored. All the FNH cases were singular in this study.

Mostly typically, FNH is faintly high-signal (sometimes described as iso-signal in literature) on T2WI (3,6,25), iso-signal on DDVD map (21,22), slightly high-signal on SDC map (22), iso-signal or slightly high-signal on ADC map (25-27). On the other hand, T2WI high-signal favors the diagnosis of MT, and typically a liver MT has a lower ADC relative to adjacent liver parenchyma. Our earlier study noted that lesion being not high-signal on T2WI, being iso-signal on DDVD, being not high-signal on SDC, being not low-signal on ADC, and the existence of stellate scar had odds ratios of 49.1, 45.8, 30, 8.5, and 13.3, respectively, favoring the diagnosis of FNH (22). A stellate scar favors the diagnosis of FNH; however, it can be sometimes difficult to differentiate between FNH stellate scar and MT central necrosis. The same as our earlier report, we applied a scoring scheme termed ‘LiverMss-FNH’ this study (Figure 3): the lesion on T2WI being not high-signal was assigned a score ‘1’ favoring the FNH diagnosis (i.e., signal score ≤1.5; otherwise scored 0); the lesion being ‘homogenously’ iso-signal on DDVD map, except the high-signal due to stellate scar or a peripheral rim which is often associated with respiration (Figure 4), was assigned a score ‘1.5’ favoring the FNH diagnosis (otherwise scored 0); the lesion on SDC map being not high-signal was assigned a score ‘1’ favoring the FNH diagnosis (i.e., signal score ≤1.5; otherwise scored 0); the lesion on ADC map being not low-signal was assigned a score ‘0.5’ favoring the FNH diagnosis (i.e., signal score ≥1; otherwise scored 0); the existence of stellate scar on T2WI was assigned a score ‘0.5’ (otherwise scored 0). In the current study, practically only three grades (i.e., 0, 1, or 1.5) were assigned on ADC map. The maximum value of LiverMss was 4.5. A FNH typical in all aspects should be: (I) T2WI slightly high-signal but not high-signal; (II) DDVD iso-signal; (III) SDC slightly high-signal but not high-signal; (IV) ADC iso-signal or slightly high-signal but not low-signal; and (V) existence of a stellate scar (22).

Figure 3 LiverMss scoring scheme. T2WI not high-signal, DDVD iso-signal, SDC not high-signal, ADC not low-signal, and the existence of stellate scar appearance on T2WI favor the diagnosis of FNH for a liver mass. The maximum LiverMss is 4.5. Modified with permission from (22). ADC, apparent diffusion coefficient; DDVD, diffusion-derived ‘vessel density’; FNH, focal nodular hyperplasia; SDC, slow diffusion coefficient; SQ, semi-quantitative; T2WI, T2-weighted image.

Figure 4 Illustration for DDVD signal scoring for FNH. Case A (A1,A2) is a case of typical homogenous iso-signal FNH lesion (arrows), the lesion is almost invisible on DDVD map. Case B (B1,B2) is a case of typical homogenous iso-signal FNH lesion (arrows), the lesion is almost invisible on DDVD map. However, there is high-signal partial ring (asterisks) around the FNH lesion which was caused by the slight mismatch of position between b=0 and b=2 s/mm² images to construct the DDVD map. Case C (C1-C3) also has a high-signal ring (asterisks) around the FNH lesion (arrow) on both DDVD maps (derived from b=0 and b=10 s/mm² images), and the ADC map (derived from b=0 and b=800 s/mm² images). We read this lesion has ‘homogeneous’ iso-signal on both DDVD map and the ADC map. Note that being ‘homogeneous’ is not absolutely homogeneous, it is that the lesion’s signal texture is similar to the adjacent liver’s signal texture. Case D (D1,D2) also has a high-signal ring (asterisks) around the FNH lesion (arrows) on DDVD map (derived from b=0 and b=10 s/mm² images). Images of cases A, B, and D are reused with permission from (21). Images of case C reused with permission from (22). ADC, apparent diffusion coefficient; DDVD, diffusion-derived ‘vessel density’; DWI, diffusion-weighted imaging; FNH, focal nodular hyperplasia; T2WI, T2-weighted image.

Following our earlier results that we need LiverMss ≥4.0 to define confidently a lesion to be FNH (22), if one (or more) of the DWI metric maps was of insufficient quality (for example due to respiration motion), we could also use a ‘subtraction approach’: the lesion on T2WI being high-signal was assigned a score ‘−1’; the lesion being not ‘homogenously’ iso-signal on DDVD map was assigned a score ‘−1.5’; the lesion on SDC map being high-signal was assigned a score ‘−1’; the lesion on ADC map being low-signal was assigned a score ‘−0.5’, the absence of stellate scar was assigned a score ‘−0.5’. If the sum of the negative scores is ≤−1.0 (i.e., LiverMss ≤−3.5), then a diagnosis of FNH could not be made confidently.

Statistical analysis was performed using GraphPad Prism (GraphPad Software, San Diego, CA, USA).

Results

Two HCC cases with apparent intralesional hemorrhage were excluded from SQ scoring.

Six MT cases (median size: 1.4 cm, range: 0.8–2.0 cm) had LiverMss ’subtraction approach’, with four cases scored ‘−3’, one case scored ‘−2.5’, and one case scored ‘−2.0’, respectively; thus, their LiverMss would ≤1.5 (n=4), ≤2.0 (n=1), ≤2.5 (n=1), respectively, and these cases were unlikely to be FNH.

With the 12 FNH (median size: 3.5 cm, range: 1.4–5.8 cm) and 50 MT (median size: 5.6 cm, range: 1.6–16.9 cm) evaluated with the SQ scoring scheme, the distribution of SQ scores of FNH and MT for each sign is shown in Figure 5. The odds ratio results for each SQ sign are shown in Table 1, which generally support our earlier results (22).

Figure 5 Percentage distribution of lesion SQ scores on T2WI (A), on SDC map (C), and ADC map (D), lesion being iso-intensity or not iso-intensity (B), and existence (+) or nonexistence (−) of stellate scar appearance (E). ADC, apparent diffusion coefficient; FNH, focal nodular hyperplasia; MT, malignant tumor; SDC, slow diffusion coefficient; SQ, semi-quantitative; T2WI, T2-weighted image.

LiverMss results for FNH (n=12) and for MT (n=50) are shown in Figure 6. Seventy-five percent (9/12) of the FNH had LiverMss ≥4.0. Two of the FNH lesions scored 3.0 had only one signal sign being untypical of FNH, and one FNH lesion scored 3.0 had very heterogenous signals (Figure 7A). Six out of seven MT cases scored ≥2.5 had liver cirrhosis as evident on MRI, and another case had embolization treatment. The remaining MT (43/50) all had LiverMss ≤2.0.

Figure 6 Separation of 12 lesions of FNH and 50 MT cases (HCC n=35, ICC n=10, Met n=5) evaluated with LiverMss (arrows: treated cases). MT cases of 1–4, 6, 7 all had MRI appearance of cirrhosis (denoted with dark blue color; cases 1, 2, 6 have apparent ascites; case 2 also has apparent pleural effusion). Case 1 was under anti-cancer immunotherapy, and cases 3 and 5 had received embolization treatment. Blue dots denoted cases with liver cirrhosis signs visible on MRI or a combination of apparent splenomegaly and ascites seen on MRI. ADC, apparent diffusion coefficient; DDVD, diffusion-derived ‘vessel density’; F, female; FNH, focal nodular hyperplasia; HCC, hepatocellular carcinoma; ICC, intrahepatic cholangiocarcinoma; M, male; Met, metastasis; MRI, magnetic resonance imaging; MT, malignant tumor; SDC, slow diffusion coefficient; T2WI, T2-weighted image; yrs, years.

Figure 7 Three cases of FNH. Case A (A1-A4) is the case 10 shown on Figure 6. This is a quite atypical case with heterogeneous internal signals (arrows). A diagnosis of FNH could not be made based on non-contrast MRI. While the primary surgical pathology diagnosis of case A is FNH, a note was added in the pathological report that well-differentiated HCC could not be excluded. The case B (B1-B4) and case C (C1-C4) have typical FNH signal (arrows), though case C does not show a stellate scar. Red asterisk on (B2) denotes an artificial high-signal due to respiratory motion. ADC, apparent diffusion coefficient; DDVD, diffusion-derived ‘vessel density’; FNH, focal nodular hyperplasia; HCC, hepatocellular carcinoma; MRI, magnetic resonance imaging; SDC, slow diffusion coefficient; SQ, semi-quantitative; T2WI, T2-weighted image.

Visualizations of the difference between FNH and MT, and the SQ score results, are shown in Figures 7-14. T2WI of the two excluded cases are shown in Figure 15.

Figure 8 One case of HCC (A1-A5; case 1 in Figure 6) and one case of ICC (B1-B5; case 6 in Figure 6) showing DDVD iso-signal. The HCC lesion (arrows) shows faintly lower ADC (A1-A5). The HCC case had liver cirrhosis and ascites and was under immunotherapy. Except for the lesion does not have stellate scar, the signals are very similar to FNH. The ICC lesion (arrows) shows iso-signal on DDVD and SDC (B1-B5); however, the lesion shows high signal on T2WI (with spleen signal regarded as high signal) and low signal on ADC. (B2) Liver parenchyma has micro-nodular appearance consistent with liver cirrhosis. ADC, apparent diffusion coefficient; DDVD, diffusion-derived ‘vessel density’; FNH, focal nodular hyperplasia; HCC, hepatocellular carcinoma; ICC, intrahepatic cholangiocarcinoma; SDC, slow diffusion coefficient; SQ, semi-quantitative; T2WI, T2-weighted image.

Figure 9 Two cases of liver FNH [yellow arrows in case A (A1-A4) and case B (B1-B4)]. Though without a central stellate scar, the case B has typical FNH signal, scored 1, 1, 1 and 1 on T2WI, DDVD, SDC, and ADC, respectively. ADC, apparent diffusion coefficient; DDVD, diffusion-derived ‘vessel density’; FNH, focal nodular hyperplasia; SDC, slow diffusion coefficient; SQ, semi-quantitative; T2WI, T2-weighted image.

Figure 10 Four cases of liver FNH [yellow arrows in case A (A1-A4), case B (B1-B4), case C (C1-C4), and case D (D1-D4)]. Though without a central stellate scar, the case A has typical FNH signal, scored 1.5, 1, 1.5, and 1 on T2WI, DDVD, SDC, and ADC, respectively. (B2) The FNH lesion has slightly higher DDVD value (thin white arrows), with a central scar showing artificial high-signal (due to slight displacement between b=0 and b=10 s/mm² images). (C2,D2) The lesion (thin white arrows) has an artificially high-signal ring (asterisks). An adjacent slice DDVD map is inserted in (C2,D2). Thin white arrow in (D3) shows central stellate scar high-signal. ADC, apparent diffusion coefficient; DDVD, diffusion-derived ‘vessel density’; FNH, focal nodular hyperplasia; SDC, slow diffusion coefficient; SQ, semi-quantitative; T2WI, T2-weighted image.

Figure 11 Three cases of liver HCC [yellow arrows in case A (A1-A4), case B (B1-B4), and case C (C1-C4)]. Case A is a typical case for MT signal, being high on T2WI, DDVD, and SDC, and low on ADC. The case B is difficult to score for DDVD map, and we graded the lesion as score 1.5, note that the lesion has high SDC signal and low ADC (thus inconsistent with FNH). The border of the case B lesion has a ring signal on DDVD map and SDC map which are not reliable. ADC, apparent diffusion coefficient; DDVD, diffusion-derived ‘vessel density’; FNH, focal nodular hyperplasia; HCC, hepatocellular carcinoma; MT, malignant tumor; SDC, slow diffusion coefficient; SQ, semi-quantitative; T2WI, T2-weighted image.

Figure 12 Two cases of HCC [case A (A1-A6): a male aged 82 years; case B (B1-B6): a male aged 61 years]. T1WI (A1,B1) and T2WI (A2,B2) show intra-tumoral hemorrhage. It is likely that the hemosiderin deposition in the tumor caused T2* effect and the signal void on DWI b=0 mm²/s image (A3,B3) and DDVD map (A4,B4, asterisks). We consider that the signal on SDC and ADC might also not be reliable. However, the high lesion signal on SDC may suggest malignancy. Note that hemorrhage is very uncommon among FNH. ADC, apparent diffusion coefficient; DDVD, diffusion-derived ‘vessel density’; DWI, diffusion-weighted imaging; FNH, focal nodular hyperplasia; HCC, hepatocellular carcinoma; SDC, slow diffusion coefficient; T1WI, T1-weighted image; T2WI, T2-weighted image.

Figure 13 Two cases of liver Mets [yellow arrow in case A (A1-A4), and yellow and white arrows in case B (B1-B4)]. Both cases A and B had ascites and multiple liver mass lesions. Only one Mets lesion in case B is scored (yellow arrow). The lesion denoted with white arrow is not scored. ADC, apparent diffusion coefficient; DDVD, diffusion-derived ‘vessel density’; Met, metastasis; SDC, slow diffusion coefficient; SQ, semi-quantitative; T2WI, T2-weighted image.

Figure 14 One case (A1-A4) of ICC (arrow) showing DDVD iso-signal and SDC higher-signal (score: 2.5). According to our preliminary experience, the DDVD and SDC appearance of this case is typical for ICC. ICC also commonly shows high-signal on ADC. ADC, apparent diffusion coefficient; DDVD, diffusion-derived ‘vessel density’; ICC, intrahepatic cholangiocarcinoma; SDC, slow diffusion coefficient; SQ, semi-quantitative; T2WI, T2-weighted image.

Figure 15 Two cases of FNH excluded from analysis (T2WI). The lesion in (A, arrow) is close to the diaphragm and the DWI images suffered from substantial respiratory motion. The lesion in (B, arrow) is too small and the signal on diffusion metric maps could not be ascertained. DWI, diffusion-weighted imaging; FNH, focal nodular hyperplasia; T2WI, T2-weighted image.

Discussion

Our recent study suggested that a LiverMss ≥4.0 can strongly suggest the diagnosis of FNH for a liver mass (22); the current study further validates this result. In this study, 75% (9/12) of the FNH had LiverMss ≥4.0, and two of the FNH lesions scored 3.0 had only one signal sign being untypical of FNH. If we exclude the six MT cases with liver cirrhosis and the other treated case, all the MT cases had LiverMss ≤2.0. Therefore, LiverMss ≥3.0 suggests the possibility of a liver mass being FNH, and LiverMss ≥4.0 can strongly suggest the diagnosis of FNH (Figure 6).

Because FNH is mainly composed of hepatocytes, it appears similar to the background liver on unenhanced images. With hepatocyte-specific contrast agents, FNH, as a hyperplastic growth of hepatocytes, almost always shows hepatobiliary phase uptake. The utilization of hepatobiliary contrast agents increases the MRI accuracy, reducing the necessity of invasive diagnostic procedures. However, hepatocyte-specific contrast agents incur additional costs and scan time. It will be highly relevant if the majority of FNH cases, even though not all cases, can be confidently diagnosed with non-contrast MRI.

In our earlier study, 89.3% (50/56) of the MT had LiverMss ≤1.5. Among MT cases, an HCC patient with liver cirrhosis had the highest LiverMss of 3.5, and two additional HCC patients with liver cirrhosis had LiverMss of 2.5 (Figure 1) (22). In the current study, six out of seven MT cases with the highest LiverMss had liver cirrhosis. We suggest that apparent liver cirrhosis background may lead to inaccuracy for LiverMss scoring. Liver cirrhosis is associated with higher extracellular water content (28-31) and longer T2 relaxation of the liver parenchyma (32-35). Extracellular fluid excess is a common condition in advanced liver cirrhosis patients with ascites. With a 1.5-T scanner, Mesropyan et al. (34) reported that, compared with those of healthy controls, cirrhotic livers with portal hypertension had longer T2 (53.72±7.56 vs. 48.58±8.41 ms) and higher extracellular volume fraction values (45%±18.55% vs. 26.14%±2.31%). Compared with healthy controls, spleen in liver cirrhosis patients also had longer T2 (113.17±18.72 vs. 98.83±11.69 ms) and extracellular volume fraction values (42.53%±6.29% vs. 25.82%±2.40%). Similar trends have been described by Özyurt et al. (35), though with livers of milder fibrosis severity. Liver fibrosis and cirrhosis have been measured to be with lower liver ADC (36-38), and sometimes with higher spleen ADC (39-43). In a patient study, Subbiah et al. reported that the Model for End-Stage Liver Disease (MELD) score is negatively correlated with liver ADC but positively with spleen ADC (41,43). These will have complications for LiverMss (Table 2). For example, a brighter background T2WI liver and spleen may lead to the lesion appears relatively ‘less bright’. Since liver cirrhosis is associated with a higher ‘pre-test’ probability of HCC for a liver mass, we advocate a caution for application of LiverMss on apparently cirrhotic liver background (however, milder liver fibrosis is inevitably common among HCC patients). LiverMss cannot be applied to diagnose FNH on apparently cirrhotic liver background, but may be applied to diagnose MT (Figures 1,6, Table 2).

The current study is dealing with research scenario, and we are in the process of building our experience for LiverMss assessment. In practice, likely the ’subtraction approach’ may be easier to apply. For example, if the lesion is not homogenously iso-signal on DDVD map, or if the lesion shows SDC high-signal and without stellate scar, then the LiverMss will be ≤3.5, and a firm diagnosis of FNH cannot be made.

An important limitation of our studies is that we have not (yet) included HCA patients. FNH is a benign lesion that does not require any intervention, while adenoma presents the risk for malignization, necrosis, and bleeding. Adenomas >4 cm and those with symptoms related to intratumoral hemorrhage constitute surgical indication. Based on the currently available data (44-48), we may postulate the potential non-contrast DWI differences between FNH and HCA. HCAs occur in women of childbearing age in the Western population. Prolonged use of oral contraceptives is a significant risk factor, increasing the incidence by 30–40-fold. HCAs in the Asian populations exhibit distinct demographic and clinical characteristics (44). The age distribution is similar (mean age of 35–39 years); however, 39–70% of patients are males in Asia, compared with 0–16% in the Western population (44). Hepatocyte nuclear factor 1α-inactivated HCA (HHCA) and inflammatory HCA (IHCA) are the two most common subtypes in the Western population (accounting for 30–45% of cases each). In contrast, IHCA, accounting for 38–50% of cases, is the most prevalent subtype in the Asian population, followed by β-catenin-activated HCA (β-HCA), which accounts for 9–26% of cases. HHCAs are far less prevalent in the Asian population, representing only 7–16% of cases (44). IHCAs are associated with a low risk of malignant transformation or bleeding. IHCA shows an absence (suggesting no intralesional steatosis) or only focal signal dropout on out-phase image, and is associated marked hypersignal on T2WI, with a stronger signal in the outer part of the lesions (the so called ‘atoll sign’), correlating with sinusoidal dilatation areas; and strong arterial enhancement, with persistent enhancement in the portal venous and delayed phases (45,46). HHCA is commonly associated with intralesional steatosis and shows diffused signal dropout on out-of-phase sequence. Homogeneous intra-tumoral fat, the hallmark imaging feature of this subtype, is observed in 78–100% of cases (45,46). On MR, the imaging features of β-HCA are not specific, and it can be challenging to differentiate these tumors from HCC or, rarely, FNH. Intralesional fat or hemorrhage is very uncommon for FNH. Yang et al. (47) used ultrasound-based microvascular imaging (US-MVI) morphologic features to categorize microvascular architecture patterns for liver masses. Morphological features of vessels were divided into six patterns: (I) no signal; (II) dot-like or linear flow signal; (III) nodular rim signal; (IV) spoked-wheel flow signal; (V) residual-root or crab-claw flow signal; and (VI) irregular blood flow. I–IV patterns were defined as hypovascular supply, while V and VI patterns were defined as hypervascular supply. According to Yang et al. (47), with US-MVI method, all their 12 cases of FNH were defined as ‘hypovascular supply’, 9 of their 35 HCC cases were defined as ‘hypovascular supply’ and 26 of HCC cases were defined as ‘hypervascular supply’, while 5 of their 8 HCA cases were defined as ‘hypovascular supply’ and 3 of their 8 HCA cases were defined as ‘hypervascular supply’. According to Qiu et al. (48), with a similar methodology, all their 5 cases of FNH (100%) were defined as ‘hypovascular supply’, while 7 of their 24 HCC cases were defined as ‘hypovascular supply’ and 17 of HCC cases were defined as ‘hypervascular supply’ (Table 3). Note that, with the US-MVI method used by Yang et al. (47) and Qiu et al. (48), the ‘hypovascular supply’ was not of that compared to liver parenchyma. We can hypothesize that IHCA exhibit a high-signal on DDVD map, and its high-signal on T2WI, the ‘atoll sign’, and possible high SDC signal allow them to be separated from FNH.

This study has a number of other limitations. The number of FNH (n=12) remained. The same as our earlier study, without breathhold data acquisition, misalignment between b=0 and b=10 s/mm² images, or between two high b-value images, or between b=0 and b=600 (or 800) s/mm² images, can lead to erroneous DDVD/SDC/ADC signals. It is anticipated that artificial intelligence-powered accelerated data reconstruction will enable single-breathhold imaging of DDVD and SDC with sufficient signal-to-noise ratio in the future. This study did not differentiate between the three types of MTs (i.e., HCC, Mets, and ICC). We empirically noted that ICC mass typically would show higher-signal on SDC map (SQ score: 2.5, probably due to the accumulation of microscopic mucin drops), and some ICC show iso-signal on DDVD map which is consistent with the ultrasound MVI features of ICC listed in Table 3. The usefulness of these appearances for diagnostic differentiation for ICC needs to be confirmed in the future with more patient data. We have earlier noted that markedly high-signal on both b=0 s/mm² DWI and DDVD map favoring the diagnosis of Mets (21). As Mets are more likely associated with a longer T2 value and higher perfusion than those of HCC (21), and HCC is commonly associated with various degrees of liver fibrosis, the overall separation overall between FNH and Mets will be easier than the separation between FNH and HCC (Figure 16). Finally, SQ scoring is always associated with a certain degree of subjectivity. In this study, a consensus approach was adopted for the SQ scoring, and inter-reader agreement was not assessed. This was due to the fact that the authors felt we were still at a learning curve on how to better interpret liver mass DDVD and SDC signals. We will prepare an atlas to standardize liver mass DDVD and SDC signals reading and make the atlas available externally.

Figure 16 LiverMss separation of FNH and Mets. Data are from this study and from reference (22). Out of nine Mets cases in this study, four had subtraction score (denoted with blue dots), and these scores should be read as ‘no higher than this score’. FNH, focal nodular hyperplasia; Met, metastasis.

Conclusions

In conclusion, this study further supports that LiverMss offers practical diagnostic separation of liver FNH and MT for the majority of patients. Two-thirds of liver FNH, as long as they are of reasonable size and the images are not degraded by respiratory motion, can be diagnosed by LiverMss without the need for contrast agent administration. LiverMss ≥3.0 suggests the possibility of a liver mass being FNH, and LiverMss ≥4.0 can strongly favor the diagnosis of FNH. In the meantime, we advocate a caution for application of LiverMss on apparently cirrhotic livers to diagnose FNH.

Acknowledgments

None.

Footnote

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-aw-2280/dss

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-aw-2280/coif). Y.X.J.W. serves as the Editor-In-Chief of Quantitative Imaging in Medicine and Surgery. He is the founder of Yingran Medicals Ltd., which develops medical image-based diagnostics software. There is a Chinese patent pending related to this article (Y.X.J.W.). The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. All imaging data were prospectively acquired with institutional ethical approvals and with informed consent obtained from individual participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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