Hepatocellular carcinoma (HCC) is the most common primary malignant tumor of the liver and has high mortality and morbidity rates (1,2). It has been shown that the histological grade of HCC can predict long-term survival before local treatment or liver transplantation, and is an independent predictor of postoperative recurrence (3). Therefore, accurate prediction of histological grade is critical to clinical decision-making and prognosis. Magnetic resonance imaging (MRI) has been used for the grading of HCC in the last 20 years. The application of MRI in HCC grading has developed rapidly, in which the most important and widely used is diffusion-weighted imaging (DWI). Several studies showed that the apparent diffusion coefficient (ADC) values from DWI can improve the value of MRI in grading of HCC (4-6). In general, lower ADC values are predictive of worse histological grades of HCCs. However, the ADC value indirectly reflects the histological grade of the tumor by reflecting the movement and diffusion of water molecules between the tumor tissues, and it does not reflect the material changes in the tumor parenchyma. In addition, universally accepted consensus about the DWI sequence appropriate choice of b values could not be reached (7), so that the accuracy of the ADC values from DWI in grading HCC is restricted. Therefore, it is essential to find a novel and reliable imaging method that can improve the accuracy of the grading of HCC.
In recent years, amide proton transfer-weighted (APTw) imaging has been introduced as a novel contrast mechanism in the field of molecular imaging (8,9). Based on the chemical exchange saturation transfer (CEST) principle, APTw MRI can indirectly detect cellular mobile proteins, without any exogenous contrast agent injection, through the exchange between amide protons and bulk water protons, thereby diagnosing the disease (10). APTw MRI has been applied to brain tumors, stroke (11-14), and several other diseases (15-18). A number of previous studies have successfully applied APTw MRI to detecting glioma (19,20), grading glioma (21-25), assessing tumor response to treatments (26-29), as well as predicting genetic markers in glioma (30-32). These findings caused us to seek the value of APTw MRI in predicting the histological grade of HCC. Some previous studies have shown that APTw MRI can detect liver composition changes between after-meal and overnight-fast conditions and assess the scan-rescan reproducibility in liver scanning (33,34), which confirmed the feasibility of APTw MRI in the liver. To our knowledge, no studies have been reported to evaluate the clinical potential of APTw MRI in predicting the histological grade of HCC.
In this study, we hypothesized that APTw MRI may be useful for grading HCC. This is based on the fact that high-grade HCC typically shows a higher tumor cell proliferation and cellular density, leading to overall elevated mobile protein levels, and thus, an increased APTw value (10). The aim of this study was to prospectively evaluate the potential feasibility and capability of APTw MRI to predict the histological grade of HCC, compared with widely used DWI.
This prospective study was approved by the institutional review board. All patients were required to sign the informed consents prior to being recruited. Between May 2017 and April 2018, a total of 70 consecutive patients suspected of having malignant hepatic lesions based on previous CT or ultrasonography examinations were enrolled. Thirty-eight patients were excluded for various reasons: (I) with MR contraindications (n=5); (II) with low image quality, small lesions (<1 cm), and previous HCC surgery (n=15); and (III) no pathological results, non-HCC, or the time interval between MR imaging and pathology >14 days (35) (n=18). Finally, 32 patients with pathologically confirmed HCCs were included for analysis, including 25 men and 7 women (mean age, 63.3±11.9 years; range, 30–76 years). All tumors were histologically classified from grade 1 to 4 according to the major Edmondson-Steiner grade on the final pathologic reports. We defined high-grade (Edmondson-Steiner grades 3 and 4) and low-grade (grades 1 and 2) HCCs, based on the fact that there are significant differences in survival between these two HCCs (36,37). The characteristics of the included patients are shown in Table 1.
All patients were instructed to fast for 6–8 h prior to the MR examination. The studies were carried out using a 3.0 T MR system (Achieva Intera 3.0 T, Philips Medical Systems, Best, the Netherlands) with an eight-channel, phased-array torso coil. Routine liver MRI was performed with the following sequences: breath-hold, transverse T1-weighted in-phase and opposed-phase, dual gradient-echo sequence [repetition time (TR) =241.25 ms, echo time (TE) =1.15/2.3 ms, matrix =320×320, field of view (FOV) =360 mm × 360 mm, slice thickness =6 mm, slice interval =1.5 mm]; a turbo-spin-echo sequence with coronal and transverse T2-weighted imaging (T2WI; TR =1,614 ms/1,457 ms, TE =70 ms/80 ms, matrix =512×512, FOV =360 mm × 360 mm, slice thickness =6 mm, slice interval =1.5 mm); and DWI (TR =3,000 ms, TE =54 ms, matrix =192×192, FOV =360 mm × 360 mm, slice thickness =6 mm, slice interval =1.5 mm) with two b values (0, 1,000 s/mm2). The total scanning time of the routine sequences was approximately seven minutes.
An APTw pulse sequence was applied on one T2WI slice that showed a single section through the largest cross-section of a solid tumor. APTw imaging was based on a single-shot, turbo-spin-echo sequence: TR, 4 sec; turbo-spin-echo factor, 63; field of view, 256 mm × 384 mm; reconstructed matrix 256×256; and slice thickness, 6 mm. Localized high-order shimming was performed to reduce B0 field inhomogeneity. We used a pulse-train radiofrequency (RF) irradiation (saturation duration, 200 ms ×4; inter-pulse delay, 10 ms; power level, 2 µT). The APTw imaging was performed with a multi-offset, multi-acquisition protocol. The 31 offsets were 0, ±0.25,±0.5, ±0.75, ±1, ±1.5, ±2, ±2.5, ±3.0 , ±3.25 , ±3.5 , ±3.75 , ±4 , ±4.5, ±5.0, and ±6.0 ppm, and the values in parentheses were the number of acquisitions, which was 1 if not specifically noted (38). The saturated image at the offset of 15.6 ppm was also acquired to assess the conventional MT imaging. The total acquisition time for the APTw imaging procedure was 4 minutes and 21 seconds. The duration of a total MR examination was about 12 minutes.
Baseline clinical characteristics of patients
For the morphological evaluation of HCCs, one observer who did not participate in drawing regions of interest (ROIs) recorded the following characteristics of the HCCs: the tumor size and the clinical data, such as age, sex, etiology of liver disease, and biochemical factors [including serum alpha-fetoprotein (AFP), alanine transaminase (ALT), and aspartate aminotransferase (AST) levels] were collected from medical records.
The APTw image data were post-processed using Interactive Data Language (IDL, ITT Visual Information Solutions, Boulder, CO, USA). The normalized saturated signal intensity curve (Ssat/S0) was calculated with 31 different frequency offsets (−6 to 6 ppm), and the Z-spectrum was then plotted (8,9). The voxel-wise Z-spectrum was fitted by a 12th-order polynomial model, and the fitted curve was interpolated to a finer resolution of 1 Hz. Further, as previously reported (39), the original Z-spectrum was corrected for the residual B0 inhomogeneity effects through the centering of the Z-spectrum. As usual, the magnetization transfer ratio (MTR) and the MTR asymmetry (MTRasym) were defined as follows:
in which Ssat and S0 are the signal intensities with and without selective RF irradiation, respectively. The S0 image was acquired for the signal normalization. Specifically, the APTw image was constructed with the MTRasym at the offsets of ±3.5 ppm with respect to the water signal (8,9):
In this study, the APTw images were displayed by rainbow colors, and a display window (-5%, +5%) was used. In addition, the conventional MT imaging was quantified as follows:
The ROI image analysis was performed by two observers (Observer 1, YL and Observer 2, WJ, with three and five years of experience in abdominal imaging diagnosis, respectively) who were blinded to the clinical and histological information. Observer 1 performed a second measurement after one week. By using the T2WI image as an anatomical reference, ROIs of approximately 200–700 mm2 were placed manually in the solid component of the tumor for each patient. Large cystic cavities, large areas of necrosis, calcification, or hemorrhage, or large vessels were excluded from the ROI selection. The Z-spectrum and MTRasym spectrum data, APTw values, and ADC values were recorded for each ROI.
The inter- and intra-observer agreement for measures from the two observers were analyzed by calculation of the intraclass correlation coefficients (ICCs). ICC ≥0.75 indicated excellent concordance; 0.60–0.74, good; 0.40–0.59, fair; and ≤0.40, poor (35). An independent t-test was used to compare continuous variables. Categorical variables were compared by χ2 test. Receiver operating characteristic (ROC) curves and areas under the ROC curves (AUCs), with 95% confidence intervals (CIs), were generated for the significant parameters. The optimal cutoff value and the corresponding sensitivity and specificity values were calculated. In addition, the correlations between APTw or ADC values and the histological grades of HCC were evaluated by the Spearman correlation analyses. SPSS (version 20.0 for Windows, IBM Corporation, USA) and MedCalc 15.8 were used for statistical analysis. P<0.05 was considered to indicate statistical significance.
Z-spectrum and APTw image characteristics
Figure 1 shows the ROI-averaged Z-spectra, and the corresponding MTRasym spectra for two typical high- and low-grade HCC cases. The Z-spectra for both cases were very smooth in the offset range from −6 to 6 ppm. The Z-spectrum (−6 to 6 ppm) of the high-grade HCC was higher than that of the low-grade HCC (Figure 1A). Notably, the MTRasym (3.5 ppm) was significantly higher for the high-grade HCC than for the low-grade HCC (Figure 1B).
Quantitative imaging analysis
The ICCs between the two observers were 0.856 (95% CI: 0.726–0.927) for APTw values and 0.936 (95% CI: 0.874–0.968) for ADC values. The ICCs of intra-observer were 0.750 (95% CI: 0.726–0.927) for APTw values, and 0.800 (95% CI: 0.782–0.935) for ADC values. Figure 4 shows the APTw values of the high- and low-grade HCCs as determined by the two observers.
Because several measurements are highly reproducible, the APTw and ADC values for the high- and low-grade HCCs from the first measurement of Observer 1 were statistically compared. As listed in Table 2, the APTw values were higher in the high-grade HCC [grades 3 and 4, (2.76±1.38)%] than in the low-grade HCC [grades 1 and 2, (1.59±0.79)%; P=0.034]. Meanwhile, the ADC values were lower in the high-grade HCC [(0.53±0.21)×10−3mm2/s] than in the low-grade HCC [(0.79±0.18)×10−3mm2/s; P=0.010].
Diagnostic performance analysis
The ROC analyses demonstrated the good diagnostic performance of the APTw, ADC values, and their combination in differentiating high- from low-grade HCCs from the first measurement of Observer 1, with AUCs of 0.814 for APTw, 0.745 for ADC, and 0.822 for their combination, as showed in Figure 5. Corresponding sensitivity, and specificity values were detailed in Table 3. The optimal APTw cutoff value was 2.30%, and the corresponding sensitivity and specificity in the prediction of high-grade HCC were 92.3% and 68.4%, respectively. The optimal ADC value was 0.60×10−3mm2/s, and the corresponding sensitivity and specificity of ADC in the prediction of high-grade HCC were 84.6% and 73.7%, respectively. The sensitivity and specificity of the combination of both in the prediction of high-grade HCC were 100.0% and 68.4%, respectively.
Correlation with the histological grades
Significant correlations were found between APTw values and histological grades (r=0.534; P=0.002), as well as between ADC values and histological grades (r=−0.417; P=0.018).
This study assessed the differences between the APTw and ADC values for the high- and low-grade HCCs. The results demonstrated significantly higher APTw values (P=0.034), but significantly lower ADC values (P=0.010), in the high- than in the low-grade HCC. Moderate correlations were found between APTw values and histological grades (r=0.534; P=0.002), as well as between ADC values and histological grades (r=−0.417; P=0.018). The significance of APTw imaging is that endogenous protein information in tissue is obtained indirectly through the bulk water signal used in MRI. Notably, an egg white phantom experiment showed that the APTw signal mostly reflects mobile proteins (40). Theoretically, the effect of APTw in tumor is primarily correlated with the tissue content of labile amide protons of mobile proteins (10,41). The application of APTw imaging to brain tumors has clearly (9,19-26) demonstrated that high APTw values are associated high cellularity and proliferation.
We found a significant increase in APTw values in the high-grade HCC, agreeing with those previous results in other malignancies (21,22). After the effects of conventional MT and direct water saturation were minimized in the Z-spectra, the upward shift in the MTRasym spectrum [including MTRasym (3.5 ppm), namely APTw] for high-grade HCC may be attributable to many factors, such as a higher tumor cell proliferation rate and cellular density. Despite differences in APTw values between high- and low-grade HCC, the liver was heterogeneous on the APTw image, as shown in Figures 2D and 3D. Similar to other MRI sequences, APTw MRI is prone to some confounding signal contributions that may mislead and confuse its interpretation (10). In the two cases presented above, the intrahepatic blood vessels showed hyperintensity on APTw images, perhaps because the mobile proteins in the blood generate strong endogenous APTw signals (10). Fortunately, on standard structural MRI sequences (such as T2w, FLAIR, and T1w), the areas of large necrosis, hemorrhages, or large vessels were often evident. By referring to routine structural MR images, APTw images could identify “hyperintensity artifacts”, such as necrosis, hemorrhages, and vessels, which was necessary for accurate interpretation. This might be the reason that APTw imaging had lower specificity in identifying the high- from low-grade HCC. On APTw images (Figures 2D and 3D), compared with the normal liver parenchyma that removed intrahepatic blood vessels, the low-grade HCC signal was generally lower, with only a few patchy high signals, which might be related to blood vessels or necrosis, but the high-grade HCC signal was overall higher, which might be associated with increased blood vessels in high-grade tumors (35).
Our results were consistent with the previous studies demonstrating lower ADC values for high-grade HCC than for low-grade HCC (4-6). Moderate correlations were found between APTw values and histological grades, which was superior to ADC values. Theoretically, ADC was correlated to tumor grade and reflected tumor cellular-level water diffusion. However, APTw, based on detection cellular mobile proteins, was correlated to tumor grade and provided a different aspect of the tumor microenvironment, namely the protein and peptide concentrations. Compared to the sensitivity of ADC, the sensitivity of the combination of both MRI parameters increased from 84.6% to 100.0% in the prediction of high-grade HCC. Furthermore, according to AUC analysis, APTw might yield better diagnostic performance in predicting the histological grade of HCC compared to ADC (0.814 and 0.745). The combination of both MRI parameters increased AUC of ADC from 0.888 to 0.910, although the two were not statistically significant. Therefore, we have reason to conclude that APTw MRI combined with DWI is more conducive to accurately and comprehensively reflect the characteristics of HCC (42).
There were several limitations to our study. First, the 2D APTw imaging sequence used allowed only one single-slice acquisition. This might influence the obtained APTw values, especially in more heterogeneous tumors. A 3D imaging acquisition sequence used in the brain (43,44) should be optimized and applied to the liver in the future. Second, the semi-quantitative APTw metrics, namely MTRasym (3.5 ppm), was used in this study. APTw is not pure due to other contributions, such as the upfield nuclear Overhauser effect of aliphatic protons and even some other CEST effects around 3.5 ppm. To more accurately quantify the APT effect, more complicated APT imaging acquisition or analysis approaches may be used in the future (45-49). Third, APTw may be affected some tissue parameters, particularly conventional MT and water T1 (50,51). Fortunately, no difference in MTR (15.6 ppm) between high- from low-grade HCCs [(13.2±7.0)% vs. (13.1±13.4)%, P=0.998] was found; moreover, APTw was reportedly insensitive to water T1 under the saturation power 2 µT used in this study (52-54). Fourth, this study did not include CT or MR enhancement details in HCC patients, which resulted in an inability to perform an accurate liver imaging reporting and data system (LI-RADS) classification of HCC. We should further add the HCC patient information and analyze the link between APTw imaging and LI-RADS in next step. Fifth, the pathologic features, including the proliferation index and microvascular density, were not analyzed, which limited the further correlation between APTw value and pathologic features. Finally, our sample size was relatively small. A large prospective cohort study that includes detailed pathologic information, CT or MR enhancement sequence and a fully developed 3D APTw imaging acquisition is needed in the future.
In conclusion, our preliminary study has demonstrated that APTw imaging can be used to differentiate high- from low-grade HCCs at the protein level. The APTw imaging signal may be a useful imaging biomarker that complements DWI for more accurate and comprehensive HCC characterization.
Funding: This study was supported by grants from the National Natural Science Foundation of China (81771826, 81361120392, and 81401404), Beijing Municipal Natural Science Foundation (7154235 and 7162171), and Beijing Hospital Nova Project (BJ-2016-037).
Conflicts of Interest: The authors have no conflicts of interest to declare.
Ethical Statement: All procedures performed were in accordance with the ethical standards of the institutional committee and with the 1964 Helsinki Declaration and its later amendments.
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