Clinical Radiology 69 (2014) e517ee524
Contents lists available at ScienceDirect
Clinical Radiology journal homepage: www.clinicalradiologyonline.net
Spectral CT imaging in the differential diagnosis of necrotic hepatocellular carcinoma and hepatic abscess Y. Yu a, L. Guo a, C. Hu a, K. Chen b, * a
Department of Radiology, The First Affiliated Hospital of Soochow University, No. 188, Shi Zi Street, Suzhou 215006, Jiangsu, China b Department of Radiology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, No. 197, Rui Jin Er Road, Shanghai 200025, China
art icl e i nformat ion Article history: Received 20 April 2014 Received in revised form 6 August 2014 Accepted 22 August 2014
AIM: To explore the value of CT spectral imaging in the differential diagnosis of necrotic hepatocellular carcinoma (nHCC) and hepatic abscess (HA) during the arterial phase (AP) and portal venous phase (PP). MATERIALS AND METHODS: Sixty patients with 36 nHCCs and 24 HAs underwent spectral CT during AP and PP. Iodine or water concentration were measured and the normalized iodine concentration (NIC) and lesion-normal parenchyma iodine concentration ratio (LNR) were calculated. The two-sample t-test was used to compare quantitative parameters. Two readers qualitatively assessed lesion types according to imaging features. Sensitivity and specificity were compared between the qualitative and quantitative studies. RESULTS: NIC and LNR in the AP for the wall of nHCC (0.14 0.04 mg/ml; 2.77 0.74) were higher than those of HA (0.13 0.02 mg/ml; 1.4 0.9). NIC and LNR in the PP for the wall of HA (0.66 0.05 mg/ml; 1.2 0.2) were higher than those of nHCC (0.5 0.11 mg/ml; 0.94 0.12). The differences in NIC in the AP were not significant but the differences in LNR in AP, and NIC and LNR in the PP were significant. The best quantitative parameter was LNR in AP, and a threshold of 1.52 would yield a sensitivity and specificity of 100% and 91.7%, respectively, for differentiating nHCC from HA. CONCLUSION: CT spectral imaging with quantitative iodine concentration analysis may help to increase the accuracy of differentiating nHCC from HA. Ó 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Introduction
* Guarantor and correspondent: K. Chen, Department of Radiology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, No. 197, Rui Jin Er Road, Shanghai 200025, China. Tel.: þ86 13701769751. E-mail address: [email protected] (K. Chen).
Hepatocellular carcinoma (HCC) is the fifth most common neoplastic process and the third leading cause of cancer-related deaths worldwide.1 HCC usually occurs as a complication of chronic liver disease and most often arises in cirrhotic livers. The imaging appearance of HCC can vary dramatically.2 However, hepatic abscess (HA) is a localized accumulation of pus surrounded by a capsule, resulting
http://dx.doi.org/10.1016/j.crad.2014.08.018 0009-9260/Ó 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
e518
Y. Yu et al. / Clinical Radiology 69 (2014) e517ee524
from an infectious process of bacterial origin with destruction of the hepatic parenchyma and stroma.3,4 Accurate diagnosis of the HA has important prognostic and therapeutic implications because of the treatable nature of the lesions and high morbidity and mortality associated with untreated or missed lesions.4 Although diagnosis of HCC is easier to establish, mainly in relation to improved radiodiagnostic examinations, the tumour may occur under atypical presentations mimicking other benign or malignant processes.5 As was reported in previous studies, HCC that develop central necrosis or cyst may mimic the appearance of HA.3,5,6 In this case, differentiating necrotic HCC (nHCC) from HA is sometimes difficult because there is a considerable overlap in the clinical presentation and CT appearances between the two different entities.3,5,6 However, the distinction between the nHCC and HA is of great clinical importance to initiate the appropriate therapy, especially in patients presenting with non-specific symptoms. The role of CT or MRI in the differential diagnosis of nHCC and HA has been discussed in previous studies,3,5 but the use of CT spectral imaging in this aspect has not been reported. The purpose of the present study was to preliminarily investigate the usefulness of CT spectral imaging in differentiating nHCC from HA.
Materials and methods Patients The local ethics committee approved this prospective study and all patients provided written informed consent. From June 2011 to February 2013, 250 patients who had liver masses with cystic or necrotic cavities detected at ultrasonography underwent spectral CT dual-phase imaging. One hundred and ninety patients were excluded from the study because (a) they had no nHCC or HA or (b) there was inadequate confirmation of histological findings. Sixty patients (41 men, 19 women; median age 54 years; range 24e75 years) were enrolled in the present study. Thirty-six patients (28 men, eight women; median age 57 years; range 24e75 years) had 36 nHCCs (mean diameter 6 cm, range 3.8e9.6 cm) and 24 patients (13 men, 11 women; median age 42 years; 26e67 years) had 38 HAs (mean diameter 5.2 cm, range 3.4e7.6 cm). Only the largest was selected for analysis when an individual patient had multiple lesions. Thus, 36 nHCCs and 24 HAs were included in the present study. Ten of the 36 nHCCs were in patients with cirrhosis as a result of chronic hepatitis B. Six patients with HA had liver cirrhosis or chronic hepatitis B. All HCCs in 36 patients were proven histopathologically after surgical resection. Histopathological reports revealed the following grades of differentiation according to EdmondsoneSteiner classification: none were grade 1 HCCs; five grade 2 HCCs; 14 grade 3 HCCs; and 17 grade 4 HCCs. In 24 patients with 38 HAs, the diagnoses were proved by means of percutaneous drainage (n ¼ 16) or aspiration (n ¼ 8) of pus from the lesions.
The clinical characteristics of patients with nHCC or HA are shown in Table 1. The symptoms included fever (n ¼ 8), chills (n ¼ 10), and right upper quadrant abdominal pain (n ¼ 18) in patients with nHCC. Leukocytosis or neutrophilia was noted in eight patients with nHCC and nine patients with HA. The serum alpha-foetoprotein (AFP) level was elevated in 15 nHCC patients and five HA patients (Table 1).
CT examinations Triple-phase CT (i.e., unenhanced and two-phase contrast-enhanced CT examinations) were performed by using a Discovery CT750 HD CT system (64 detectors, GE Healthcare, Waukesha, WI, USA). Unenhanced images were acquired using the conventional helical scan mode at 120 kVp tube voltage. Patients were then injected with nonionic contrast medium (iopamidol, 300 mg iodine/ml; Iopamiro 300, Shanghai BRACCO Sine Pharmaceutical, Shanghai, China) via antecubital venous access at a rate of 3e4 ml/s for a total of 80e100 ml during the arterial (AP) and portal venous phase (PP). The delay for AP imaging was determined using automatic scan-triggering software (SmartPrep; GE Healthcare). AP imaging began 10 s after the trigger attenuation threshold (100 HU) was reached at the level of the supra-coeliac abdominal aorta. PP imaging began at a delay of 30 s after AP imaging. AP and PP imaging were performed in the spectral imaging mode with fast tube voltage switching between 80 and 140 kVp during a single rotation. Other imaging parameters were as follows: 0.625 mm collimation thickness, 600 mA tube current, 0.6 s rotation speed, 0.983 helical pitch, 21.8 mGy CT dose index volume (comparable to a 21.5 mGy dose administered for conventional contrast-enhanced liver imaging in a normal-size patient). The CT images were reconstructed by using projection-based material-decomposition software and a standard reconstruction kernel. Three types of images were reconstructed from the single spectral CT acquisition for analysis: conventional polychromatic images obtained at 140 kVp, iodine- and waterbased material decomposition images, and monochromatic images obtained at values ranging from 40 to 140 keV.
Quantitative analyses All the measurements were performed on an advanced workstation (AW4.4; GE Healthcare, Waukesha, WI, USA) with a Gemstone Spectral Imaging (GSI) viewer. The default Table 1 Clinical characteristics of patients with nHCC or HA.
Fever Chills Right upper quadrant pain Weight loss Leukocytosis or neutrophilia AFP >20 ng/ml
nHCC (n ¼ 36)
HA (n ¼ 24)
8 10 18 11 8 15
9 10 11 5 9 5
nHCC, necrotic hepatocellular carcinoma; HA, hepatic abscess; AFP, alphafoetoprotein.
Y. Yu et al. / Clinical Radiology 69 (2014) e517ee524
70 keV monochromatic images and iodine-based material decomposition images were reviewed. Circular regions of interest (ROIs) were placed on the walls and necrotic cavities of lesions, normal hepatic parenchyma, and the aorta on the default 70 keV monochromatic images. Areas of focal change in hepatic parenchymal attenuation, large vessels, and prominent artefacts were carefully avoided. To ensure consistency, all measurements were performed three times at different image levels, and average values were calculated. For all measurements, the size, shape, and position of the ROIs were kept consistent between the two phases by applying the copy-and-paste function. The GSI viewer software package automatically calculated the attenuation values, iodine (water) and water (iodine) concentration for the lesions, aorta, and normal hepatic parenchyma. Two recently introduced parameters were derived from the iodine concentration measurements: (1) normalized iodine concentration (NIC), calculated as NIC ¼ IClesion =ICaorta ; where IClesion and ICaorta are the iodine concentrations in the lesions and in the aorta; iodine concentrations in the lesions were normalized to those of the aorta in order to minimise variations in patients. (2) The lesion-to-normal parenchyma ratio (LNR) for the iodine concentration, calculated as LNR ¼ IClesion =ICliver ; where IClesion and ICliver are the iodine concentrations in the lesions and in the normal hepatic parenchyma.
Qualitative analyses The two radiologists (with more than 15 years of experience) qualitatively reviewed the CT images including conventional polychromatic images, monochromatic images and iodine-based material decomposition images using the GSI viewer in consensus at a workstation (AW4.4; GE Healthcare). They were blinded to the diagnosis of the lesion, the patient information, and the results of the correlative imaging examinations. The readers recorded the following lesion features including number, location, shape, necrosis or cyst, internal septa, pseudocapsule, mural nodules, presence of enhancement in AP, enhancement pattern of the lesions and perilesional liver tissue. The shape was described as regular (round or ovoid) or irregular. The changes in enhancement degree or pattern between the two phases were characterized as expansion, washout, or none. Expansion was defined as an increasing area of enhancement in the lesion, while washout was defined as a change from high density relative to the density of the liver during the AP to isodensity or hypodensity relative to that of the liver during the PP. The enhancement pattern of the perilesional liver tissue was classified as wedge-shaped enhancement, circumferential enhancement, and no enhancement difference. Finally, the readers characterized each lesion in consensus as a nHCC or HA on the basis of the imaging findings. The typical enhancement pattern for nHCC was
e519
that the solid portion was obviously enhanced in the AP with a relatively quick washout in the PP and the necrotic or cystic portion showed no enhancement. HA was usually depicted as a single or multiloculated hypodense mass with an enhancing peripheral rim; occasionally, it demonstrated central gas, the “cluster” sign, and the “double target” sign.7e9 Differences among the observers were resolved by means of a consensus conference. The sensitivity (correct diagnoses of nHCC) and specificity (correct diagnoses of HA) of the individual phase were evaluated.
Statistical analysis The data were analysed using SPSS version 13.0 (Chicago, IL, USA). Quantitative values were recorded as mean standard deviation. The two-sample t-test was performed to compare the quantitative parameters NIC and LNR between the nHCC and HA, and chi-square test was used to compare each CT feature, with p < 0.05 indicating significance. Receiver operating characteristic (ROC) curves were generated to help establish the threshold values of NIC and LNR required for significant differentiation of nHCC from HA. The diagnostic capability was determined by calculating the area under the receiver operating characteristic curve. The best sensitivity and specificity were achieved by using the optimal thresholds. Sensitivity was defined as the number of correct diagnoses of nHCC divided by the number of proven nHCC, multiplied by 100. Specificity was defined as the number of correct diagnoses of HA divided by the number of proven HA, multiplied by 100. The null hypothesis test was that the area under the receiver operating characteristic curve was 0.5; the alternative was that this area was >0.5. The McNemar test was used to test for statistical differences in sensitivity and specificity between spectral quantitative image analysis and conventional qualitative image analysis for differentiating nHCC from HA.
Results Quantitative analyses Values for spectral quantitative assessment of the wall and necrotic cavities of nHCC and HA are listed in Table 2. NIC and LNR in the AP for the wall of nHCC (0.14 0.04 mg/ ml; 2.77 0.74) were higher than those of HA (0.13 0.02 mg/ml; 1.4 0.9; Fig 1aeb). The differences in NIC in the AP were not significant, but the differences in LNR in the AP were significant. NIC and LNR in the PP for the wall of HA (0.66 0.05 mg/ml; 1.2 0.2) were higher than those of nHCC (0.5 0.11 mg/ml; 0.94 0.12; Fig 1ced). The differences in NIC and LNR in the PP were both significant between the wall of nHCC and those of HA (p 0.001). There were no significant differences in NIC in AP, NIC in the PP and LNR in the PP between the necrotic cavities of nHCC and those of HA (p > 0.05). Patients with nHCC had necrotic cavities with a significantly higher water (iodine) concentration than did the patients with HA during the AP
e520
Y. Yu et al. / Clinical Radiology 69 (2014) e517ee524
Table 2 Spectral quantitative assessment of the walls and necrotic cavities of nHCC and HA. Group AP Wall of nHCC Wall of HA p-Value PP Wall of nHCC Wall of HA p-Value AP Necrotic cavities Necrotic cavities p-Value PP Necrotic cavities Necrotic cavities p-Value
NIC
LNR
Water (Iodine)
0.14 0.04 0.13 0.02 0.58
2.77 0.74 1.40 0.90 0.05). No enhancement between the AP and the PP was noted in 13 (36%) of the 36 nHCCs and three (12%) of the 24 HAs. There were significant differences in enhancement pattern of the lesions (p ¼ 0.002) and perilesional liver tissue (p < 0.001). Based on the qualitative analysis of imaging features seen during the combined AP and PP, a sensitivity and specificity of 83.3% (30 of 36 nHCCs) and 83.3% (20 of 24 HAs), respectively, was achieved for differentiating between nHCC and HA. Therefore, spectral quantitative image analysis, as compared with conventional qualitative CT image analysis, sensitivity and specificity increased from 83.3% and 83.3% to 100% and 91.7%, respectively. There were significant differences in sensitivity (p ¼ 0.031) but no significant differences in specificity (p ¼ 0.500) between spectral quantitative image analysis and conventional qualitative image analysis for differentiating nHCC from HA.
Discussion Accurate diagnosis of HCC results from advances in imaging techniques and better image interpretation. CT and MRI of HCC are characterized by the timing and pattern of contrast enhancement.5 However, when HCC develops central necrosis or cyst, the imaging characteristics are unusually atypical and can mimic HA.3,5,6 In these cases, the distinction between nHCC and HA using qualitative imaging features analyses alone may be difficult. To the authors’ knowledge, the present study is the first to investigate the application value of quantitative and qualitative analysis using CT spectral imaging in differentiating nHCC from HA. CT spectral imaging based on the rapid switching between 140 and 80 kVp allows the reconstruction of conventional polychromatic images corresponding to 140 kVp, monochromatic images with energies ranging from 40e140 keV, and the material decomposition images.2,10 This imaging method has also found use in several clinical applications including preoperative detection of insulinomas,10 diagnosis of pulmonary embolism,11 and differentiating hypervascular hepatic lesions.2,12,13 LV et al.13 reported use of spectral CT with fast tube voltage switching might increase the sensitivity for differentiating small haemangioma from small HCC in two-phase imaging. Other previous studies2,12 also indicated that CT spectral imaging with quantitative iodine concentration analysis might help to increase the accuracy of differentiating HCC from focal nodular hyperplasia or angiomyolipoma. For medical diagnostic imaging, water and iodine are often selected as the basis pair for material decomposition
Y. Yu et al. / Clinical Radiology 69 (2014) e517ee524
e521
Figure 1 Box plots of NIC (a, c) and LNR (b, d) for the walls and necrotic cavities of nHCC and HA during the AP and PP. NICAP and NICPP are cited in milligrams per millilitre.
image presentation because their atomic numbers span the range of atomic numbers for materials generally found in medical imaging and approximate those of soft tissue and iodinated contrast material to result in materialattenuation images that are intuitive to interpret.13 For the wall of nHCC or HA, iodine-based material decomposition images could be very sensitive, showing focal uptake of the iodinated contrast material. Furthermore, the measured iodine concentration in lesions might be a useful quantitative parameter that reflects the blood supply of lesions. For the cystic or necrotic cavities of nHCC or HA, the measured water (iodine) concentrations could be used to evaluate the degree of necrosis of the lesions. According to the present study results, NIC and LNR in the AP for the wall of nHCC were higher than those of HA, whereas NIC and LNR in the PP for the wall of HA were higher than those of nHCC. It was reported that intense enhancement of the abscess wall was present in the AP and persistent in the PP. The rapid enhancement of the abscess
wall has been attributed to increased capillary permeability.4 However, HCC usually consists of a significant, rapid enhancement in the AP with a relatively quick washout in the PP due to a feeding hepatic artery.2 So the iodine concentrations in the AP for the wall of nHCC, reflecting the blood supply from hepatic artery, were higher than those of HA, reflecting the increased capillary permeability. Also, the wall of HA had significantly higher iodine concentrations than those of nHCC during the PP due to the persistent enhancement of abscess wall in the PP. The differences in LNR in the AP and NIC and LNR in the PP between the wall of nHCC and that of HA were significant, indicating that spectral quantitative parameters of the lesion wall had value in differentiating nHCC from HA. Although NIC in the AP and NIC and LNR in the PP for the necrotic cavities of HA were higher than those of nHCC, there were no significant differences in NIC in the AP and NIC and LNR in the PP between the necrotic cavities of nHCC and those of HA. This might indicate that spectral quantitative parameters of the
e522
Y. Yu et al. / Clinical Radiology 69 (2014) e517ee524
Figure 2 Receiver operating characteristic curves for normalized iodine concentration (NIC) and lesion-normal parenchyma iodine concentration ratio (LNR) of the walls of lesions in differentiating nHCC from HA during the AP (a) and PP (b).
necrotic cavities of lesions had no value in differentiating nHCC from HA. As mentioned above, some patients in the present study had liver cirrhosis. In the cirrhotic liver, important changes occur in the liver circulation. The increase of intrahepatic vascular resistance decreases the portal fraction of liver perfusion.14,15 This decrease of portal perfusion is partially compensated by an increase of arterial inflow.14,15 So, LNR in the AP may become smaller due to the increasing arterial inflow of liver parenchyma. However, LNR in the PP may become larger owing to the decreasing portal perfusion. Therefore, LNR may be not an accurate quantitative parameter for the patients with liver cirrhosis. In this case, NIC may be more accurate than LNR. ROC curve analysis in the present study revealed that NIC and LNR of the wall had high sensitivity and specificity for differentiating nHCC from HA. The best quantitative parameter was LNR in the AP and the threshold of 1.52 would yield a sensitivity and specificity of 100% and 91.7%, respectively. Compared with conventional qualitative Table 3 Diagnostic performance of spectral quantitative parameters of the wall of lesions for distinguishing nHCC from HA. Group
NICAP
LNRAP
NICPP
LNRPP
Areas under the ROC Thresholdsa Sensitivitiesb (%) Specificitiesc (%)
0.551 0.17 38.9 (14) 100 (24)
0.931 1.52 100 (36) 91.7 (22)
0.861 0.51 72.2 (26) 100 (24)
0.787 0.89 55.6 (20) 100 (24)
NICAP, normalized iodine concentrations in the arterial phase; LNRAP, the lesion-to-normal-parenchyma iodine concentration ratio in the arterial phase; NICPP, normalized iodine concentrations in the portal venous phase; LNRPP, the lesion-to-normal-parenchyma iodine concentration ratio in the portal venous phase. a Threshold NICAP and NICPP are cited in milligrams per millilitre. b Sensitivity values are cited as percentages. Data in parentheses are numbers of nHCC lesions (n ¼ 36) used to calculate percentages. c Specificity values are cited as percentages. Data in parentheses are numbers of HA lesions (n ¼ 24) used to calculate percentages.
image analysis, quantitative image analysis with spectral CT improved both the sensitivity (from 83.3% to 100%) and specificity (from 83.3% to 91.7%). There were significant differences in sensitivity but no significant differences in specificity. So, although the results were suggestive of an improvement in specificity, it was not possible to conclude improved specificity of this method due to the small number of HA. The threshold values evaluated in the present study were based on the specific populations from which they were obtained and thus were probably overestimations of performance. The accuracy of threshold values needs to be confirmed by a large samples study in the future. Table 4 Morphology and enhancement pattern of nHCC and HA. Features
nHCC HA p-Values (n ¼ 36) (n ¼ 24)
Lobe location Right hepatic lobe 20 (55) Left hepatic lobe 16 (44) Shape Regular 14 (39) Irregular 22 (61) Necrosis or cyst 36 (100) Internal septa 8 (22) Mural nodules 15 (42) Pseudocapsule 10 (28) Presence of enhancement in the AP 36 (100) Enhancement pattern of perilesional liver tissue Wedge-shaped enhancement 3 (8) Circumferential enhancement 1 (3) No enhancement difference 32 (89) Enhancement change between AP and PP Expansion 16 (44) Washout 7 (20) None 13 (36)
0.389 16 (67) 8 (33) 0.073 15 9 24 16 2 0 22
(63) (38) (100) (67) (8) (0) (92)
1.000 0.001 0.005 0.013 0.304
Contents lists available at ScienceDirect
Clinical Radiology journal homepage: www.clinicalradiologyonline.net
Spectral CT imaging in the differential diagnosis of necrotic hepatocellular carcinoma and hepatic abscess Y. Yu a, L. Guo a, C. Hu a, K. Chen b, * a
Department of Radiology, The First Affiliated Hospital of Soochow University, No. 188, Shi Zi Street, Suzhou 215006, Jiangsu, China b Department of Radiology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, No. 197, Rui Jin Er Road, Shanghai 200025, China
art icl e i nformat ion Article history: Received 20 April 2014 Received in revised form 6 August 2014 Accepted 22 August 2014
AIM: To explore the value of CT spectral imaging in the differential diagnosis of necrotic hepatocellular carcinoma (nHCC) and hepatic abscess (HA) during the arterial phase (AP) and portal venous phase (PP). MATERIALS AND METHODS: Sixty patients with 36 nHCCs and 24 HAs underwent spectral CT during AP and PP. Iodine or water concentration were measured and the normalized iodine concentration (NIC) and lesion-normal parenchyma iodine concentration ratio (LNR) were calculated. The two-sample t-test was used to compare quantitative parameters. Two readers qualitatively assessed lesion types according to imaging features. Sensitivity and specificity were compared between the qualitative and quantitative studies. RESULTS: NIC and LNR in the AP for the wall of nHCC (0.14 0.04 mg/ml; 2.77 0.74) were higher than those of HA (0.13 0.02 mg/ml; 1.4 0.9). NIC and LNR in the PP for the wall of HA (0.66 0.05 mg/ml; 1.2 0.2) were higher than those of nHCC (0.5 0.11 mg/ml; 0.94 0.12). The differences in NIC in the AP were not significant but the differences in LNR in AP, and NIC and LNR in the PP were significant. The best quantitative parameter was LNR in AP, and a threshold of 1.52 would yield a sensitivity and specificity of 100% and 91.7%, respectively, for differentiating nHCC from HA. CONCLUSION: CT spectral imaging with quantitative iodine concentration analysis may help to increase the accuracy of differentiating nHCC from HA. Ó 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Introduction
* Guarantor and correspondent: K. Chen, Department of Radiology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, No. 197, Rui Jin Er Road, Shanghai 200025, China. Tel.: þ86 13701769751. E-mail address: [email protected] (K. Chen).
Hepatocellular carcinoma (HCC) is the fifth most common neoplastic process and the third leading cause of cancer-related deaths worldwide.1 HCC usually occurs as a complication of chronic liver disease and most often arises in cirrhotic livers. The imaging appearance of HCC can vary dramatically.2 However, hepatic abscess (HA) is a localized accumulation of pus surrounded by a capsule, resulting
http://dx.doi.org/10.1016/j.crad.2014.08.018 0009-9260/Ó 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
e518
Y. Yu et al. / Clinical Radiology 69 (2014) e517ee524
from an infectious process of bacterial origin with destruction of the hepatic parenchyma and stroma.3,4 Accurate diagnosis of the HA has important prognostic and therapeutic implications because of the treatable nature of the lesions and high morbidity and mortality associated with untreated or missed lesions.4 Although diagnosis of HCC is easier to establish, mainly in relation to improved radiodiagnostic examinations, the tumour may occur under atypical presentations mimicking other benign or malignant processes.5 As was reported in previous studies, HCC that develop central necrosis or cyst may mimic the appearance of HA.3,5,6 In this case, differentiating necrotic HCC (nHCC) from HA is sometimes difficult because there is a considerable overlap in the clinical presentation and CT appearances between the two different entities.3,5,6 However, the distinction between the nHCC and HA is of great clinical importance to initiate the appropriate therapy, especially in patients presenting with non-specific symptoms. The role of CT or MRI in the differential diagnosis of nHCC and HA has been discussed in previous studies,3,5 but the use of CT spectral imaging in this aspect has not been reported. The purpose of the present study was to preliminarily investigate the usefulness of CT spectral imaging in differentiating nHCC from HA.
Materials and methods Patients The local ethics committee approved this prospective study and all patients provided written informed consent. From June 2011 to February 2013, 250 patients who had liver masses with cystic or necrotic cavities detected at ultrasonography underwent spectral CT dual-phase imaging. One hundred and ninety patients were excluded from the study because (a) they had no nHCC or HA or (b) there was inadequate confirmation of histological findings. Sixty patients (41 men, 19 women; median age 54 years; range 24e75 years) were enrolled in the present study. Thirty-six patients (28 men, eight women; median age 57 years; range 24e75 years) had 36 nHCCs (mean diameter 6 cm, range 3.8e9.6 cm) and 24 patients (13 men, 11 women; median age 42 years; 26e67 years) had 38 HAs (mean diameter 5.2 cm, range 3.4e7.6 cm). Only the largest was selected for analysis when an individual patient had multiple lesions. Thus, 36 nHCCs and 24 HAs were included in the present study. Ten of the 36 nHCCs were in patients with cirrhosis as a result of chronic hepatitis B. Six patients with HA had liver cirrhosis or chronic hepatitis B. All HCCs in 36 patients were proven histopathologically after surgical resection. Histopathological reports revealed the following grades of differentiation according to EdmondsoneSteiner classification: none were grade 1 HCCs; five grade 2 HCCs; 14 grade 3 HCCs; and 17 grade 4 HCCs. In 24 patients with 38 HAs, the diagnoses were proved by means of percutaneous drainage (n ¼ 16) or aspiration (n ¼ 8) of pus from the lesions.
The clinical characteristics of patients with nHCC or HA are shown in Table 1. The symptoms included fever (n ¼ 8), chills (n ¼ 10), and right upper quadrant abdominal pain (n ¼ 18) in patients with nHCC. Leukocytosis or neutrophilia was noted in eight patients with nHCC and nine patients with HA. The serum alpha-foetoprotein (AFP) level was elevated in 15 nHCC patients and five HA patients (Table 1).
CT examinations Triple-phase CT (i.e., unenhanced and two-phase contrast-enhanced CT examinations) were performed by using a Discovery CT750 HD CT system (64 detectors, GE Healthcare, Waukesha, WI, USA). Unenhanced images were acquired using the conventional helical scan mode at 120 kVp tube voltage. Patients were then injected with nonionic contrast medium (iopamidol, 300 mg iodine/ml; Iopamiro 300, Shanghai BRACCO Sine Pharmaceutical, Shanghai, China) via antecubital venous access at a rate of 3e4 ml/s for a total of 80e100 ml during the arterial (AP) and portal venous phase (PP). The delay for AP imaging was determined using automatic scan-triggering software (SmartPrep; GE Healthcare). AP imaging began 10 s after the trigger attenuation threshold (100 HU) was reached at the level of the supra-coeliac abdominal aorta. PP imaging began at a delay of 30 s after AP imaging. AP and PP imaging were performed in the spectral imaging mode with fast tube voltage switching between 80 and 140 kVp during a single rotation. Other imaging parameters were as follows: 0.625 mm collimation thickness, 600 mA tube current, 0.6 s rotation speed, 0.983 helical pitch, 21.8 mGy CT dose index volume (comparable to a 21.5 mGy dose administered for conventional contrast-enhanced liver imaging in a normal-size patient). The CT images were reconstructed by using projection-based material-decomposition software and a standard reconstruction kernel. Three types of images were reconstructed from the single spectral CT acquisition for analysis: conventional polychromatic images obtained at 140 kVp, iodine- and waterbased material decomposition images, and monochromatic images obtained at values ranging from 40 to 140 keV.
Quantitative analyses All the measurements were performed on an advanced workstation (AW4.4; GE Healthcare, Waukesha, WI, USA) with a Gemstone Spectral Imaging (GSI) viewer. The default Table 1 Clinical characteristics of patients with nHCC or HA.
Fever Chills Right upper quadrant pain Weight loss Leukocytosis or neutrophilia AFP >20 ng/ml
nHCC (n ¼ 36)
HA (n ¼ 24)
8 10 18 11 8 15
9 10 11 5 9 5
nHCC, necrotic hepatocellular carcinoma; HA, hepatic abscess; AFP, alphafoetoprotein.
Y. Yu et al. / Clinical Radiology 69 (2014) e517ee524
70 keV monochromatic images and iodine-based material decomposition images were reviewed. Circular regions of interest (ROIs) were placed on the walls and necrotic cavities of lesions, normal hepatic parenchyma, and the aorta on the default 70 keV monochromatic images. Areas of focal change in hepatic parenchymal attenuation, large vessels, and prominent artefacts were carefully avoided. To ensure consistency, all measurements were performed three times at different image levels, and average values were calculated. For all measurements, the size, shape, and position of the ROIs were kept consistent between the two phases by applying the copy-and-paste function. The GSI viewer software package automatically calculated the attenuation values, iodine (water) and water (iodine) concentration for the lesions, aorta, and normal hepatic parenchyma. Two recently introduced parameters were derived from the iodine concentration measurements: (1) normalized iodine concentration (NIC), calculated as NIC ¼ IClesion =ICaorta ; where IClesion and ICaorta are the iodine concentrations in the lesions and in the aorta; iodine concentrations in the lesions were normalized to those of the aorta in order to minimise variations in patients. (2) The lesion-to-normal parenchyma ratio (LNR) for the iodine concentration, calculated as LNR ¼ IClesion =ICliver ; where IClesion and ICliver are the iodine concentrations in the lesions and in the normal hepatic parenchyma.
Qualitative analyses The two radiologists (with more than 15 years of experience) qualitatively reviewed the CT images including conventional polychromatic images, monochromatic images and iodine-based material decomposition images using the GSI viewer in consensus at a workstation (AW4.4; GE Healthcare). They were blinded to the diagnosis of the lesion, the patient information, and the results of the correlative imaging examinations. The readers recorded the following lesion features including number, location, shape, necrosis or cyst, internal septa, pseudocapsule, mural nodules, presence of enhancement in AP, enhancement pattern of the lesions and perilesional liver tissue. The shape was described as regular (round or ovoid) or irregular. The changes in enhancement degree or pattern between the two phases were characterized as expansion, washout, or none. Expansion was defined as an increasing area of enhancement in the lesion, while washout was defined as a change from high density relative to the density of the liver during the AP to isodensity or hypodensity relative to that of the liver during the PP. The enhancement pattern of the perilesional liver tissue was classified as wedge-shaped enhancement, circumferential enhancement, and no enhancement difference. Finally, the readers characterized each lesion in consensus as a nHCC or HA on the basis of the imaging findings. The typical enhancement pattern for nHCC was
e519
that the solid portion was obviously enhanced in the AP with a relatively quick washout in the PP and the necrotic or cystic portion showed no enhancement. HA was usually depicted as a single or multiloculated hypodense mass with an enhancing peripheral rim; occasionally, it demonstrated central gas, the “cluster” sign, and the “double target” sign.7e9 Differences among the observers were resolved by means of a consensus conference. The sensitivity (correct diagnoses of nHCC) and specificity (correct diagnoses of HA) of the individual phase were evaluated.
Statistical analysis The data were analysed using SPSS version 13.0 (Chicago, IL, USA). Quantitative values were recorded as mean standard deviation. The two-sample t-test was performed to compare the quantitative parameters NIC and LNR between the nHCC and HA, and chi-square test was used to compare each CT feature, with p < 0.05 indicating significance. Receiver operating characteristic (ROC) curves were generated to help establish the threshold values of NIC and LNR required for significant differentiation of nHCC from HA. The diagnostic capability was determined by calculating the area under the receiver operating characteristic curve. The best sensitivity and specificity were achieved by using the optimal thresholds. Sensitivity was defined as the number of correct diagnoses of nHCC divided by the number of proven nHCC, multiplied by 100. Specificity was defined as the number of correct diagnoses of HA divided by the number of proven HA, multiplied by 100. The null hypothesis test was that the area under the receiver operating characteristic curve was 0.5; the alternative was that this area was >0.5. The McNemar test was used to test for statistical differences in sensitivity and specificity between spectral quantitative image analysis and conventional qualitative image analysis for differentiating nHCC from HA.
Results Quantitative analyses Values for spectral quantitative assessment of the wall and necrotic cavities of nHCC and HA are listed in Table 2. NIC and LNR in the AP for the wall of nHCC (0.14 0.04 mg/ ml; 2.77 0.74) were higher than those of HA (0.13 0.02 mg/ml; 1.4 0.9; Fig 1aeb). The differences in NIC in the AP were not significant, but the differences in LNR in the AP were significant. NIC and LNR in the PP for the wall of HA (0.66 0.05 mg/ml; 1.2 0.2) were higher than those of nHCC (0.5 0.11 mg/ml; 0.94 0.12; Fig 1ced). The differences in NIC and LNR in the PP were both significant between the wall of nHCC and those of HA (p 0.001). There were no significant differences in NIC in AP, NIC in the PP and LNR in the PP between the necrotic cavities of nHCC and those of HA (p > 0.05). Patients with nHCC had necrotic cavities with a significantly higher water (iodine) concentration than did the patients with HA during the AP
e520
Y. Yu et al. / Clinical Radiology 69 (2014) e517ee524
Table 2 Spectral quantitative assessment of the walls and necrotic cavities of nHCC and HA. Group AP Wall of nHCC Wall of HA p-Value PP Wall of nHCC Wall of HA p-Value AP Necrotic cavities Necrotic cavities p-Value PP Necrotic cavities Necrotic cavities p-Value
NIC
LNR
Water (Iodine)
0.14 0.04 0.13 0.02 0.58
2.77 0.74 1.40 0.90 0.05). No enhancement between the AP and the PP was noted in 13 (36%) of the 36 nHCCs and three (12%) of the 24 HAs. There were significant differences in enhancement pattern of the lesions (p ¼ 0.002) and perilesional liver tissue (p < 0.001). Based on the qualitative analysis of imaging features seen during the combined AP and PP, a sensitivity and specificity of 83.3% (30 of 36 nHCCs) and 83.3% (20 of 24 HAs), respectively, was achieved for differentiating between nHCC and HA. Therefore, spectral quantitative image analysis, as compared with conventional qualitative CT image analysis, sensitivity and specificity increased from 83.3% and 83.3% to 100% and 91.7%, respectively. There were significant differences in sensitivity (p ¼ 0.031) but no significant differences in specificity (p ¼ 0.500) between spectral quantitative image analysis and conventional qualitative image analysis for differentiating nHCC from HA.
Discussion Accurate diagnosis of HCC results from advances in imaging techniques and better image interpretation. CT and MRI of HCC are characterized by the timing and pattern of contrast enhancement.5 However, when HCC develops central necrosis or cyst, the imaging characteristics are unusually atypical and can mimic HA.3,5,6 In these cases, the distinction between nHCC and HA using qualitative imaging features analyses alone may be difficult. To the authors’ knowledge, the present study is the first to investigate the application value of quantitative and qualitative analysis using CT spectral imaging in differentiating nHCC from HA. CT spectral imaging based on the rapid switching between 140 and 80 kVp allows the reconstruction of conventional polychromatic images corresponding to 140 kVp, monochromatic images with energies ranging from 40e140 keV, and the material decomposition images.2,10 This imaging method has also found use in several clinical applications including preoperative detection of insulinomas,10 diagnosis of pulmonary embolism,11 and differentiating hypervascular hepatic lesions.2,12,13 LV et al.13 reported use of spectral CT with fast tube voltage switching might increase the sensitivity for differentiating small haemangioma from small HCC in two-phase imaging. Other previous studies2,12 also indicated that CT spectral imaging with quantitative iodine concentration analysis might help to increase the accuracy of differentiating HCC from focal nodular hyperplasia or angiomyolipoma. For medical diagnostic imaging, water and iodine are often selected as the basis pair for material decomposition
Y. Yu et al. / Clinical Radiology 69 (2014) e517ee524
e521
Figure 1 Box plots of NIC (a, c) and LNR (b, d) for the walls and necrotic cavities of nHCC and HA during the AP and PP. NICAP and NICPP are cited in milligrams per millilitre.
image presentation because their atomic numbers span the range of atomic numbers for materials generally found in medical imaging and approximate those of soft tissue and iodinated contrast material to result in materialattenuation images that are intuitive to interpret.13 For the wall of nHCC or HA, iodine-based material decomposition images could be very sensitive, showing focal uptake of the iodinated contrast material. Furthermore, the measured iodine concentration in lesions might be a useful quantitative parameter that reflects the blood supply of lesions. For the cystic or necrotic cavities of nHCC or HA, the measured water (iodine) concentrations could be used to evaluate the degree of necrosis of the lesions. According to the present study results, NIC and LNR in the AP for the wall of nHCC were higher than those of HA, whereas NIC and LNR in the PP for the wall of HA were higher than those of nHCC. It was reported that intense enhancement of the abscess wall was present in the AP and persistent in the PP. The rapid enhancement of the abscess
wall has been attributed to increased capillary permeability.4 However, HCC usually consists of a significant, rapid enhancement in the AP with a relatively quick washout in the PP due to a feeding hepatic artery.2 So the iodine concentrations in the AP for the wall of nHCC, reflecting the blood supply from hepatic artery, were higher than those of HA, reflecting the increased capillary permeability. Also, the wall of HA had significantly higher iodine concentrations than those of nHCC during the PP due to the persistent enhancement of abscess wall in the PP. The differences in LNR in the AP and NIC and LNR in the PP between the wall of nHCC and that of HA were significant, indicating that spectral quantitative parameters of the lesion wall had value in differentiating nHCC from HA. Although NIC in the AP and NIC and LNR in the PP for the necrotic cavities of HA were higher than those of nHCC, there were no significant differences in NIC in the AP and NIC and LNR in the PP between the necrotic cavities of nHCC and those of HA. This might indicate that spectral quantitative parameters of the
e522
Y. Yu et al. / Clinical Radiology 69 (2014) e517ee524
Figure 2 Receiver operating characteristic curves for normalized iodine concentration (NIC) and lesion-normal parenchyma iodine concentration ratio (LNR) of the walls of lesions in differentiating nHCC from HA during the AP (a) and PP (b).
necrotic cavities of lesions had no value in differentiating nHCC from HA. As mentioned above, some patients in the present study had liver cirrhosis. In the cirrhotic liver, important changes occur in the liver circulation. The increase of intrahepatic vascular resistance decreases the portal fraction of liver perfusion.14,15 This decrease of portal perfusion is partially compensated by an increase of arterial inflow.14,15 So, LNR in the AP may become smaller due to the increasing arterial inflow of liver parenchyma. However, LNR in the PP may become larger owing to the decreasing portal perfusion. Therefore, LNR may be not an accurate quantitative parameter for the patients with liver cirrhosis. In this case, NIC may be more accurate than LNR. ROC curve analysis in the present study revealed that NIC and LNR of the wall had high sensitivity and specificity for differentiating nHCC from HA. The best quantitative parameter was LNR in the AP and the threshold of 1.52 would yield a sensitivity and specificity of 100% and 91.7%, respectively. Compared with conventional qualitative Table 3 Diagnostic performance of spectral quantitative parameters of the wall of lesions for distinguishing nHCC from HA. Group
NICAP
LNRAP
NICPP
LNRPP
Areas under the ROC Thresholdsa Sensitivitiesb (%) Specificitiesc (%)
0.551 0.17 38.9 (14) 100 (24)
0.931 1.52 100 (36) 91.7 (22)
0.861 0.51 72.2 (26) 100 (24)
0.787 0.89 55.6 (20) 100 (24)
NICAP, normalized iodine concentrations in the arterial phase; LNRAP, the lesion-to-normal-parenchyma iodine concentration ratio in the arterial phase; NICPP, normalized iodine concentrations in the portal venous phase; LNRPP, the lesion-to-normal-parenchyma iodine concentration ratio in the portal venous phase. a Threshold NICAP and NICPP are cited in milligrams per millilitre. b Sensitivity values are cited as percentages. Data in parentheses are numbers of nHCC lesions (n ¼ 36) used to calculate percentages. c Specificity values are cited as percentages. Data in parentheses are numbers of HA lesions (n ¼ 24) used to calculate percentages.
image analysis, quantitative image analysis with spectral CT improved both the sensitivity (from 83.3% to 100%) and specificity (from 83.3% to 91.7%). There were significant differences in sensitivity but no significant differences in specificity. So, although the results were suggestive of an improvement in specificity, it was not possible to conclude improved specificity of this method due to the small number of HA. The threshold values evaluated in the present study were based on the specific populations from which they were obtained and thus were probably overestimations of performance. The accuracy of threshold values needs to be confirmed by a large samples study in the future. Table 4 Morphology and enhancement pattern of nHCC and HA. Features
nHCC HA p-Values (n ¼ 36) (n ¼ 24)
Lobe location Right hepatic lobe 20 (55) Left hepatic lobe 16 (44) Shape Regular 14 (39) Irregular 22 (61) Necrosis or cyst 36 (100) Internal septa 8 (22) Mural nodules 15 (42) Pseudocapsule 10 (28) Presence of enhancement in the AP 36 (100) Enhancement pattern of perilesional liver tissue Wedge-shaped enhancement 3 (8) Circumferential enhancement 1 (3) No enhancement difference 32 (89) Enhancement change between AP and PP Expansion 16 (44) Washout 7 (20) None 13 (36)
0.389 16 (67) 8 (33) 0.073 15 9 24 16 2 0 22
(63) (38) (100) (67) (8) (0) (92)
1.000 0.001 0.005 0.013 0.304
