Assessment of blood flow in the hepatic tumors using non-contrast micro flow imaging: Initial experience

Abstract

PURPOSE:

To evaluate micro-flow imaging (MFI) in depicting the vascular architecture of hepatocellular carcinoma (HCC) and other focal liver lesions.

MATERIALS AND METHODS:

A total of 81 hepatic lesions were enrolled in this study. Each patient underwent CDFI, MFI, and CEUS examinations. The blood flow was first graded into three types (grade 1, 2 and 3) based on its richness with Adeler classification method. The differences in the grade of blood flow in liver tumors were compared between CDFI and MFI. With respect to the presented morphology, the blood flow was further classified into five types (Type I, II, III, IV and V). The morphological differences in blood flow shown by MFI between malignant and benign hepatic tumors were then analyzed.

RESULTS:

For the total 81 lesions, MFI detected 61 lesion cases (75.31%) with blood flow grade 2 and 3, which obviously outperformed CDFI which detected 28 cases (34.57%) of grade 2 and 3 (χ2 = 35.27, P = 0.000). The MFI also showed that the most common blood flow morphology of HCC is Type-III (21/48, 43.75%) while the hepatic hemangioma (HEM) is mostly presented as Type V (5/10, 50%). Moreover, the grade of blood flow in MFI varied with different pathological subtypes of HCC (χ2 = 5.610, P = 0.018).

CONCLUSIONS:

Compared with traditional CDFI, MFI reveals more blood vessels in liver lesions with clearer view of blood flow distribution. Besides, MFI technology can demonstrate grade of blood flow for various differentiation stages of malignant liver tumors.

Keywords

Micro-flow imaging (MFI)liver tumor vascular color Doppler flow imaging

1 Introduction

The characteristics of blood flow in tumors are of great value in differentiating between benign and malignant tumors, as well as reflecting different stages of tumor development. The blood flow within the tumor is also directly related to tumor growth, infiltration, and metastasis [1, 2].

Color Doppler Flow Imaging (CDFI) is a commonly accepted method for evaluating blood flow in liver tumors tumors. However, this technique is less effective for the detection of low-speed or micro-flow vascular signals. Contrast-enhanced ultrasound (CEUS) is an accurate and reliable imaging technique that can significantly improve the detection of low-velocity and micro flow, indicating the microcirculation of liver tumors [3 –6]. Nevertheless, CEUS examinations require the use of contrast agents and cannot be done at any time or anywhere. Moreover, the cost of CEUS is significantly higher than conventional ultrasound imaging technique.

Micro-flow imaging technology (MFI) is a brand-new Doppler ultrasound imaging technology developed in recent years. Different from CDFI, MFI can better display the low-speed and micro blood flow within lesions, while suppressing the low-speed clutter caused by tissue motion. We should note that, different from the previously reported MFI technique, it does not require contrast media and can display tiny, low-velocity blood flow within the lesion [7]. Previously similar techniques such as superb microvascular flow imaging (SMI) have discussed its value on vessel detection within the lesions of superficial organs such as breast and thyroid glands [8 –11]. However, there are few reports on the application of hepatic tumors. In addition, comparison with CEUS is missing in these reports. Thus, there is no confirmation of the blood vessels shown in MFI [12, 13]. In order to compare MFI with CDFI in terms of the ability of detecting low-speed and micro blood flow, and to confirm the existence of blood flow shown in MFI at the same time, the results of CEUS were used as a reference in this study. The differences of low-speed and micro blood flow displayed on MFI were further compared between benign and malignant tumors.

2 Patients and methods

2.1 Patients

The study was a prospective study. The study design and protocol were approved by the Ethics Committee in ZhongShan hospital (ethics number: B2016-062). Each patient signed an informed consent form prior to the examination. From December 2016 to October 2017, 81 patients with focal liver masses, where intrahepatic blood flow had been successfully detected with all the image modes (CDFI, MFI and CEUS), were selected and included in this study. The average age of patients was 55.4±13.0 years (range from 23 to 79 years old), including 54 males and 27 females. Of these 81 patients, 62 were with single lesions, 19 were with multifocal lesions. For these with multifocal lesions, the largest lesions were selected for imaging study. Therefore, there were in total 81 liver focal lesions in 81 patients with a lesion size of 4.7±2.3 cm (range from 1.2 cm to 10 cm). The pathological types of 81 liver lesions included hepatocellular carcinoma (HCC) (n = 48), hepatic metastases (MET) (n = 11), hepatic hemangioma (HEM) (n = 10), hepatic focal nodular hyperplasia (FNH) (n = 10) and hepatic abscess (ABS) (n = 2). Sixty of the lesions were confirmed by surgical pathology. 19 were diagnosed as FNH or HEM with results of CEUS and enhanced MRI. No significant changes were observed afterwards in the size of these lesions with 6 months follow-up. The left 2 patients were diagnosed as ABS combining CEUS and enhanced MRI. Ultrasound-guide punctures were performed and confirmed the results.

2.2 Examination method

The patient was fasted for 6 hours and checked supine or left lying. The ultrasound scanner Philips-EPIQ7 (Philips Medical Systems, Bothell, WA) combined with a probe C5-1 was used. The related MFI and CEUS software were equipped as well. In order to avoid inter-observer variability, all the examinations were performed by the same sonographer who had 20 years of experience in liver ultrasonography. Each patient received B-mode ultrasound scanning, CDFI, MFI, and CEUS. B-mode ultrasound examination was firstly performed for the whole liver. When the lesion was found, the border, morphology, echo, and the size were measured. Afterwards, CDFI and MFI techniques were applied sequentially to detect the blood flow within the lesion. The patient was required to hold breath and a dynamic image with 5 to 10 seconds was recorded. When the arterial blood flow of focal liver lesions was observed in the CDFI and MFI images, the frame which was considered containing most abundant vascular information would be registered. For CDFI, the wall filter was set to the lowest level and the color gain was adjusted to be as sensitive as possible to display small blood vessels before background noise occurs. The MFI settings included dual display (One shows the liver tumor in B-mode, and the other one shows the blood flow within liver tumors with MFI mode), low velocity selected for the speed range of blood flow, and the gain set to be optimized for display.

The examination was then followed by CEUS. SonoVue ultrasound contrast agent was injected subcutaneously via cubital vein 2.0 ml/times, followed by 5 ml 0.9% saline. After the injection of contrast agent, real-time images were recorded for up to 5 minutes for further analysis. Then the enhanced performance of liver tumors in three phases were observed. The three phases are: the arterial phase (30 seconds after contrast injection), the portal phase (31–120 seconds after contrast injection), and the delayed phase (121–300 seconds after contrast injection). When CEUS is performed, the gain, depth, and focus of the adjusted image were adjusted optimal to show the lesion, and the focus point is placed in the far field of the image. The CEUS settings include a mechanical index (MI) of 0.06, a dynamic range of 50 dB, and an imaging gain of 55%.

2.3 Image analysis

The images were reviewed by two sonographers who both had more than 10 years’ experience in liver ultrasound image diagnosis. When there are disagreements in image analysis, further discussions will be made to reach a consensus.

First, in order to show the different richness of blood flow shown by CDFI and MFI, we classified the blood flow into three grades according to Adler classification method [14]. Grade 1: a small amount of blood flow within the mass, 1 or 2 dot-like or short line blood vessels were visible; Grade 2: moderate blood flow within the mass, 3 or 4 dot-like or 1 long line blood vessels were visible, the blood vessel length was close to or beyond the radius of the mass; Grade 3: there are abundant blood flow within the mass, with more than 5 dot-like or 2 long line blood vessels visible (see Fig. 1).

Fig.1

Illustration of blood flow with different grades in micro-flow imaging. A: grade 1, a small amount of blood flow within the mass, 1 or 2 dot-like or short line blood vessels were visible; B: grade 2, moderate blood flow within the mass, 3 or 4 dot-like or 1 long line blood vessels were visible, the blood vessel length was close to or beyond the radius of the mass; C: grade 3, there are abundant blood flow within the mass, with more than 5 dot-like or 2 long line blood vessels visible.

Second, the imaging capability of MFI and CDFI technique to indicate the blood flow distribution of intrahepatic lesion was evaluated based on the enhancement position detected by CEUS. As the reference, the position of blood flow enhancement in the hepatic focal lesions was observed during the CEUS arterial phase (within 30 seconds after injection of contrast agent).

Third, the blood flow morphology in the liver lesions of these 81 patients shown in MFI was divided into 5 types (see Figs. 2 and 3): type I, peripheral; type II, central; type III, peripheral and central; type IV, radial; type V, ring-like. The morphological difference of blood flow was compared between malignant and benign tumors.

Fig.2

A schematic diagram of blood flow morphology in MFI for focal hepatic lesions. A: Type I, peripheral, blood flow around the mass. B: Type II, central, blood flow in the center of the tumor; C: Type III, peripheral and central, blood flow around and in the center of the mass; D: Type IV, radial, radial blood flow is shown in the center of the mass; E: Type V, ring-like, circular blood flow around the mass.

Fig.3

Example of different blood flow morphology displayed in micro-flow imaging. A: Type I with blood flow around the mass; B: Type II with blood flow in the center of the mass; C: Type III with blood flow around and in the center of the mass; D: Type IV with radial blood flow in the mass; E: Type E with ring-like blood flow around the mass.

2.4 Statistical analysis

The quantitative data was expressed as frequency plus percentage. The weighted K statistics method was applied to compare the percentage difference. The bigger the chi-squared value, the greater the difference. P values of <0.05 were considered to indicate statistical significance.

3 Results

3.1 Blood flow grade

Through our work, there was a significant difference between MFI and CDFI to detect the presence of blood flow in liver tumors (see Table 1). Among 81 cases of liver tumors, MFI detected 61 cases with blood flow grade 2 and grade 3, accounting for 75.31%, which is significantly greater than CDFI, which detected 28 cases of grade 2 and grade 3, accounting for 34.57% (χ2 = 35.27, P = 0.000).

Table 1
The blood flow grades of 81 hepatic lesions with CDFI and MFI

CDFI MFI Total

Grade 1 Grade 2 Grade 3

Grade 1 20 28 5 53

Grade 2 0 12 10 22

Grade 3 0 0 6 6

Total 20 40 21 81

CDFI	MFI	Total
Grade 1	20	28	5	53
Grade 2	0	12	10	22
Grade 3	0	0	6	6
Total	20	40	21	81

χ²= 35.27, P = 0.000. Note: CDFI, color Doppler flow imaging; MFI, micro-flow imaging.

3.2 Blood flow distribution

Take the position of initial enhancement of lesion during arterial phase in CEUS as a reference, the blood flow position shown by CDFI and MFI had the coincidence rate of 71.61% (58/81) and 88.89% (72/81) respectively. There was a statistically significant difference between the two (χ2 = 15.03, P = 0.000) (see Table 2).

Table 2
The blood flow distribution shown by MFI and CDFI in comparison with CEUS

Blood flow distribution in MFI

Blood flow distribution in CDFI Conformity Non-conformity Total

Conformity 57 1 58

Non-conformity 15 8 23

Total 72 9 81

	Blood flow distribution in MFI
Conformity	57	1	58
Non-conformity	15	8	23
Total	72	9	81

Note: MFI, micro-flow imaging. χ2 = 15.03, P = 0.000.

3.3 Blood flow morphology and its correlation with lesion type

The blood flow morphology of the 81 liver tumors in MFI is presented in Table 3. It can be seen from the table that the most common observed blood flow morphology in MFI for HCC was Type-III (21/48, 43.75%), i.e. the peripheral and central blood flow. For HEM, the blood flow morphology was mostly Type V (5/10, 50%) in MFI, displaying with a ring-like shape. For FNH, Type IV is the most common blood flow morphology in MFI (7/10, 70%). In the total 81 cases, 59 malignant cases (HCC and MET) were compared with 22 benign cases (HEM, ABS, and FNH), and the difference in blood flow morphology was statistically significant (χ2 = 8.993, P = 0.003).

Table 3
The blood flow morphology of 81 hepatic lesion in MFI

Blood flow morphology in MFI

Lesion Type I Type II Type III Type IV Type V Total

HCC 19 (39.6% /65.5%) 0 21 (43.8% /75.0%) 5 (10.4% /41.7%) 3 (6.2% /27.3%) 48 (100% /59.3%)

MET 4 (36.4% /13.8%) 1 (9.1% /100.0%) 3 (27.3% /10.7%) 0 3 (27.3% /27.3%) 11 (100% /13.6%)

FNH 0 0 3 (30.0% /10.7%) 7 (70.0% /58.3%) 0 10 (100% /12.3%)

HEM 4 (40.0% /13.8%) 0 1 (10.0% /3.6%) 0 5 (50.0% /45.5%) 10 (100% /12.3%)

ABS 2 (100% /6.9%) 0 0 0 0 2 (100% /2.5%)

Total 29 (35.8% /100%) 1 (1.2% /100%) 28 (34.6% /100%) 12 (14.8% /100%) 11 (13.6% /100%) 81 (100% /100%)

Blood flow morphology in MFI
HCC	19 (39.6% /65.5%)	0	21 (43.8% /75.0%)	5 (10.4% /41.7%)	3 (6.2% /27.3%)	48 (100% /59.3%)
MET	4 (36.4% /13.8%)	1 (9.1% /100.0%)	3 (27.3% /10.7%)	0	3 (27.3% /27.3%)	11 (100% /13.6%)
FNH	0	0	3 (30.0% /10.7%)	7 (70.0% /58.3%)	0	10 (100% /12.3%)
HEM	4 (40.0% /13.8%)	0	1 (10.0% /3.6%)	0	5 (50.0% /45.5%)	10 (100% /12.3%)
ABS	2 (100% /6.9%)	0	0	0	0	2 (100% /2.5%)
Total	29 (35.8% /100%)	1 (1.2% /100%)	28 (34.6% /100%)	12 (14.8% /100%)	11 (13.6% /100%)	81 (100% /100%)

Note: HCC, hepatocellular carcinoma; MET, metastasis; FNH, focal nodular hyperplasia; HEM, hemangioma; ABS, abscess; MFI, micro-flow imaging the numbers in the bracket represent the number of the current cell divided by the total number of the current row (left), the number of the current cell divided by the total number of the current column. χ²= 8.993, P = 0.003.

3.4 Blood flow status and its correlation with HCC subtypes

Blood flow status includes blood flow grade and morphology as described above. The correlation between blood flow status and HCC subtypes were further analyzed. According to the degree of pathological differentiation, all the 48 cases of HCC were further graded by Edmonson method. The Edmonson I-II classes were grouped as highly differentiated and the Edmonson III-IV classes were grouped as poorly differentiated. As a result, there were 28 highly-differentiated (Edmonson I-II) and 20 poorly-differentiated (Edmonson III-IV) lesions. MFI showed that there was a statistically difference in blood flow grade in the HCC masses with different degree of pathological differentiation (P = 0.038) (see Table 4, Fig. 4). There was no significant difference in the size of the mass and the blood flow morphology (P > 0.05).

Fig.4

Different pathological grades of HCC showed different blood flow grade in MFI. A and B present the first case with. HCC. The left MFI image showed blood flow in mass with grade 2; the right pathological examination confirmed the HCC tumor with Edmonson grade II, which is highly differentiated. C and D present the second case with HCC. The left MFI image showed blood flow in mass with grade 3; the right pathological examination confirmed the HCC tumor with Edmonson grade III, which is poorly differentiated.

Table 4

The characteristic of blood flow within tumors shown by MFI for highly and poorly differentiation HCC

Pathological grading (Edmondson)	n	Size	Blood flow distribution Grade 1/2/3	Blood flow morphology Type I /II/III/IV/V
Highly differentiated (I and II)	28	41.32±22.76	11/12/5	12/0/11/1/4
Poorly differentiated (III-IV)	20	54.35±25.73	3/7/10	7/0/10/2/1
P Value		P = 0.986	P = 0.038^*	P = 0.527

4 Discussion

Neovascularization is an important part of the tumor’s microenvironment and the basis for tumor growth. The distribution of blood flow within the tumor plays an important role in the differential diagnosis of tumors [15]. The traditional CDFI technology is a simple, economical method for clinical assessment of tumor blood supply. However, CDFI examination is angularly dependent and has a low signal-to-noise ratio. It can solely show the blood vessels with a wide diameter (>1 mm) and a high flow rate (>3∼5 cm/s). When the tissue motion artifacts were eliminated by the filter wall, the small blood flow with clinical information of the lesion may be simultaneously filtered out as well [16, 17].

CEUS that has emerged in recent years is the most sensitive tool to determine the microcirculatory perfusion of liver tumors and can clearly show the distribution of nourishing blood vessels in liver tumors [18, 19]. Unlike CT and MRI contrast agents, SonoVue is a blood pool contrast agent. Contrast agent microbubbles do not enter the intercellular matrix through the vascular endothelium. Therefore, the enhanced part of the mass in CEUS can reliably describe neovascularization in the tumor [20]. However, CEUS is an invasive examination that requires injection of contrast agent, which is expensive and less acceptable to patients. Moreover, since contrast agents have the risk of allergy, whether the patient can do CEUS will also depend on his physiological condition.

MFI technology is a novel vascular imaging technology. Different from traditional CDFI and power Doppler imaging which employ a wall filter to remove tissue noise, MFI incorporates a novel spatial-temporal filter, which analyzes Doppler signal to separate tissue clutter from low-speed and micro blood flow. Thus, MFI can improve spatial resolution, enhance vessel visualization, and reduce noise without using contrast agents. The tiny blood vessels which are difficult to be found in CDFI and can be easily detected in MFI are what we wish to analyze in this study.

In this study, 21 (21/81, 25.9%) liver tumors were shown with blood flow of grade 3 during the MFI examination, whereas only 6 cases (6/81, 7.4%) of them were detected by using CDFI. Higher sensitivity for micro and low velocity blood flow with MFI has been proven in comparison with CDFI. We then took the position of enhancement during the arterial phase of CEUS as a reference. The coincidence rate between MFI and CEUS in terms of blood flow distribution was 88.89% (72/81), which was better than 71.61% (58/81) for CDFI. This confirmed that the blood flow displayed in MFI has higher consistency with CEUS.

Moreover, the morphology of blood flow in MFI is easier to be identified than it is in CDFI, which can add value to the diagnosis of some liver tumors. The typical manifestation of blood flow for hepatic FNH is the radial color flow with a low resistance index in the center of the lesion. This type of blood flow is highly specific for the diagnosis of FNH [21, 22]. It is however reported that CDFI can only show 30% to 40% of FNH with such morphology [23]. In this study, 70% (7/10) hepatic FNH on the MFI showed radial blood flow in the center of the lesion, which was better than the 30% display rate (3/10) of CDFI. This result further confirms the fact that MFI can better display the low-velocity and micro blood flow than CDFI. Moreover, MFI could be more helpful for the diagnosis of FNH, as it presents more clearly the radial blood flow distribution within lesions.

Studies have shown that there is a significant difference in the blood flow morphology between hepatic malignant tumors (HCC and MET) and benign cases (HEM, ABS, FNH) in MFI. In this study, HCC is the most common hepatic malignancy. In CEUS, it performs as a rich blood supplied tumor, with distorted, irregular and unevenly distributed blood flow around and in the center. MFI confirms that by showing Type-III, i.e. the central and peripheral type, is the most common morphology of blood flow for HCC (21/48, 43.75%). Different from HCC, there is only 1 case (10.00%) in the 10 HEM tumors presented with Type-III blood flow in MFI.

There is a consensus that the carcinogenesis process of HCC is a multi-stage process. When a cirrhotic nodule is becoming HCC, hemodynamic changes will occur within the nodule. The changes include a decrease in the original normal hepatic arterial and portal vein structure, replaced by new blood vessels. In addition, the higher the degree of malignancy of the nodule is, the more neovascularity accumulated within the nodule [24, 25]. In this study, different blood flow grade can be detected by MFI with different HCC differentiation. For poorly differentiated (III-IV) HCC, MFI showed more abundant vascular information with 50.0% of grade 3, which is significantly greater than that of highly differentiated (I-II) (17.85%) (P = 0.018). However, different from previous studies, there is no statistically significant difference in the blood flow morphology with different HCC subtypes. The reasons include: i) the previous studies are based on the imaging technique of CEUS, which requires the injection of contrast agent and shows the blood vessels after a flash with high-transmission power ultrasound exposure, ii) the setting of blood flow morphology including their description and classification is different from previous studies [26]. Nevertheless, it should be noted that benign and malignant liver tumors may show the same morphological type of blood flow in MFI. For example 27.27% (3/11) of MET and 50.00% (5/10) of HEM share the same type V, i.e. the ring-like blood flow. Therefore, when a focal liver mass manifests as a certain type of blood flow morphology in MFI, a comprehensive analysis must be combined with clinical history and other imaging modalities for differential diagnosis.

There are still some limitations in this study. First, the number of cases studied, especially benign cases, is small. More cases need to be supplemented to evaluate the value of MFI in the differentiation of benign and malignant tumors. Second, study on the relationship between the blood flow status of liver tumors and the micro vessel density in pathological examination will be conducted, with more cases in the future.

In conclusion, this study shows that MFI technology can evaluate the blood flow of liver tumors more effectively compared to conventional CDFI. Different blood flow status can be observed with benign and malignant liver tumors, as well as with different stages of hepatic malignancy. It is expected that MFI will play a role in the differential diagnosis of liver tumors and evaluation of therapeutic effects after local treatment in the future.

Conflict of interest

We declare that we have no conflict of interest.

Footnotes

Acknowledgements

We would like to thank Zhouye Chen and Wei Guo a lot for their assistance in the preparation of the manuscript. This work was supported by the following funding: Shanghai Natural Science Foundation (grant number: 19ZR1450700) and National Natural Science Foundation of China (grant number: 81571676) and Medical Leading Talent Fund of Shanghai.

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	Blood flow distribution in MFI
Blood flow distribution in CDFI	Conformity	Non-conformity	Total
Conformity	57	1	58
Non-conformity	15	8	23
Total	72	9	81

Blood flow morphology in MFI
Lesion	Type I	Type II	Type III	Type IV	Type V	Total
HCC	19 (39.6% /65.5%)	0	21 (43.8% /75.0%)	5 (10.4% /41.7%)	3 (6.2% /27.3%)	48 (100% /59.3%)
MET	4 (36.4% /13.8%)	1 (9.1% /100.0%)	3 (27.3% /10.7%)	0	3 (27.3% /27.3%)	11 (100% /13.6%)
FNH	0	0	3 (30.0% /10.7%)	7 (70.0% /58.3%)	0	10 (100% /12.3%)
HEM	4 (40.0% /13.8%)	0	1 (10.0% /3.6%)	0	5 (50.0% /45.5%)	10 (100% /12.3%)
ABS	2 (100% /6.9%)	0	0	0	0	2 (100% /2.5%)
Total	29 (35.8% /100%)	1 (1.2% /100%)	28 (34.6% /100%)	12 (14.8% /100%)	11 (13.6% /100%)	81 (100% /100%)

Assessment of blood flow in the hepatic tumors using non-contrast micro flow imaging: Initial experience

Abstract

PURPOSE:

MATERIALS AND METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1 Introduction

2 Patients and methods

2.1 Patients

2.2 Examination method

2.3 Image analysis

3 Results

3.1 Blood flow grade

Table 1 The blood flow grades of 81 hepatic lesions with CDFI and MFI CDFI MFI Total Grade 1 Grade 2 Grade 3 Grade 1 20 28 5 53 Grade 2 0 12 10 22 Grade 3 0 0 6 6 Total 20 40 21 81

Table 2 The blood flow distribution shown by MFI and CDFI in comparison with CEUS Blood flow distribution in MFI Blood flow distribution in CDFI Conformity Non-conformity Total Conformity 57 1 58 Non-conformity 15 8 23 Total 72 9 81

Conflict of interest

Footnotes

Acknowledgements

References

Table 1
The blood flow grades of 81 hepatic lesions with CDFI and MFI

CDFI MFI Total

Grade 1 Grade 2 Grade 3

Grade 1 20 28 5 53

Grade 2 0 12 10 22

Grade 3 0 0 6 6

Total 20 40 21 81

Table 2
The blood flow distribution shown by MFI and CDFI in comparison with CEUS

Blood flow distribution in MFI

Blood flow distribution in CDFI Conformity Non-conformity Total

Conformity 57 1 58

Non-conformity 15 8 23

Total 72 9 81