A dual-input four-compartment model for the assessment of hepatocellular carcinoma in dynamic PET / CT images

Abstract

The present invention relates to a dual-input four-chamber model for the evaluation of dynamic PET / CT imaging of hepatocellular carcinoma. The present invention collects HCC dynamic PET / CT data for pathological diagnosis, including 5 minutes of dynamic data supplemented by 1 minute of static data 60 minutes after injection and a single 5 minutes of dynamic data; secondly, the tracer time-radioactivity curve data of normal liver tissue, hepatic artery, portal vein, and hepatocellular carcinoma are extracted from the PET / CT images; then the gravitational search algorithm is used to solve the kinetic parameters of the liver 4-chamber model; finally, the correlation between the kinetic parameters K1~k3 of the two time groups and the difference in the tracer kinetic parameters of the hepatocellular carcinoma tissue image and the surrounding healthy liver tissue image are analyzed and compared, and compared with the commonly used liver 3-chamber model kinetic parameters, the present invention can better characterize the metabolism of HCC and normal liver tissue, and has certain value for clinical auxiliary diagnosis of HCC.

Description

Technical Field

[0001] The invention relates to an evaluation method for hepatocellular carcinoma using a dual-input four-chamber model in dynamic PET / CT images, and belongs to the technical field of liver cancer auxiliary diagnosis. Background Art

[0002] Positron emission tomography (PET) / computed tomography (CT) is an effective noninvasive functional imaging modality for the diagnosis and evaluation of HCC. 18 F-fluoro-2-deoxyglucose( 18 F-FDG) is the most commonly used radiotracer in PET / CT to measure glucose metabolism in tissues. Recent studies have shown that 18 F-FDG6P can enter the endoplasmic reticulum (ER) through the glucose-6-phosphate transporter (G6PT), where it is hydrolyzed to produce free 18 F-FDG is further released into the cytoplasm. In in vitro experiments with mouse breast cancer cells, some researchers proposed a four-compartment model with ER, confirming that ER 18 F-FDG plays a key role in HCC metabolism. Therefore, the present invention uses the early 5-minute dynamic data supplemented by the 1-minute static PET / CT data 60 minutes after injection to more accurately evaluate HCC kinetic parameters through a 4-compartment model with ER. Summary of the invention

[0003] The present invention provides a dual-input four-chamber model for dynamic PET / CT imaging of hepatocellular carcinoma evaluation method, the present invention uses early 5 minutes of dynamic data supplemented by 1 minute of static PET / CT data 60 minutes after injection, and improves the reliability of hepatocellular carcinoma PET / CT imaging dynamic parameter evaluation through a 4-chamber model with ER.

[0004] The technical solution of the present invention is: a dual-input four-chamber model for dynamic PET / CT imaging of hepatocellular carcinoma evaluation method, the specific steps of the method are as follows:

[0005] Step 1. Extract tracer time-radioactivity curve data of normal liver tissue images, hepatic artery, portal vein, and hepatocellular carcinoma images from PET / CT imaging of hepatocellular carcinoma patients, including 5-minute dynamic data supplemented by 1-minute static data 60 minutes after injection and single 5-minute dynamic data;

[0006] Step 2. The gravitational search algorithm was used to estimate the kinetic parameters of the liver 4-compartment kinetic model. The kinetic parameters of the 5-minute dynamic data supplemented with the 1-minute static data 60 minutes after injection and the single 5-minute dynamic data in the liver 4-compartment kinetic model were analyzed. The correlation between the kinetic parameters of the two time groups and the difference in the tracer kinetic parameters between the hepatocellular carcinoma tissue images and the surrounding healthy liver tissue images were compared.

[0007] In Step 2, the liver 4-compartment kinetic model includes the following:

[0008] Hepatic artery 18 F-FDG concentration A(t) and portal vein 18 F-FDG concentration P(t), hepatic artery perfusion index HPI, considering the effect of dual blood supply in the liver, 18 F-FDG concentration C B (t) is expressed as:

[0009] C B (t)=HPI×A(t)+(1-HPI)×P(t) (1)

[0010] C E (t) indicates the free state in liver tissue 18 F-FDG concentration; C M (t) indicates phosphorylation in liver tissue 18 F-FDG-6-phosphate concentration; C R (t) indicates ER 18 F-FDG-6P concentrations, K1 and k2 are 18 The rate constant of F-FDG transport from blood to tissue and from tissue back to blood; k3 is 18 F-FDG is phosphorylated to 18 The rate constant (HK) of F-FDG6P; k5 is 18 The import rate of F-FDG6P into the ER; k6 refers to 18 F-FDG6P to 18 Dephosphorylation rate of F-FDG; t = time frame;

[0011] The four-compartment kinetic model of the liver is equivalently described by a set of ordinary differential equations (ODE):

[0012]

[0013] in,

[0014]

[0015] Solving the following relationship:

[0016]

[0017] C T (t) is the output function of the liver four-compartment kinetic model, which is the curve of the tracer concentration in the tissue measured by PET / CT images over time; where:

[0018] α1=V i +(1-v r )(1-V b -V i ) (5)

[0019] α2=(1-v r )(1-V b -V i ) (6)

[0020] α3=v r (1-V b -V i ) (7)

[0021]

[0022] V b 、V i Represent the volume fractions of blood and tissue fluid respectively, and v represents the volume ratio of endoplasmic reticulum and cytoplasm in the cell.

[0023] The beneficial effects of the present invention are as follows: the present invention adopts a dual-input four-chamber model for the evaluation of dynamic PET / CT imaging of hepatocellular carcinoma, and the obtained kinetic parameters can provide biological insights related to radioactive drug targets and disease processes, and the reliability of the evaluation of kinetic parameters of hepatocellular carcinoma PET / CT imaging is improved by using a four-chamber model with ER. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flow chart of the present invention;

[0025] Figure 2 This is a diagram of the four-chamber model of the liver of the present invention. DETAILED DESCRIPTION

[0026] Example 1: Figure 1-Figure 2 As shown, the present invention provides a dual-input four-chamber model for dynamic PET / CT imaging of hepatocellular carcinoma evaluation method, the patient data used are as follows: the patient data is provided by the PET / CT center of the First People's Hospital. A total of 24 case data of 21 HCC patients are included. Written informed consent is obtained from all patients; the steps of the method are as follows:

[0027] Step 1. Extract tracer time-radioactivity curve data of normal liver tissue images, hepatic artery, portal vein, and hepatocellular carcinoma images from PET / CT imaging of hepatocellular carcinoma patients, including 5-minute dynamic data supplemented by 1-minute static data 60 minutes after injection and single 5-minute dynamic data;

[0028] Specifically, the PET / CT scanning protocol used in the present invention is as follows: All examinations were performed using a Philips Ingenuity TF PET / CT scanner (Cleveland, OH, USA), and image processing was performed using the workstation Philips IntelliSpace Portal v7.0.4.20175. Dynamic PET / CT scanning was performed after the patient fasted for at least 6 hours and blood glucose was verified. A low-dose liver CT scan (120 kV, 100 Ma) was first performed for attenuation correction and image fusion. 5.5 MBq / kg was injected intravenously 18 After F-FDG, a dynamic PET scan was performed in the liver region for 5 minutes. The dynamic PET data sampling protocol was divided into 16 frames: 12 × 5 seconds and 4 × 60 seconds, and the dynamic PET images were reconstructed using the standard ordered subset expectation maximization (OSEM) algorithm. Then, 60 minutes after the injection, a conventional whole-body static scan was performed, including 11 beds from the skull to the proximal thigh, with each bed scanned for 1 minute.

[0029] Regions of interest (ROIs) were manually drawn in the CT images of each patient, including HCC, background liver tissue, aorta, and portal vein, and manually adjusted slice by slice. After image fusion, the ROIs were copied to the PET images, and a time-activity curve (TAC) consisting of the maximum SUV (SUVmax) extracted from each frame was generated.

[0030] Step 2, the gravitational search algorithm was used to estimate the kinetic parameters of the liver 4-compartment kinetic model. The kinetic parameters of the 5-minute dynamic data supplemented with 1-minute static data 60 minutes after injection and the single 5-minute dynamic data in the liver 4-compartment kinetic model were analyzed. The correlation between the kinetic parameters of the two time groups and the difference in the tracer kinetic parameters of hepatocellular carcinoma tissue images and surrounding healthy liver tissue images were compared. The dual-input functional four-compartment model with endoplasmic reticulum (4C model) can be used for kinetic modeling of 18F-FDG PET / CT dynamic data of the liver;

[0031] Specifically, the hepatic artery 18 F-FDG concentration A(t) and portal vein 18 F-FDG concentration P(t), hepatic artery perfusion index HPI, considering the effect of dual blood supply in the liver, 18 F-FDG concentration C B(t) is expressed as:

[0032] C B (t)=HPI×A(t)+(1-HPI)×P(t) (1)

[0033] C E (t) indicates the free state in liver tissue 18 F-FDG concentration; C M (t) indicates phosphorylation in liver tissue 18 F-FDG-6-phosphate ( 18 F-FDG6P) concentration; C R (t) indicates ER 18 F-FDG-6P concentration (all concentrations are measured in kBq / ml). K1 and k2 are 18 The rate constant for the transport of F-FDG from blood to tissues and from tissues back to blood (via GLUT); k3 is 18 F-FDG is phosphorylated to 18 The rate constant (HK) of F-FDG6P; k5 is 18 The import rate of F-FDG6P into the ER (calculated as G6PT); k6 refers to 18 F-FDG6P to 18 Dephosphorylation rate of F-FDG (by G6Pase), t = time frame.

[0034] The four-compartment kinetic model of the liver is equivalently described by a set of ordinary differential equations (ODE):

[0035]

[0036] in,

[0037]

[0038] Solving the following relationship:

[0039]

[0040] C T (t) is the output function of the liver four-compartment kinetic model, which is the curve of the tracer concentration in the tissue measured by PET / CT images changing with time.

[0041] α1=V i +(1-v r )(1-V b -V i ) (5)

[0042] α2=(1-v r )(1-V b -Vi ) (6)

[0043] α3=v r (1-V b -V i ) (7)

[0044]

[0045] V b 、V i Represent the volume fractions of blood and tissue fluid respectively, and v represents the volume ratio of endoplasmic reticulum and cytoplasm in the cell.

[0046] The parameter estimation results of the model are calculated using the gravitational search algorithm (GSA).

[0047] Results analysis: The present invention used MedCalc version 13.0.0.0 (MedCalc software, Ostend, Belgium) for statistical analysis. Parameter results are expressed as mean ± standard deviation. Independent sample t test was used to compare the estimated parameters between HCC and background liver tissue, and P < 0.05 indicated a significant difference. At the same time, the Pearson coefficient was used to evaluate the parameter correlation of different time group data in the 4C model.

[0048] Table 1. Kinetic parameters estimated by 4C model and 3C model

[0049]

[0050] In the 4-compartment model (liver 4-compartment kinetic model), K1 and k2 of HCC were higher than those of background liver tissue (P=0.005, P=0.019). Similarly, k3 and HPI of HCC were also higher than those of background liver tissue (P=0.003, P<0.001). It is worth noting that k5 of HCC was higher than that of background liver tissue (P=0.036). k6 of HCC was lower than that of background liver tissue (P<0.001). V b There were significant differences between HCC and background liver tissues (P=0.001). i , v were higher than those in the background liver tissue, but there was no significant difference (P=0.484, P=0.260).

[0051] In the 3-compartment model, K1, k2, HPI, and V b The k4 was lower than that of normal liver tissue (P<0.001). There was no significant difference in k3 between HCC and background liver tissue (P=0.127).

[0052] Table 2 summarizes the results of correlation analysis between the kinetic parameters calculated using the 4C model for 5-minute dynamic data supplemented with 1-minute static data at 60 minutes after injection and single 5-minute dynamic data. A strong correlation was observed between K1 and k2 in different time groups (P<0.001, P<0.001); k3 and k5 showed a strong correlation (P=0.007, P=0.043); but the correlation of k6 in the two time groups was poor. The results showed that some kinetic parameters of single 5-minute dynamic data can effectively distinguish HCC from healthy background liver tissue.

[0053] Table 2. Correlation of kinetic parameters in different time groups

[0054]

[0055] The specific implementation modes of the present invention are described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above implementation modes, and various changes can be made within the knowledge scope of ordinary technicians in this field without departing from the purpose of the present invention.

Claims

1. A dual-input four-chamber model for the evaluation of hepatocellular carcinoma in dynamic PET / CT imaging, characterized by: The specific steps of the method are as follows: Step 1. Extract tracer time-radioactivity curve data of normal liver tissue images, hepatic artery, portal vein, and hepatocellular carcinoma images from PET / CT imaging of hepatocellular carcinoma patients, including 5-minute dynamic data supplemented by 1-minute static data 60 minutes after injection and single 5-minute dynamic data; Step 2, the gravitational search algorithm was used to estimate the kinetic parameters of the liver 4-compartment kinetic model. The kinetic parameters of the 5-minute dynamic data supplemented with the 1-minute static data 60 minutes after injection and the single 5-minute dynamic data in the liver 4-compartment kinetic model were analyzed. The correlation between the kinetic parameters of the two time groups and the difference in the tracer kinetic parameters between the hepatocellular carcinoma tissue images and the surrounding healthy liver tissue images were compared. In Step 2, the liver 4-compartment kinetic model includes the following: Hepatic artery 18 F-FDG concentration A(t) and portal vein 18 F-FDG concentration P(t), hepatic artery perfusion index HPI, considering the effect of dual blood supply in the liver, 18 F-FDG concentration C B (t) is expressed as: C B (t)=HPI×A(t)+(1-HPI)×P(t) (1) C E (t) indicates the free state in liver tissue 18 F-FDG concentration; C M (t) indicates phosphorylation in liver tissue 18 F-FDG-6-phosphate concentration; C R (t) indicates ER 18 F-FDG-6P concentrations, K1 and k2 are 18 The rate constant of F-FDG transport from blood to tissue and from tissue back to blood; k3 is 18 F-FDG is phosphorylated to 18 The rate constant (HK) of F-FDG6P; k5 is 18 The import rate of F-FDG6P into the ER; k6 refers to 18 F-FDG6P to 18 Dephosphorylation rate of F-FDG; t = time frame; The four-compartment kinetic model of the liver is equivalently described by a set of ordinary differential equations (ODE): in, Solving the following relationship: C T (t) is the output function of the liver four-compartment kinetic model, which is the curve of the tracer concentration in the tissue measured by PET / CT images over time; where: α1=V i +(1-v r )(1-V b -V i ) (5) α2=(1-v r )(1-V b -V i ) (6) α3=v r (1-V b -V i ) (7) V b 、V i Represent the volume fractions of blood and tissue fluid respectively, and v represents the volume ratio of endoplasmic reticulum and cytoplasm in the cell.

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