Conclusiones

Liver cancer is a type of malignant tumour. There are two types of malignant (Reynolds,

2001). First, primary liver cancer, where tumours have originated in the liver. Second, metastatic secondary liver cancer, where tumours spread from cancer sites elsewhere

in the body such as lung, colon, and breast. As listed in Table 2.3 (Moreira, 2015;

Garrean et al.,2008;Robinson,2000;Al-Salem,2014;Reynolds,2001)

Malignant tumour in early stage often does not cause symptoms until it has reached an advanced stage. So many cases are diagnosed fairly late. Liver cancer treatment is determined by tumour characteristics such as number, size, and location in the liver; tumour effect on liver functions or cause cirrhosis and/or tumour has spread outside the liver.

Malignant lesion Outline

Hepatocellular carcinoma (HCC)

• Most common type of primary liver cancer. • 75% people with cancer have HCC disease. • HCC can start as a single tumour or as multi-

ple tumours through the liver.

• Multiple sites are more common than single tumour.

(Davis et al.,2008;Zviniene,2012)

Cholangiocarcinoma

• Start in the bile ducts of the liver.

• 10-20% people have liver cancer diagnosed as Cholangiocarcinoma.

(Iwatsuki et al.,1998)

Hemangiosarcoma

• Rare type of liver cancer; Begins in the blood vessels of the liver;

• Grows quickly. • Diagnosed fairly late.

(Rademaker et al.,2000a)

Hepatoblastoma

• Very rare type of liver cancer.

• Usually seen in children under 4 year’s age. (Schnater et al.,2003;Faraj et al.,2008)

Table 2.3: Types of malignant tumour. Hepatocellular carcinoma (HCC)

Hepatocellular carcinoma (HCC), also called malignant hepatoma is a primary common liver cancer. Most cases of HCC are due to either a viral hepatitis infection or cirrhosis (alcoholism being the most common cause of hepatic cirrhosis) (Davis et al.,

Chapter 2. Research Background

could be seen focal, multifocal or diffuse. US, CT and MRI are used to diagnose HCC but the CT and MRI is better than US in detection. However, in some cases, the biopsy is required for diagnostic accuracy.

Cholangiocarcinoma

Cholangiosarcoma is a second common primary malignant tumour of bile duct that accounts approximately 10-20% of all primary liver cancer (Reddy and Faust,

2005; Khan et al., 2005). The Cholangiocarcinoma is characterised on CT and MRI as irregular shape with peripheral enhancement in portal phase (Blechacz and Gores,

2008).

Hemangiosarcoma

Hemangiosarcoma is a rare metastases malignant liver lesion that usually occurs with no symptoms in elderly men (Rademaker et al.,2000b). The Hemangiosarcoma originates in spleen and often spreads to the liver and lung. The most important of hemangiosarcoma characteristic is an aggressive lesion, grows quickly and effects on blood vessels (Shoemaker et al.,2016).

Hepatoblastoma

Hepatoblastoma is another type of malignancy tumour of fetal hepatocytes, which is the most frequent in children and infants (Schnater et al., 2003). Usually, the right lobe is affected more than left lobe with no symptoms (Davenport et al., 2012). The treatment is made by Surgical tumour removal or liver transplantation (Ang et al.,

2007).

The next section will introduce our dataset, experimental setup and evaluation ma- trices that used in this thesis.

2.4

Dataset and Evaluation Measurements

In this section, we will first present the datasets used in this thesis. Furthermore, we introduces the evaluation measurements that will be used to evaluate the proposed framework for liver segmentation, lesion detection, vessels extraction and also liver lesion classification/characterisation.

2.4.1

Datasets

In order to provide a rigorous evaluation and benchmarking of the proposed frame- work, the following two datasets (patients anonymised) were used during experiments:

1. Dataset I, obtained from ImageClef (Marvasti et al.,2015).

The overall dataset comprises of two datasets, collected from two different institutions with a total number of 174 CT scan images and divided into 80 cases malignant (34 case HCC and 46 case Metastases) and 94 cases benign (56 case Cysts and 38 case Haemangiomas), as presented in Figure2.8.

Figure 2.8: The overview of the dataset size; (a) Split dataset based on the lesion category (Malignant/ Benign); (b) Split dataset based on the lesion types (Cysts, Hae- mangiomas, HCC, Metastases).

2.4.1.1 Dataset I

The dataset I is given in ImageClef 2014 for liver CT annotation task (Marvasti et al.,

2015). a 50 3D abdominal CT scans acquired from 46 patient and divided into 29 cases malignant and 21 cases benign with total number of lesions 137. Among the 50 CT scans, 98 lesion is malignant, while 39 lesion is benign. The dataset I contains four common types of liver lesions; two types are benign (14 case Cysts and 7 cases Haemangiomas) and two types are malignant (13 case HCC and 16 case Metastases) , as illustrated in Figure2.9.

Chapter 2. Research Background

Figure 2.9: The overview of the dataset I; (a) Split dataset based on the lesion cate- gory (Malignant/ Benign); (b) Split dataset based on the number of the lesions for each of benign and malignant; (c) Split dataset based on the lesion types (Cysts, Haeman- giomas, HCC, Metastases).

The CT images had varied resolutions (x: 190-308, y: 213-387) voxels in plane and contain between 41 and 588 slices depending on the field-of-view and the slice thickness. The slice thickness between 0.5 and 5 mm and the slice spacing varies from 0.674 to 1.007 mm.

The reference segmentation are available for the liver and lesions by ImageClef. In addition, the liver lesion characterisation are provided by a radiologist on each scan. The RadLex ontology (Mejino Jr et al.,2008) was used to characterise of the high-level features (semantic features) for the lesion annotation.

2.4.1.2 Dataset II

The dataset II is obtained from King Hussein Medical Centre, Amman, Jordan and the patient details is anonymised. The total number of lesions 328 obtained from 124 CT scan, acquired from 115 patient. Among the 328 lesions, 117 were benign while 211 were malignant. In overall, the 124 CT case divided into 51 case malignant and 73 case benign. The dataset II contains four common types of liver lesions; two types are benign (42 case Cysts and 31 case Haemangiomas) and two types are malignant (21 case HCC and 30 case Metastases) , as illustrated in Figure2.10.

Figure 2.10: The overview of the dataset II; (a) Split dataset based on the lesion cate- gory (Malignant/ Benign); (b) Split dataset based on the number of the lesions for each of benign and malignant; (c) Split dataset based on the lesion types (Cysts, Haeman- giomas, HCC, Metastases).

The dataset was composed of 76 men and 39 women who ranged in age from 24 to 86 years with mean age of 53.7 years. All scans were acquired between 2009 and 2016. The CT scan images have a resolution of 512x512 voxels in plane and contain between 159 and 482 slices depending on the field-of-view and the slice thickness. The slice thickness between 2 and 5 mm and the slice spacing varies from 0.65625 to 1 mm and the voxel size range from 0.6836 to 0.8789 mm.

All of the CT scans were acquired in triple phase. On each CT scan, the liver lesion detection and characterisation was provided by three experts radiologist, with more than 15 years experience based on RadLex ontology.