Application of quantitative imaging in oncologic management

Medical imaging, such as computed tomography （CT）, magnetic resonance imaging （MRI） and positron emissiontomography （PET）, plays a vital role for the decision-making in oncologic management. In clinical practice, imaging-derivedtumor metrics are routinely applied in oncologic management as an imaging biomarker. For example, the ResponseEvaluation Criteria in Solid Tumors （RECIST） are commonly used for tumor treatment response evaluation based on thedynamic changes in tumor size. However, the current cross-sectional images are interpreted qualitatively for lesioncharacterization, treatment response evaluation and prognostic prediction by highly trained radiologists, which hasincreasingly apparent limitations. Therefore, there is a demanding shift toward more quantitative imaging interpretation.

Low-dose computed tomography with 4th-generation iterative reconstruction algorithm in assessment of oncologic patients

AIM To compare radiation dose and image quality of lowdose computed tomography(CT) protocol combined with hybrid-iterative reconstruction algorithm with standarddose CT examinations for follow-up of oncologic patients. METHODS Fifty-one patients with known malignant diseases which underwent, during clinical follow-up, both standarddose and low-dose whole-body CT scans were enrolled. Low-dose CT was performed on 256-row scanner, with 120 kV and automated m A modulation, and iterative reconstruction algorithm. Standard-dose CT was performed on 16-rows scanner, with 120 kV, 200-400 m As(depending on patient weight). We evaluated density values and signal-to-noise ratio, along with image noise(SD), sharpness and diagnostic quality with 4-point scale.RESULTS Density values in liver, spleen and aorta were higher in lowdose images(liver 112.55 HU vs 103.90 HU, P < 0.001), as SD values in liver and spleen(liver 16.81 vs 14.41). Volumetric-Computed-Tomographic-Dose-Index(CTDIvol) and Dose-Length-Product(DLP) were significantly lower in low-dose CT as compared to standard-dose(DLP 1025.6 m Gy*cm vs 1429.2 m Gy*cm, P < 0.001) with overall dose reduction of 28.9%. Qualitative analysis did not reveal significant differences in image noise and diagnostic quality.CONCLUSION Automatic tube-current modulation combined with hybriditerative algorithm allows radiation dose reduction of 28.9% without loss of diagnostic quality, being useful in reducing dose exposure in oncologic patients.

Characterization of focal liver lesions with SonoVue~-enhanced sonography: International multicenter-study in comparison to CT and MRI

AIM： To evaluate in a multicenter study whether the sonographic characterization of focal liver lesions can be improved using SonoVue-enhancement; and to compare this method with computed tomography （CT） and magnetic resonance imaging （MRI）. METHODS： One hundred and thirty four patients withone focal liver lesion detected in baseline ultrasound （US） were examined with conventional US, contrastenhanced US （n = 134）, contrast-enhanced CT （n = 115） and/or dynamic contrast-enhanced MRI （n = 70）. The lesions were classified as malignant, benign or indeterminate and the type of lesion was determined. The final diagnosis based on the combined information of all imaging examinations, clinical information and histology （n = 32） was used. Comparisons were made to see whether the addition of contrast-enhanced US led to the improvement of the characterization of doubtful focal liver lesions.RESULTS： In comparison with unenhanced US, SonoVue markedly improves sensitivity and specificity for the characterization （malignant/benign） of focal liver lesions. In comparison with CT and/or dynamic MRI, SonoVue -enhanced sonography applied for characterization of focal liver lesions was 30.2% more sensitive in the recognition of malignancy and 16.1% more specific in the exclusion of malignancy and overall 22.9% more accurate. In the subgroup with confirmative histology available （n = 30）, sensitivity was 95.5% （CEUS）, 72.2% （CT） and 81.8% （MRI）, and specificity was 75.0% （CEUS）, 37.5% （CT） and 42.9% （MRI）. The sensitivity and specificity of CEUS for the identification of focal nodular hyperplasia （FNH） and hemangiomas was 100% and 87%, resulting in an accuracy of 94.5%.CONCLUSION： SonoVue-enhanced sonography emerges as the most sensitive, ost specific and thus most accurate imaging modality for the characterization of focal liver lesions.

Application of Dual-Energy Computed Tomography for Breast Cancer Diagnosis

The present study aimed to investigate the possibility of using dual-energy computed tomography (CT) before therapy to discriminate between normal breast tissue and tumor tissue in patients with breast cancer, without the need to use a contrast medium. The following patient data were extracted by interview and from the hospital’s radiology information system: height, weight, age, menstrual cycle, CT images of normal tissue and tumors with or without contrast medium, and the histopathological diagnosis of the aspiration biopsy. The median age of the 43 participants was 56 years (range, 30 - 80 years). The CT values were evaluated using a clinical analytical program based on the three-material decomposition technique. Breast cancer was classified into ductal carcinoma in situ, invasive ductal carcinoma, invasive lobular carcinoma, fibromatosis-like metaplastic carcinoma, and apocrine carcinoma. In all conditions, regardless of contrast medium, the CT values of tumor tissues were higher than those of normal breast tissue, indicating the effectiveness of dual-energy CT (DE-CT) in the diagnosis of breast cancer. By contrast, DE-CT showed limited potential for distinguishing ductal carcinoma in situ from invasive ductal carcinoma. There have only been a few reports regarding CT examination of breast cancer, and it is expected this study encourage the development of DE-CT imaging to improve tumor detection in patients with breast cancer.

18F-FDG PET/CT makes a significant contribution to diagnosis of malignancy in patients with cervical lymphadenopathy： a study using optimal scale regression tests

Background The specificity and precision of lymphadenopathy assessment using US, CT and MRI are generally unsatisfactory, while fluorodeoxyglucose-positron emission tomography/computed tomography （18F-FDG PET/CT） can support this process by providing additional information about the lymph node features. However, which image features of 18F-FDG PET/CT play the key role in the diagnosis and cutoffs of malignant cervical lymphadenopathy still needs to be determined by further studies. Our study aimed to identify 18F-FDG PET/CT abnormalities that would assist in making a reliable diagnosis of malignant cervical lymphadenopathy in enlarged cervical lymph nodes of patients with unknown primary diseases. Methods One hundred and ninety-one consecutive patients of cervical lymphadenopathy with unknown primary causes were examined by 18F-FDG PET/CT from May 2007 to October 2011 and a definite diagnosis was established by pathologic biopsy. 18F-FDG PET/CT images were evaluated to identify the relevant abnormalities. All image features were analyzed by optimal scale regression tests to determine the important factors that were predictive for the diagnosis of malignant cervical lymphadenopathy and the cutoffs. Results The factors studied in 18F-FDG PET/CT images for predicting malignant cervical lymphadenopathy were sex, age, node location, size, shape, margins, maximum standard uptake value （SUV）, mean SUV, FDG uptake pattern and number of nodes. It was found that mean SUV, maximum SUV, FDG uptake pattern, location, size and margins were the important risk factors of cervical lymph nodes that could predict malignant cervical lymphadenopathy. Signs of mean SUV〉2.5 （or maximum SUV〉3.5）, nodular FDG uptake pattern, location of IIA, III, IV, VB, VI and VII regions, size〉1.5 cm and vague margins had their optimal diagnostic accuracy （Ac） and Youden index （YI）, further, combination of any three factors of these six important risk factors would led to the best diagnosticAc of 96% and YI of 0.93. Conclusions Signs of mean SUV, maximum SUV, FDG uptake pattern, location, size and margins of node in ~SF-FDG PET/CT imaging are important predictive factors of malignant cervical lymphadenopathy. A combination of multiple factors may yield a higher diagnostic efficacy.