Xiaoyu Huang

The histopathological growth patterns (HGPs) of liver metastases (LMs) are independently associated with the long-term prognosis of the primary tumor, with different HGPs predicting different patient outcomes and clinical treatment decisions. Non-invasive imaging biomarkers for stratification of HGPs are beneficial for treatment monitoring, evaluation of efficacy, and prognosis prediction of LMs. This review describes the state of research regarding computed tomography (CT), magnetic resonance imaging (MRI), and radiomics imaging biomarkers for LM-HGPs; discusses the advantages of CT, MRI, and radiomics for classification of LM-HGPs; and provides a reference for the stratification of LM-HGPs. Finally, the difficulties and deficiencies of CT, MRI, and radiomics in LM-HGP research are summarized along with the proposed directions for future research. Graphical abstract

Spontaneous intracerebral hemorrhage (ICH) has high morbidity and mortality. Computed tomography (CT) plays an important role in the diagnosis, treatment, and research of cerebrovascular diseases. Non-contrast CT is widely used in the clinical diagnosis of ICH because of its high imaging speed and high sensitivity and specificity in the detection of stroke. Many markers-based CT imaging, quantitative parameters, and artificial intelligence (AI) methods based on CT are increasingly used for the prediction of hematoma expansion (HE), prognosis of ICH, and the evaluation of perihematomal edema (PHE). Therefore, we performed a comprehensive review of studies, focusing on current research evidence related to CT use for the prediction of HE and prognostic. This review discusses recent insights into, outlines current limitations, and puts forward suggestions for the challenges and directions of future research. Although at present the prognosis for ICH is not optimistic, the treatment methods remain controversial. However, identifying imaging markers that can evaluate and predict existing possible existing therapeutic targets could help to provide individualized advice for patients and achieve patient risk stratification, which is a key step in improving treatment outcomes.

Energy spectrum computed tomography (CT) has become a promising approach for the differential diagnosis of tumor subtypes. To explore the value of energy spectrum CT parameters in the differential diagnosis of high-grade clear cell renal cell carcinoma (ccRCC) and type II papillary renal cell carcinoma (pRCC). Forty-two cases of high-grade ccRCC and 28 cases of type II pRCC were retrospectively reviewed. All region of interest (ROI) measurements were maintained consistently between the two-phase contrast-enhanced examinations. The ROIs encompassed as much of the enhancing areas of the lesions as possible. Energy spectrum CT parameters of all cases, including the 70 keV (HU) value, normalized iodine concentration (NIC), and energy spectrum curve slope were recorded by two radiologists with over 10 years of experience in abdominal CT diagnosis. In the cortical phase (CP) and parenchymal phase (PP), the 70 keV (HU) value, NIC, and slope value of the energy spectrum curve of high-grade ccRCC were significantly higher than those of type II pRCC. In the CP, NIC showed the highest differential diagnosis efficiency for the two group tumors, with a sensitivity of 78.9% and a specificity of 77.0%. There was no statistical difference in tumor hemorrhage, tumor envelope, tumor morphology, tumor border, lymph node metastasis, embolism, renal pelvis invasion, or tumor calcification between the two tumor types. However, there was significant difference in the number of tumors (P = 0.019). Energy spectrum CT parameters are valuable for the differential diagnosis of high-grade ccRCC and type II pRCC.

Background: Anti-angiogenic drugs have become a research hotspot in recent years. However, dynamically observing their therapeutic effect at different time points during treatment is a clinical problem. Purpose: To explore the feasibility of the quantitative parameters of spectral computed tomography (CT) in evaluating the anti-angiogenic effect of bevacizumab on rat C6 glioma. Material and Methods: Twenty-six male Sprague-Dawley rats were used to establish the C6 glioma model. The rats were randomly divided into the experimental group (n = 13) and control group (n = 13). The experimental group was intraperitoneally injected with 0.2 µL/g bevacizumab every day, whereas the control group was injected with the same dose of normal saline every day for one week. Spectral CT scanning was performed on the 4th and 8th days after treatment; meanwhile, the brain tissues were collected by heart perfusion for H&E staining, and VEGF and HIF-1α immunohistochemical staining. Results: On the 4th and 8th days, significant differences in the 70-keV single-energy CT value, slope of the energy spectrum curve, and iodine concentration were found between the experimental group and the control group. Correlation analysis between immunohistochemistry and quantitative parameters of spectral CT showed that the single energy CT value of 70 keV, slope of the energy spectrum curve, and concentration of iodine were positively correlated with VEGF and HIF-1α at different time points in the experimental group and the control group. Conclusion: Spectral CT multi-parameter imaging can be employed as a new method to evaluate the anti-angiogenic effect of bevacizumab on rat C6 glioma.

Computed tomography (CT) image features of chromophobe renal cell carcinoma (ChRCC) and papillary renal cell carcinoma (PRCC) are, occasionally, sometimes difficult to identify. However, spectral CT might provide quantitative parameters to differentiate them. To differentiate between ChRCC and PRCC with quantitative parameters using spectral CT. Forty cases of RCC confirmed with pathological tests were analyzed retrospectively (27 cases of PRCC and 13 cases of ChRCC). All patients underwent non-enhanced CT and dual-phase contrast-enhanced CT scans. For each lesion, the CT value of monochromatic images as well as iodine and water concentrations were measured, and the slope of spectrum curve was calculated. Data were analyzed using Student’s t-test. Sensitivity and specificity of the quantitative parameters were analyzed using the receiver operating characteristic (ROC) curve. During the cortex phase (CP) and parenchyma phase (PP), the CT value and slope of spectrum curve of ChRCC were higher than those of PRCC, and significant differences were observed at low energy levels (40–70 keV). Normalized iodine concentration of ChRCC and that of PRCC was significantly different during CP and PP (P < 0.05). The water (iodine) concentrations of ChRCC and PRCC in CP and PP were not statistically different (P > 0.05). All the ROCs for parameters were above the reference line. Spectral CT may help increase the diagnostic accuracy of differentiating PRCC from ChRCC using a quantitative analysis.

To examine the value of spectral CT quantitative parameters in gastrointestinal stromal tumor (GIST) risk classification.

Glioma is the most common neoplasm that is neuroepithelial in nature. However, Spectral computed tomography (CT) has rarely been reported to detect angiogenesis in tumors. To investigate the value of multi-parameter spectral CT for the detection of angiogenesis in C6 glioma in rats. Fifteen male Wistar rats were seeded with C6 glioma cells in the right basal ganglia and spectral CT-enhanced scanning was performed at days 7, 10, and 14 after the C6 glioma cells were seeded. The spectral CT parameters were measured in three areas: the solid tumor; the peritumoral area; and the contralateral mirror area. After different periods of scanning, the rats’ brain tissue was stained with HE and CD105 immunohistochemical staining. Different periods of spectral CT quantitative parameters and pathological images were analyzed. The spectral CT parameter and CD105 among the solid tumor, peritumoral area, and contralateral mirror area were significantly different: monochromatic CT value (211.30 ± 34.67 HU, 119.16 ± 13.31 HU, and 55.59 ± 7.87 HU, P < 0.001); CD105 (16.14 ± 1.91, 6.79 ± 1.31, and 2.50 ± 0.51, P < 0.001); spectral curve slope (10.35 ± 1.89, 5.33 ± 0.87, 0.88 ± 0.26, P < 0.001); iodine (water) value (49.75 ± 9.02, 26.04 ± 4.32, 4.36 ± 1.18, P < 0.001). CD105 correlated strongly with the CT value at 65 keV (correlation coefficient r = 0.98, P < 0.001). Multi-parameter spectral CT can reflect the formation of tumor angiogenesis in rat C6 glioma to a certain extent and can be used as an effective means to evaluate glioma.