3D MR neurography with gadolinium contrast to improve the visualization of pelvic nerves and the branches.

Objective: To evaluate the effectiveness of 3D NerveVIEW sequence with gadolinium contrast on the visualization of pelvic nerves and their branches compared to that without contrast. Methods: Participants were scanned twice using 3D NerveVIEW sequence with and without gadolinium contrast to acquire pelvic nerve images. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and contrast ratio of the nerves were calculated and compared to determine the quality of images. To subjectively assess, using a 3-point scale, branch nerves critical to therapeutic decision-making, including the pelvic splanchnic nerve and pelvic plexus, the superior gluteal nerve, and the pudendal nerve. Results: In the 32 eligible participants after using contrast, the CNRs of the images of nerve-to-bone and nerve-to-vessel significantly increased (p < 0.05). The CR of the images with contrast of all nerve-to-surrounding tissues (i.e., bone, muscle, blood vessels, and fat) were also found significantly higher (p < 0.05). The assessment of observers also shows higher scores for images with contrast compared to images without contrast. Conclusion: The 3D NerveVIEW sequence combined with gadolinium contrast improved vascular suppression, increased the contrast between pelvic nerves and surrounding tissue, and enhanced the visualization of nerves and their branches. This study may be helpful for the technically challenging preoperative planning of pelvic diseases surgery.

Non-contrast enhanced MRI for efficiency evaluation of high-intensity focused ultrasound in adenomyosis ablation.

OBJECTIVE: To investigate the value of T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) in evaluating the therapeutic effect of high-intensity focused ultrasound (HIFU) in adenomyosis ablation. MATERIAL AND METHODS: One hundred eighty-nine patients with adenomyosis were treated with HIFU. The ablation areas on T2WI and DWI sequences were classified into different types: type I, relatively ill-defined rim or unrecognizable; subtype IIa, well-defined rim with hyperintensity; subtype IIb, well-defined rim with hypointensity. The volume of ablation areas on T2WI (VT2WI) and DWI (VDWI) was measured and compared with the non-perfused volume (NPV), and linear regression was conducted to analyze their correlation with NPV. RESULTS: The VT2WI of type I and type II (subtype IIa and subtype IIb) were statistically different from the corresponding NPV (p = 0.004 and 0.024, respectively), while no significant difference was found between the VDWI of type I and type II with NPV (p = 0.478 and 0.561, respectively). In the linear regression analysis, both VT2WI and VDWI were positively correlated with NPV, with R2 reaching 0.96 and 0.97, respectively. CONCLUSIONS: Both T2WI and DWI have the potential for efficient evaluation of HIFU treatment in adenomyosis, and DWI can be a replacement for CE-T1WI to some extent.

Identification of the predictive genes for the response of colorectal cancer patients to FOLFOX therapy.

BACKGROUND: Colorectal cancer is a malignant tumor with high death rate. Chemotherapy, radiotherapy and surgery are the three common treatments of colorectal cancer. For early colorectal cancer patients, postoperative adjuvant chemotherapy can reduce the risk of recurrence. For advanced colorectal cancer patients, palliative chemotherapy can significantly improve the life quality of patients and prolong survival. FOLFOX is one of the mainstream chemotherapies in colorectal cancer, however, its response rate is only about 50%. METHODS: To systematically investigate why some of the colorectal cancer patients have response to FOLFOX therapy while others do not, we searched all publicly available database and combined three gene expression datasets of colorectal cancer patients with FOLFOX therapy. With advanced minimal redundancy maximal relevance and incremental feature selection method, we identified the biomarker genes. RESULTS: A Support Vector Machine-based classifier was constructed to predict the response of colorectal cancer patients to FOLFOX therapy. Its accuracy, sensitivity and specificity were 0.854, 0.845 and 0.863, respectively. CONCLUSION: The biological analysis of representative biomarker genes suggested that apoptosis and inflammation signaling pathways were essential for the response of colorectal cancer patients to FOLFOX chemotherapy.