There have been major developments in deep learning in computer vision since the 2010s. Deep learning has contributed to a wealth of data in medical image processing, and semantic segmentation is a salient technique in this field. This study retrospectively reviews recent studies on the application of deep learning for segmentation tasks in medical imaging and proposes potential directions for future development, including model development, data augmentation processing, and dataset creation. The strengths and deficiencies of studies on models and data augmentation, as well as their application to medical image segmentation, were analyzed. Fully convolutional network developments have led to the creation of the U-Net and its derivatives. Another noteworthy image segmentation model is DeepLab. Regarding data augmentation, due to the low data volume of medical images, most studies focus on means to increase the wealth of medical image data. Generative adversarial networks (GAN) increase data volume via deep learning. Despite the increasing types of medical image datasets, there is still a deficiency of datasets on specific problems, which should be improved moving forward. Considering the wealth of ongoing research on the application of deep learning processing to medical image segmentation, the data volume and practical clinical application problems must be addressed to ensure that the results are properly applied.

The 5-year overall survival rates for head and neck cancer (HNC) relies on distant metastasis. Importantly, the epithelial-mesenchymal transition (EMT) is believed to be an initial step of metastasis. However, the relationship of epigenetic with EMT formation is still unexplored in HNC. This study focuses on invasive subclones of HNC cell lines through the simulation of invasion in vitro; and underlying mechanisms were analyzed including DNA methylation and gene expression profile. Invasive subclones of NHC cell lines were successfully obtained using transwell coated with Matrixgel. Cells invaded through 8 μm pore several times were subcultured and examined with EMT features including morphology, EMT marker genes expression, and invasive ability. Moreover, compared the profile of genes expression in parental and invasive cells was analyzed using mRNA expression array. DNA methyltransferase 3B (DNMT 3B) was upregulated in invasive subclones and might control the 5′ region of E-cadherin (E-cad) methylation and further inhibited E-cad protein expression. Interference of DNMT 3B by siRNA or miRNA 29b could reduce EMT and cell invasion. Expression array analysis revealed the most possible involved pathways in cell invasion including arginine and proline metabolism, TGF-beta, and focal adhesion. DNMT 3B might control EMT by DNA methylation manner in invasive HNC cell lines. Moreover, miR-29b mimic downregulated DNMT 3B and inhibited EMT and cell invasion indicated the role of therapeutic agent for invasive HNC. Genes identified from array data and new molecules are involved in metastasis of HNC need further validation.

The 2010 Revisions to the McDonald Criteria have established that dissemination in time (DIT) of multiple sclerosis (MS) can be demonstrated by simultaneous presence of asymptomatic gadolinium-enhancing and nonenhancing lesions on a single magnetic resonance imaging (MRI). However, gadolinium-based contrast agents (GBCAs) have contraindications. Diffusion-weighted imaging (DWI) can detect diffusion alterations in active inflammatory lesions. The purpose of this study was to investigate if DWI can be an alternative to contrast-enhanced T1-weighted imaging (CE T1WI) for demonstrating DIT in MS. We selected patients with clinically definite MS and evaluated their baseline brain MRI. Asymptomatic lesions were identified as either hyperintense or nonhyperintense on DWI and enhancing or nonenhancing on CE T1WI. Fisher’s exact test was performed to determine whether the hyperintensity on DWI was related to the enhancement on CE T1WI (P < 0.05). The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of the DWI to predict lesion enhancement were calculated. Twenty-two patients with 384 demyelinating lesions that were hyperintense on T2-weighted imaging and more than 3 mm in size were recruited. The diffusion hyperintensity and lesion enhancement were significantly correlated (P <0.001). The sensitivity, specificity, PPV, NPV and accuracy were 100%, 67.9%, 32.3%, 100% and 72.1%, respectively. A hyperintense DWI finding does not necessarily overlap with contrast enhancement. There are many false positives, possibly representing other stages of lesion development. Although DWI may not replace CE T1WI imaging to demonstrate DIT due to the low PPV, it may serve as a screening MRI sequence where the use of GBCAs is a concern.

Z-ligustilide (or ligustilide) is found in Angelica sinensis (Oliv.) Diels and may exert potential benefits in cancer treatment. Previous research has reported that ligustilide has anti-cancer effects on several types of cancer cells. However, studies of ligustilide on oral cancer cells have not been reported, especially under hypoxic conditions. This study focuses on the molecular mechanism of ligustilide-induced apoptosis in hypoxic oral cancer cells. We found that in hypoxic TW2.6 cells, ligustilide inhibited cell migration and induced caspase-dependent apoptosis. Accumulation of c-Myc accompanied by BH3-only members suggests that ligustilide may induce c-Myc-dependent apoptosis. In addition, we reported that ligustilide has an effect on ER-stress signaling. By using inhibitors of c-Myc, IRE1α, and ER-stress inhibitors, we found that cell morphologies or cell viability were rescued to some degree. Moreover, ligustilide is able to increase the expression of γ-H2AX and enhance the occurrence of DNA damage in oral cancer cells after radiation treatment. This result suggests that ligustilide has potential as a radiation sensitizer. Altogether, we propose that ligustilide may induce c-Myc-dependent apoptosis via ER-stress signaling in hypoxic oral cancer cells.

Aberrant insulin-like growth factor-binding protein 7 (IGFBP-7) expression has been found in various cancers such as prostate, breast, and colon. IGFBP-7 induced the apoptosis of tumor and potentially predicted the clinical outcome in some cancers is further demonstrated. This study investigates the causes and underlying mechanisms of aberrant IGFBP-7 expression in unravelling head and neck squamous cell carcinoma (HNSCC). A total of 47 oral tongue cancer patient samples were primarily analyzed for the methylation status in 5′ region of IGFBP-7 by methylation-specific PCR (MS-PCR). Subsequently the invasion, overexpression, and knockdown of IGFBP-7 in the HNSCC A253 invasive subpopulation were employed to examine the effect of IGFBP-7. The epithelial–mesenchymal transition (EMT) marker genes and AKT/GSK3β/β-catenin signaling were further evaluated by Western blot for the understanding the role of aberrant IGFBP-7 expression and thereof putative mechanism. EMT expressed in the invasive subpopulation of HNSCC cell lines (A253 and RPMI 2650) was contemporary with the down-regulation of IGFBP-7. After treatment with 5-AZA-2′ deoxycytidine, the de-methylated CpG sites in the 5′ region of IGFBP-7 were observed and IGFBP-7 mRNA expression was also restored. Accordingly, re-expression IGFBP-7 in invasive subpopulation of A253 could induce the mesenchymal–epithelial transition (MET) and concurrently inhibited the cell invasion. Moreover, IGFBP-7 methylation status of 47 oral tongue tumors showed a positive correlation to invasive depth of the tumor, loco-regional recurrence, and cancer sequence. IGFBP-7 can alter EMT relative marker genes and suppress cell invasion in A253 cell through AKT/GSK3β/β-catenin signaling. The epigenetic control of IGFBP-7 in the invasion and metastasis of HNSCC was reported, suggesting that IGFBP-7 could be a prognostic factor for the probability of invasion and a therapeutic remedy.