Paired conditional generative adversarial network for highly accelerated liver 4D MRI.

Purpose.4D MRI with high spatiotemporal resolution is desired for image-guided liver radiotherapy. Acquiring densely sampling k-space data is time-consuming. Accelerated acquisition with sparse samples is desirable but often causes degraded image quality or long reconstruction time. We propose the Reconstruct Paired Conditional Generative Adversarial Network (Re-Con-GAN) to shorten the 4D MRI reconstruction time while maintaining the reconstruction quality.Methods.Patients who underwent free-breathing liver 4D MRI were included in the study. Fully- and retrospectively under-sampled data at 3, 6 and 10 times (3×, 6× and 10×) were first reconstructed using the nuFFT algorithm. Re-Con-GAN then trained input and output in pairs. Three types of networks, ResNet9, UNet and reconstruction swin transformer (RST), were explored as generators. PatchGAN was selected as the discriminator. Re-Con-GAN processed the data (3D +t) as temporal slices (2D +t). A total of 48 patients with 12 332 temporal slices were split into training (37 patients with 10 721 slices) and test (11 patients with 1611 slices). Compressed sensing (CS) reconstruction with spatiotemporal sparsity constraint was used as a benchmark. Reconstructed image quality was further evaluated with a liver gross tumor volume (GTV) localization task using Mask-RCNN trained from a separate 3D static liver MRI dataset (70 patients; 103 GTV contours).Results.Re-Con-GAN consistently achieved comparable/better PSNR, SSIM, and RMSE scores compared to CS/UNet models. The inference time of Re-Con-GAN, UNet and CS are 0.15, 0.16, and 120 s. The GTV detection task showed that Re-Con-GAN and CS, compared to UNet, better improved the dice score (3× Re-Con-GAN 80.98%; 3× CS 80.74%; 3× UNet 79.88%) of unprocessed under-sampled images (3× 69.61%).Conclusion.A generative network with adversarial training is proposed with promising and efficient reconstruction results demonstrated on an in-house dataset. The rapid and qualitative reconstruction of 4D liver MR has the potential to facilitate online adaptive MR-guided radiotherapy for liver cancer.

Deep match: A zero-shot framework for improved fiducial-free respiratory motion tracking.

BACKGROUND AND PURPOSE: Motion management is essential to reduce normal tissue exposure and maintain adequate tumor dose in lung stereotactic body radiation therapy (SBRT). Lung SBRT using an articulated robotic arm allows dynamic tracking during radiation dose delivery. Two stereoscopic X-ray tracking modes are available - fiducial-based and fiducial-free tracking. Although X-ray detection of implanted fiducials is robust, the implantation procedure is invasive and inapplicable to some patients and tumor locations. Fiducial-free tracking relies on tumor contrast, which challenges the existing tracking algorithms for small (e.g., <15 mm) and/or tumors obscured by overlapping anatomies. To markedly improve the performance of fiducial-free tracking, we proposed a deep learning-based template matching algorithm - Deep Match. METHOD: Deep Match consists of four self-definable stages - training-free feature extractor, similarity measurements for location proposal, local refinements, and uncertainty level prediction for constructing a more trustworthy and versatile pipeline. Deep Match was validated on a 10 (38 fractions; 2661 images) patient cohort whose lung tumor was trackable on one X-ray view, while the second view did not offer sufficient conspicuity for tumor tracking using existing methods. The patient cohort was stratified into subgroups based on tumor sizes (<10 mm, 10-15 mm, and >15 mm) and tumor locations (with/without thoracic anatomy overlapping). RESULTS: On X-ray views that conventional methods failed to track the lung tumor, Deep Match achieved robust performance as evidenced by >80 % 3 mm-Hit (detection within 3 mm superior/inferior margin from ground truth) for 70 % of patients and <3 mm superior/inferior distance (SID) ∼1 mm standard deviation for all the patients. CONCLUSION: Deep Match is a zero-shot learning network that explores the intrinsic neural network benefits without training on patient data. With Deep Match, fiducial-free tracking can be extended to more patients with small tumors and with tumors obscured by overlapping anatomy.

Delayed PCI is not beneficial for STEMI patients with impaired renal function: a retrospective cohort study.

BACKGROUND: Preexisting impaired renal function (IRF) and contrast-induced nephropathy (CIN) after percutaneous coronary intervention (PCI) in patients with ST-segment elevation myocardial infarction (STEMI) are important prognostic parameters, but it is unknown whether delayed PCI is still beneficial for STEMI patients with IRF. METHODS: A retrospective single-center cohort study was performed in 164 patients who presented at least 12 h after symptom onset, and were diagnosed with STEMI and IRF. They were assigned to two groups to receive PCI plus optimal medical therapy (OMT) and OMT alone respectively. Clinical outcomes at 30 days and 1 year were compared between two groups, and hazard ratio for survival was analyzed using Cox regression model. A power analysis demanded 34 patients in each group to produce a power of 90% and a P value of 0.05. RESULTS: The 30-day mortality was significantly lower in PCI group (n = 126) than in non-PCI group (n = 38) (11.1% versus 28.9%, P = 0.018), while there was no significant difference in the 1-year mortality and incidence of cardiovascular comorbidities between the two groups. Cox regression analysis showed that patients with IRF didn't benefit from receiving PCI on survival rate (P = 0.267). CONCLUSIONS: Delayed PCI is not beneficial on one-year clinical outcomes for STEMI patients with IRF.

Association Between Serum Galectin-3 Levels and Coronary Stenosis Severity in Patients With Coronary Artery Disease.

BACKGROUND: The relationship between galectin-3 (Gal-3) and coronary artery disease (CAD) has not been fully elucidated. AIM: This study aimed to determine the relationship between the presence and severity of CAD and serum Gal-3 levels. PATIENTS AND METHODS: Three-hundred thirty-one consecutive CAD patients were enrolled as the study group. An additional 62 patients without CAD were enrolled as the control group. Serum Gal-3 levels were separately compared between the non-CAD and CAD groups, among the stable CAD and Acute coronary syndrome (ACS) groups, and between CAD patients with low and high SYNTAX scores (SSs). The 1-year cumulative rate of major adverse cardiac events (MACEs) was also compared among ACS patients by Gal-3 levels. RESULTS: Serum Gal-3 was significantly higher in the CAD group than in the non-CAD group 3.89 (0.16-63.67) vs. 2.07 (0.23-9.38) ng/ml, P < 0.001. Furthermore, serum Gal-3 was significantly higher in the non-ST-segment elevation ACS (NSTE-ACS) group than that in the stable CAD group, 4.72 (1.0-16.14) vs. 2.23 (0.65-23.8) ng/ml, P = 0.04 and higher in the ST-segment elevation myocardial infarction (STEMI) group than that in the stable CAD group 7.87 (0.59-63.67) vs. 2.23 (0.65-23.8) ng/ml, P < 0.001. Serum Gal-3 level was an independent predictor of ACS compared with stable CAD group (OR = 1.131, 95% CI: 1.051-1.217, P = 0.001) as well as high SS (OR = 1.030, 95% CI: 1.021-1.047, P = 0.038) after adjust other confounding risk factors. Acute coronary syndrome patients with Gal-3 levels above the median (gal-3 = 4.78 ng/ml) showed a higher cumulative MACE rate than those with Gal-3 levels below the median. After adjusting other confounding risk factors, Gal-3 remained an independent risk factor for the cumulative rate of MACEs in ACS patients (6% higher rate of MACEs incidence per 1 ng/ml increment of Gal-3). CONCLUSION: Galectin-3 correlated with the presence of CAD as well as coronary stability and complexity. Galectin-3 may be valuable in predicting mid-term prognosis in ACS patients.

MiR-195-3p is a Novel Prognostic Biomarker Associated with Immune Infiltrates of Lung Adenocarcinoma.

BACKGROUND: MicroRNA-195-3p (miR-195-3p) plays an important role in some tumors, but its role in LUAD is unclear. This study explored the expression of miR-195-3p in LUAD and the relationship between the expression of miR-195-3p and the clinical and prognostic characteristics of LUAD patients. METHODS: MiR-195-3p expression and clinical information of LUAD patients were obtained from The Cancer Genome Atlas (TCGA). Kruskal-Wallis test, Wilcoxon signed rank test, logistic regression, and Cox regression were used to assess the relationship between the expression level of miR-195-3p and clinical features in LUAD tissues. Kaplan-Meier survival curves were used to analyze the effect of miR-195-3p expression levels on the prognosis of LUAD patients. Target genes of miR-195-3p were predicted by several software. GO (Gene Ontology), KEGG (Kyoto Encyclopedia of Genes and Genomes), and immune infiltration analysis were used to analyze the possible regulatory network of miR-195-3p. RESULTS: Compared with normal lung tissue, miR-195-3p is down expressed in LUAD tissue (P < 0.001). The low miR-195-3p expression in LUAD was significantly associated with N stage (P = 0.046), pathologic stage (P = 0.011), and gender (P = 0.010). Low miR-195-3p expression predicted a poorer overall survival (HR: 0.60; 95% CI: 0.45-0.81; P = 0.001) and disease-specific survival (HR: 0.55; 95% CI: 0.37-0.80; P = 0.002). The expression of miR-195-3p (HR: 0.488; 95% CI: 0.304-0.784; P = 0.003) was independently correlated with OS in LUAD patients. High expression of miR-195-3p genes, including ABCC2, AGMAT, ARNTL2, ATP6V0A4, CDC25A, CDK1, FAM111B, GJB2, GRIP1, HMGA2, HOXA9, KIF14, SYT2, and TFAP2A, were associated with poor OS in LUAD. GO and KEGG analysis suggested that miR-195-3p was related to the phagosome pathway. MiR-195-3p may promote the function of B cells, dendritic cells, eosinophils, immature dendritic cells, macrophages, Mast cells, NK cells, plasmacytoid dendritic cells, and follicular helper T cells. CONCLUSION: Low miR-195-3p expression is significantly associated with poor survival in LUAD, which may be a promising prognostic biomarker for LUAD.

Voxelwise Prediction of Recurrent High-Grade Glioma via Proximity Estimation-Coupled Multidimensional Support Vector Machine.

PURPOSE: To provide early and localized glioblastoma (GBM) recurrence prediction, we introduce a novel postsurgery multiparametric magnetic resonance-based support vector machine (SVM) method coupling with stem cell niche (SCN) proximity estimation. METHODS AND MATERIALS: This study used postsurgery magnetic resonance imaging (MRI) scans from 50 patients with recurrent GBM, obtained approximately 2 months before clinically diagnosed recurrence. The main prediction pipeline consisted of a proximity-based estimator to identify regions with high risk of recurrence (HRRs) and an SVM classifier to provide voxelwise prediction in HRRs. The HRRs were estimated using the weighted sum of inverse distances to 2 possible origins of recurrence-the SCN and the tumor cavity. Subsequently, multiparametric voxels (from T1, T1 contrast-enhanced, fluid-attenuated inversion recovery, T2, and apparent diffusion coefficient) within the HRR were grouped into recurrent (warped from the clinical diagnosis) and nonrecurrent subregions and fed into the proximity estimation-coupled SVM classifier (SVMPE). The cohort was randomly divided into 40% and 60% for training and testing, respectively. The trained SVMPE was then extrapolated to an earlier time point for earlier recurrence prediction. As an exploratory analysis, the SVMPE predictive cluster sizes and the image intensities from the 5 magnetic resonance sequences were compared across time to assess the progressive subclinical traces. RESULTS: On 2-month prerecurrence MRI scans from 30 test cohort patients, the SVMPE classifier achieved a recall of 0.80, a precision of 0.69, an F1-score of 0.73, and a mean boundary distance of 7.49 mm. Exploratory analysis at early time points showed spatially consistent but significantly smaller subclinical clusters and significantly increased T1 contrast-enhanced and apparent diffusion coefficient values over time. CONCLUSIONS: We demonstrated a novel voxelwise early prediction method, SVMPE, for GBM recurrence based on clinical follow-up MR scans. The SVMPE is promising in localizing subclinical traces of recurrence 2 months ahead of clinical diagnosis and may be used to guide more effective personalized early salvage therapy.

Bladder surface dose modeling in prostate cancer radiotherapy: An analysis of motion-induced variations and the cumulative dose across the treatment.

PURPOSE: To introduce a novel surface-based dose mapping method to improve quantitative bladder dosimetric assessment in prostate cancer (PC) radiotherapy. METHODS: Based on the planning and daily pre and postfraction MRIs of 12 PC patients, bladder surface models (SMs) were generated on manually delineated contours and regionally aligned via surface-based registration. Subsequently, bladder surface dose models (SDMs) were created using face-wise dose sampling. To determine the bladder intrafractional and interfractional motion and dose variation, we performed a pose analysis between pre and postfraction bladder SMs, as well as surface mapping for fractional SMs. Discrepancies between the received dose, accumulated from daily SDMs, and the planned dose were then assessed on the corresponding SDMs. Complementary to the surface dose mapping, dose surface histogram (DSH)-based comparisons were also performed. RESULTS: The intrafraction pose analysis revealed a significant (p < 0.05) bladder expansion, as well as an anterior/superior drift during the treatment. The intrafraction motion substantially altered dose to mid-bladder body, but not the bladder surface areas distal to or contiguous with the target. A similar pattern of dose variations was also detected by interfraction comparisons. With surface registration to the common SM, the cumulative bladder dose significantly differs from the planned dose. The discrepancy is evident in the mid-posterior range that corresponds to a mid- to high-dose region. The received DSH significantly differs from the planned DSH after permutation correction (p = 0.0122), while the overall surface-based comparison after multiple comparison correction is nonsignificant (p = 0.0800). CONCLUSIONS: We developed a novel surface-based intra and interdose mapping framework applied to a unique daily MR dataset for image-guided radiotherapy. The framework identified significant intrafraction bladder positional changes, localized the intra and interfraction variations, and quantified planned versus received dose differences on the bladder surface. The result indicates the importance of adopting the motion-integrated bladder SDM for bladder dose management.

Metformin Suppresses the Progress of Diabetes-Accelerated Atherosclerosis by Inhibition of Vascular Smooth Muscle Cell Migration Through AMPK-Pdlim5 Pathway.

Backgrounds: Our previous work revealed that AMP-activated protein kinase (AMPK) activation inhibits vascular smooth muscle cell migration in vitro by phosphorylating PDZ and LIM domain 5 (Pdlim5). As metformin is an AMPK activator, we used a mouse vascular smooth muscle cell (VSMC) line and a Myh11-cre-EGFP mice to investigate whether metformin could inhibit the migration of VSMCs in vitro and in a wire-injury model in vivo. It is recognized that VSMCs contribute to the major composition of atherosclerotic plaques. In order to investigate whether the AMPK-Pdlim5 pathway is involved in the protective function of metformin against atherosclerosis, we utilized ApoE-/- male mice to investigate whether metformin could suppress diabetes-accelerated atherosclerosis by inhibition of VSMC migration via the AMPK-Pdlim5 pathway. Methods: The mouse VSMC cell line was exogenously transfected wild type, phosphomimetic, or unphosphorylatable Pdlim5 mutant before metformin exposure. Myh11-cre-EGFP mice were treated with saline solution or metformin after these were subjected to wire injury in the carotid artery to study whether metformin could inhibit the migration of medial VSMCs into the neo-intima. In order to investigate whether the AMPK-Pdlim5 pathway is involved in the protective function of metformin against atherosclerosis, ApoE-/- male mice were divided randomly into control, streptozocin (STZ), and high-fat diet (HFD)-induced diabetes mellitus; STZ+HFD together with metformin or Pdlim5 mutant carried the adenovirus treatment groups. Results: It was found that metformin could induce the phosphorylation of Pdlim5 and inhibit cell migration as a result. The exogenous expression of phosphomimetic S177D-Pdlim5 inhibits lamellipodia formation and migration in VSMCs. It was also demonstrated that VSMCs contribute to the major composition of injury-induced neointimal lesions, while metformin could alleviate the occlusion of the carotid artery. The data of ApoE-/- mice showed that increased plasma lipids and aggravated vascular smooth muscle cell infiltration into the atherosclerotic lesion in diabetic mice were observed Metformin alleviated diabetes-induced metabolic disorders and atherosclerosis and also reduced VSMC infiltration in atherosclerotic plaques, while the Pdlim5 phospho-abolished mutant that carried adenovirus S177A-Pdlim5 undermines the protective function of metformin. Conclusions: The activation of the AMPK-Pdlim5 pathway by metformin could interrupt the migratory machine of VSMCs and inhibit cell migration in vitro and in vivo. The maintenance of AMPK activity by metformin is beneficial for suppressing diabetes-accelerated atherosclerosis.

Association Between Fasting Hyperglycemia and New-Onset Atrial Fibrillation in Patients With Acute Myocardial Infarction and the Impact on Short- and Long-Term Prognosis.

Background: The relationship between fasting hyperglycemia (FHG) and new-onset atrial fibrillation (AF) in patients with acute myocardial infarction (AMI) is unclear, and whether their co-occurrence is associated with a worse in-hospital and long-term prognosis than FHG or AF alone is unknown. Objective: To explore the correlation between FHG and new-onset AF in patients with AMI, and their impact on in-hospital and long-term all-cause mortality. Methods: We performed a retrospective cohort study comprising 563 AMI patients. The patients were divided into the FHG group and the NFHG group. The incidence of new-onset AF during hospitalization was compared between the two groups and sub-groups under different Killip grades. Logistic regression was used to assess the association between FHG and new-onset AF. In-hospital mortality and long-term all-cause mortality were compared among patients with FHG, AF, and with both FHG and AF according to 10 years of follow-up information. Results: New-onset AF occurred more frequently in the FHG group than in the NFHG group (21.6 vs. 9.2%, p < 0.001). This trend was observed for Killip grade I (16.6 vs. 6.5%, p = 0.002) and Grade II (17.1 vs. 6.9%, p = 0.005), but not for Killip grade III-IV (40 vs. 33.3%, p = 0.761). Logistic regression showed FHG independently correlated with new-onset AF (OR, 2.56; 95% CI, 1.53-4.30; P < 0.001), and 1 mmol/L increased in fasting glucose was associated with a 5% higher rate of new-onset AF, after adjustment for traditional AF risk factors. AMI patients complicated with both fasting hyperglycemia and AF showed the highest in-hospital mortality and long-term all-cause mortality during an average of 11.2 years of follow-up. Multivariate Cox regression showed FHG combined with AF independently correlated with long-term all-cause mortality after adjustment for other traditional risk factors (OR = 3.13, 95% CI 1.64-5.96, p = 0.001), compared with the group with neither FHG nor new-onset AF. Conclusion: FHG was an independent risk factor for new-onset AF in patients with AMI. AMI patients complicated with both FHG and new-onset AF showed worse in-hospital and long-term all-cause mortality than with FHG or AF alone.

Quantitative Characterization of Tumor Proximity to Stem Cell Niches: Implications on Recurrence and Survival in GBM Patients.

PURPOSE: Emerging evidence has linked glioblastoma multiforme (GBM) recurrence and survival to stem cell niches (SCNs). However, the traditional tumor-ventricle distance is insufficiently powered for an accurate prediction. We aimed to use a novel inverse distance map for improved prediction. METHODS AND MATERIALS: Two T1-magnetic resonance imaging data sets were included for a total of 237 preoperative scans for prognostic stratification and 55 follow-up scans for recurrent pattern identification. SCN, including the subventricular zone (SVZ) and subgranular zone (SGZ), were manually defined on a standard template. A proximity map was generated using the summed inverse distances to all SCN voxels. The mean and maximum proximity scores (PSm-SCN and PSmax-SCN) were calculated for each primary/recurrent tumor, deformably transformed into the template. The prognostic capacity of proximity score (PS)-derived metrics was assessed using Cox regression and log-rank tests. To evaluate the impact of SCNs on recurrence patterns, we performed group comparisons of PS-derived metrics between the primary and recurrent tumors. For comparison, the same analyses were conducted on PS derived from SVZ alone and traditional edge/center-to-ventricle metrics. RESULTS: Among all SCN-derived features, PSm-SCN was the strongest survival predictor (P < .0001). PSmax-SCN was the best in risk stratification, using either evenly sorted (P = .0001) or k-means clustering methods (P = .0045). PS metrics based on SVZ only also correlated with overall survival and risk stratification, but to a lesser degree of significance. In contrast, edge/center-to-ventricle metrics showed weak to no prediction capacities in either task. Moreover, PSm-SCN,PSm-SVZ, and center-to-ventricle metrics revealed a significantly closer SCN distribution of recurrence than primary tumors. CONCLUSIONS: We introduced a novel inverse distance-based metric to comprehensively capture the anatomic relationship between GBM tumors and SCN zones. The derived metrics outperformed traditional edge or center distance-based measurements in overall survival prediction, risk stratification, and recurrent pattern differentiation. Our results reveal the potential role of SGZ in recurrence aside from SVZ.

Automatic detection and segmentation of multiple brain metastases on magnetic resonance image using asymmetric UNet architecture.

Detection of brain metastases is a paramount task in cancer management due both to the number of high-risk patients and the difficulty of achieving consistent detection. In this study, we aim to improve the accuracy of automated brain metastasis (BM) detection methods using a novel asymmetric UNet (asym-UNet) architecture. An end-to-end asymmetric 3D-UNet architecture, with two down-sampling arms and one up-sampling arm, was constructed to capture the imaging features. The two down-sampling arms were trained using two different kernels (3 × 3 × 3 and 1 × 1 × 3, respectively) with the kernel (1 × 1 × 3) dominating the learning. As a comparison, vanilla single 3D UNets were trained with different kernels and evaluated using the same datasets. Voxel-based Dice similarity coefficient (DSCv), sensitivity (S v), precision (P v), BM-based sensitivity (S BM), and false detection rate (F BM) were used to evaluate model performance. Contrast-enhanced T1 MR images from 195 patients with a total of 1034 BMs were solicited from our institutional stereotactic radiosurgery database. The patient cohort was split into training (160 patients, 809 lesions), validation (20 patients, 136 lesions), and testing (15 patients, 89 lesions) datasets. The lesions in the testing dataset were further divided into two subgroups based on the diameters (small S = 1-10 mm, large L = 11-26 mm). In the testing dataset, there were 72 and 17 BMs in the S and L sub-groups, respectively. Among all trained networks, asym-UNet achieved the highest DSCv of 0.84 and lowest F BM of 0.24. Although vanilla 3D-UNet with a single 1 × 1 × 3 kernel achieved the highest sensitivities for the S group, it resulted in the lowest precision and highest false detection rate. Asym-UNet was shown to balance sensitivity and false detection rate as well as keep the segmentation accuracy high. The novel asym-UNet segmentation network showed overall competitive segmentation performance and more pronounced improvement in hard-to-detect small BMs comparing to the vanilla single 3D UNet.

Operating Transverse Aortic Constriction with Absorbable Suture to Obtain Transient Myocardial Hypertrophy.

Based on twice transverse aortic constrictions (TACs) in mice, it is proved that myocardial hypertrophic preconditioning (MHP) could attenuate cardiomyocyte hypertrophy and slow down progression to heart failure. For novices, however, the MHP model is usually quite difficult to establish because of the technical obstacles in ventilator operation, opening the chest repeatedly, and bleeding caused by debanding. To facilitate this model, to increase the surgical success rate and to reduce the incidence of bleeding, we switched to absorbable sutures for the first TAC combing with a ventilator-free technique. Using a 2-week absorbable suture, we demonstrated that this procedure could cause significant myocardial hypertrophy in 2 weeks; and 4 weeks after surgery, myocardial hypertrophy was almost completely regressed to the baseline. Using this protocol, the operators could master the MHP model easily with a lower operation mortality.

Quantifying vascular invasion in pancreatic cancer-a contrast CT based method for surgical resectability evaluation.

Pancreatic cancer (PC) is one of the most lethal cancers, with frequent local therapy resistance and dismal 5-year survival rate. To date, surgical resection remains to be the only treatment option offering potential cure. Unfortunately, at diagnosis, the majority of patients demonstrate varying levels of vascular infiltration, which can contraindicate surgical resection. Patients unsuitable for immediate resection are further divided into locally advanced (LA) and borderline resectable (BR), with different treatment goals and therapeutic designs. Accurate definition of resectability is thus critical for PC patients, yet the existing methods to determine resectability rely on descriptive abutment to surrounding vessels rather than quantitative geometric characterization. Here, we aim to introduce a novel intra-subject object-space support-vector-machine (OsSVM) method to quantitatively characterize the degree of vascular involvement-the main factor determining the PC resectability. Intra-subject OsSVMs were applied on 107 contrast CT scans (56 LA, BR and 26 resectable (RE) PC cases) for optimized tumor-vessel separations. Nine metrics derived from OsSVM margins were calculated as indicators of the overall vascular infiltration. The combined sets of matrics selected by the elastic net yielded high classification capability between LA and BR (AUC = 0.95), as well as BR and RE (AUC = 0.98). The proposed OsSVM method may provide an improved quantitative imaging guideline to refine the PC resectability grading system.

Value of Galectin-3 in Acute Myocardial Infarction.

Galectins are an ancient family of lectins characterized by evolutionarily conserved amino acid sequences and ß-galactoside recognition and binding sites. Galectin-3 (Gal-3) is one of 15 known galectins. This protein has important functions in numerous biological activities, including cardiac fibrosis and heart failure. In recent years, many studies have shown that Gal-3 is closely associated with acute myocardial infarction (AMI) and may be a promising biomarker for the assessment of severity as well as prognosis prediction in AMI patients, but controversy still exists. In this review, we summarize the latest literature on the relationship between Gal-3 and unstable plaques, the secretion kinetics of Gal-3 during the acute phase of AMI, and the value of Gal-3 in the prediction of post-AMI remodeling. Finally, the possible value of Gal-3 as a biological target for AMI therapy is examined.

Aberrant DNA Hypermethylation Silenced LncRNA Expression in Gastric Cancer.

BACKGROUND/AIM: Long noncoding RNAs (lncRNAs) are noncoding transcripts that are >200 nucleotides in length. However, the biological functions and regulation mechanisms of lncRNAs in gastric carcinogenesis remain unknown. MATERIALS AND METHODS: The expression levels of Linc00472 were analyzed by real-time PCR. The DNA methylation status was assessed using Combined Bisulfite Restriction Analysis (COBRA). The biological role of Linc00472 was assessed in AGS cells with Linc00472 overexpression. RESULTS: Using the next-generation sequencing approach, we identified DNA methylation-associated lncRNAs in gastric cancer cells. Among them, the expression level of Linc00472 significantly decreased in gastric cancer tissues compared to adjacent normal tissues. Furthermore, we observed a more frequent hypermethylation of CpG islands upstream of Linc00472 in gastric cancer tissues. Ectopic Linc00472 expression could significantly inhibit gastric cancer cell growth and migration. CONCLUSION: Epigenetically regulated Linc00472 expression plays a crucial role in modulating gastric cancer cell growth and motility.

Delayed angioplasty is superior to an emergency strategy in ST-segment elevation myocardial infarction patients who present late and with infarct artery spontaneous reperfusion before intervention.

OBJECTIVE: The best time to perform percutaneous coronary intervention (PCI) in ST-segment elevation myocardial infarction (STEMI) patients presenting 12 to 72 hours after chest pain is unclear. The aim of this study was to explore whether delayed PCI was superior to emergency PCI in STEMI patients who presented 12 to 72 hours after onset of symptoms and with a spontaneous reperfusion infarct-related artery (IRA). METHODS: STEMI patients who presented 12 to 72 hours after symptom onset were enrolled and assigned to either the emergency PCI or delayed PCI group. We compared the rates of procedural success and in-hospital mortality as well as the main adverse cardiac events (MACE) during hospitalisation and after one year of follow up. RESULTS: We enrolled 159 patients in this retrospective study. Emergency PCI was performed in 73 patients and delayed PCI in 86 patients. A remarkably high rate of procedural success was achieved in the delayed PCI group compared with the emergency PCI group (97.7 vs 86.3%, p = 0.007) due to a lower rate of no re-flow or slow flow (2.3 vs 13.7%, p = 0.007). There was no significant difference in terms of MACE and in-hospital mortality rates (16.4 vs 9.3%, p = 0.133; 1.4 vs 2.3%, p = 0.562). During one year of follow up, the left ventricular ejection fraction was similar in the two groups [median 58% (57-68) in the emergency PCI group vs median 56% (50-62) in the delayed PCI group, p = 0.666]. Although the emergency PCI group had a trend towards a higher rate of MACE, the difference was not statistically significant (12.2 vs 11.6%, HR = 1.067, 95% CI: 0.434-2.627, p = 0. 887). CONCLUSIONS: In STEMI patients who presented late (12-72 hours) after symptom onset and with a spontaneous reperfusion IRA, delayed PCI showed a higher rate of procedural success without increased rates of in-hospital and long-term MACE and mortality.

A post-processing method based on interphase motion correction and averaging to improve image quality of 4D magnetic resonance imaging: a clinical feasibility study.

METHODS:: Nine patients (seven pancreas, one liver, and one lung) were recruited. 4D-MRI was performed using two prototype k-space sorted techniques, stack-of-stars (SOS) and koosh-ball (KB) acquisitions. Post-processing using MoCoAve was implemented for both methods. Image quality score, apparent SNR (aSNR), sharpness, motion trajectory and standard deviation (σ_GTV) of the gross tumor volumes were compared between original and MoCoAve image sets. RESULTS:: All subjects successfully underwent 4D-MRI scans and MoCoAve was performed on all data sets. Significantly higher image quality scores (2.64 ± 0.39 vs 1.18 ± 0.34, p = 0.001) and aSNR (37.6 ± 15.3 vs 18.1 ± 5.7, p = 0.001) was observed in the MoCoAve images when compared to the original images. High correlation in tumor motion trajectories in the superoinferior direction (SI: 0.91 ± 0.08) and weaker in the anteroposterior (AP: 0.51 ± 0.44) and mediolateral (ML: 0.37 ± 0.23) directions, similar image sharpness (0.367 ± 0.068 vs 0.369 ± 0.072, p = 0.805), and minimal average absolute difference (0.47 ± 0.34 mm) of the motion trajectory profiles was found between the two image sets. The σ_GTV in pancreas patients was significantly (p = 0.039) lower in MoCoAve images (1.48 ± 1.35 cm3) than in the original images (2.17 ± 1.31 cm3). CONCLUSION:: MoCoAve using interphase motion correction and averaging has shown promise as a post-processing method for improving k-space sorted (SOS and KB) 4D-MRI image quality in thoracic and abdominal cancer patients. ADVANCES IN KNOWLEDGE:: The proposed method is an image based post-processing method that could be applied to many k-space sorted 4D-MRI methods for improved image quality and signal-to-noise ratio while preserving image sharpness and respiratory motion fidelity. It is a useful technique for the radiotherapy planning community who are interested in using 4D-MRI but aren't satisfied with their current MR image quality.

Combined morphologic and metabolic pipeline for Positron emission tomography/computed tomography based radiotherapy response evaluation in locally advanced pancreatic adenocarcinoma.

BACKGROUND AND PURPOSE: Adaptive radiation planning for pancreatic adenocarcinoma (PA) relies on accurate treatment response assessment, while traditional response evaluation criteria inefficiently characterize tumors with complex morphological features or intrinsically low metabolism. To better assess treatment response of PA, we quantify and compare regional morphological and metabolic features of the 3D pre- and post-radiation therapy (RT) tumor models. MATERIALS AND METHODS: Thirty-one PA patients with pre and post-RT Positron emission tomography/computed tomography (PET/CT) scans were evaluated. 3D meshes of pre- and post-RT tumors were generated and registered to establish vertex-wise correspondence. To assess tumor response, Mahalanobis distances (M dist∣Fusion) between pre- and post-RT tumor surfaces with anatomic and metabolic fused vectors were calculated for each patient. M dist∣Fusion was evaluated by overall survival (OS) prediction and survival risk classification. As a comparison, the same analyses were conducted on traditional imaging/physiological predictors, and distances measurements based on metabolic and morphological features only. RESULTS: Among all the imaging/physiological parameters, M dist∣Fusion was shown to be the best predictor of OS (HR = 0.52, p = 0.008), while other parameters failed to reach significance. Moreover, M dist∣Fusion outperformed traditional morphologic and metabolic measurements in patient risk stratification, either alone (HR = 11.51, p < 0.001) or combined with age (HR = 9.04, p < 0.001). CONCLUSIONS: We introduced a PET/CT-based novel morphologic and metabolic pipeline for response evaluation in locally advanced PA. The fused M dist∣Fusion outperformed traditional morphologic, metabolic, and physiological measurements in OS prediction and risk stratification. The novel fusion model may serve as a new imaging-marker to more accurately characterize the heterogeneous tumor RT response.

Prognostic Value of Hemoglobin A1c Levels in Postmenopausal Diabetic Patients Undergoing Percutaneous Coronary Intervention (PCI) for Acute Coronary Syndrome.

BACKGROUND The purpose of our study was to analyze the clinical value of glycosylated hemoglobin Alc (HbA1c) levels in postmenopausal women with acute coronary syndrome (ACS) and diabetes following percutaneous coronary intervention (PCI). MATERIAL AND METHODS A total of 173 consecutive postmenopausal patients with comorbid diabetes underwent PCI for primary ACS were enrolled in this study. Serum HbA1c levels were measured prior to PCI, and baseline clinical characteristics of all patients were collected. All patients were followed up at regular intervals for major adverse cardiovascular events (MACEs) during the first year after PCI. MACEs included cardiac death, non-fatal myocardial infarction, and target vessel revascularization (TVR). RESULTS At the endpoint of this study, 29 (16.8%) patients out of all 173 patients had MACEs. According to the effect of glycemic control (as indicated by HbA1c levels), all patients were stratified into a well-controlled group (HbA1c ≤7.0%, N=72) and a poorly-controlled group (HbA1c >7.0%, N=101). The incidence rate of MACEs and TVR in poorly-controlled diabetics was prominently higher than that in well-controlled diabetics (10.8% vs. 21.8%, p=0.04). In multivariable COX regression analysis, after adjustment for potential confounders, HbA1c ≥7.0% remained an independent risk predictor of MACE (HR, 2.17; 95%CI, 1.13-5.65; p<0.01). CONCLUSIONS In postmenopausal ACS patients with comorbid diabetes, a high level of HbA1c is associated with a higher MACE rate after PCI, which is mainly driven by a higher rate of TVR.

Discriminating lung adenocarcinoma from lung squamous cell carcinoma using respiration-induced tumor shape changes.

Based on 4D-CT, we aimed to characterize the pattern of morphological changes in lung tumors during respiration, and investigated its potential in non-invasively differentiating lung adenocarcinoma (AC) and squamous cell carcinoma (SCC). We applied a 3D surface analysis on 22 tumors (13 AC, 9 SCC) to investigate the tumor regional morphological fluctuations in response to respiration phases. Tumor surface vertices among ten respiratory phases were matched using surface-based registration, and the shape descriptors (ρ and detJ) were calculated and tracked across respiration stages in a regionally aligned scenario. Pair-wise group comparisons were performed between lung AC and SCC subtypes, in terms of ratios of maximal shape changes as well as correlation coefficients between tumor shape and respiratory stage indicators from the lung. AC type tumors had averaged larger surface measurements at exhale than at inhale, and these surface measurements were negatively correlated with lung volumes across respiratory stages. In contrast, SCC type tumors had averaged smaller surface measurements at exhale than at inhale, and the correlations with lung volumes were positive. The group differences in maximal shape changes as well as correlations were both statistically significant (p < 0.05). We developed a non-invasive lung tumor sub-type detection pipeline based on respiration-induced tumor surface deformation. Significant differences in deformation patterns were detected between lung AC and SCC. The derived surface measurements may potentially serve as a new non-invasive imaging biomarker of lung cancer subtypes.