Assessing risk stratification in long-term outcomes of rectal neuroendocrine tumors following endoscopic resection: a multicenter retrospective study.

OBJECTIVES: While endoscopic resection of rectal neuroendocrine tumors (NETs) has significantly increased, long-term data on risk factors for recurrence are still lacking. Our aim is to analyze the long-term outcomes of patients with rectal NETs after endoscopic resection through risk stratification. METHODS: In this multicenter retrospective study, we included patients who underwent endoscopic resection of rectal NETs from 2009 to 2018 and were followed for ≥12 months at five university hospitals. We classified the patients into three risk groups according to the clinicopathological status of the rectal neuroendocrine tumors: low, indeterminate, and high. The high-risk group was defined if the tumors have any of the followings: size ≥ 10 mm, lymphovascular invasion, muscularis propria or deeper invasion, positive resection margins, or mitotic count ≥2/10. RESULTS: A total of 346 patients were included, with 144 (41.6%), 121 (35.0%), and 81 (23.4%) classified into the low-, indeterminate-, and high-risk groups, respectively. Among the high-risk group, seven patients (8.6%) received salvage treatment 28 (27-67) days after the initial endoscopic resection, with no reported extracolonic recurrence. Throughout the follow-up period, 1.1% (4/346) of patients experienced extracolonic recurrences at 56.5 (54-73) months after the initial endoscopic resection. Three of these patients (75%) were in the high-risk group and did not undergo salvage treatment. The risk of extracolonic recurrence was significantly higher in the high-risk group compared to the other groups (p = 0.039). CONCLUSION: Physicians should be concerned about the possibility of metastasis during long-term follow-up of high-risk patients and consider salvage treatment.

Energy-absorption analyses of honeycomb-structured Al-alloy and nylon sheets using modified split Hopkinson pressure bar.

Thin cylindrical honeycomb-structured aluminum alloy and mono-cast (MC) nylon were studied as superior energy-absorbing materials compared to metallic foams. Their energy-absorbing performance was assessed using a modified split Hopkinson pressure bar (SHPB). Key parameters included maximum impact acceleration (amax) and its reduction ratio (compared to the none-specimen case). The lowest amax reduction ratio was observed in bulk Al sheets without honeycomb cavities. As the cavity fraction increased up to 79% in honeycomb-structured Al specimens, the amax reduction ratio improved due to broadened stress-time curves with a shallow-plateau shape. This made high-cavity-fraction Al specimens preferable for higher-energy absorption and lighter-weight buffering materials. In nylon specimens, the amax reduction ratio increased until the fraction reached 52% due the softer and more deformable nature of the polymeric nylon. Thicker or rotated Al specimens also showed higher amax reduction ratios due to sufficient and continuous energy absorption. The modified SHPB demonstrated effective energy-buffering concepts and provided insightful amax interpretations, overcoming complexities in energy absorption analyses.

Unravelling interobserver variability in gastrointestinal glandular neoplasia: a contemporary study of US and Korean pathologists.

AIMS: Interobserver variability in the assessment of gastric neoplasia biopsies between most Western and Eastern (predominantly represented by Japanese in the literature) pathologists has been documented. It is unknown if such variability exists between the US and Korean pathologists in the current era. METHODS: Ten gastrointestinal (GI) pathologists from the USA (n=5) and South Korea (n=5) evaluated 100 scanned images of gastric (n=50) and colorectal (n=50) neoplasia biopsies and answered multiple questionnaires. Consensus was defined as the answer chosen by the majority. Cohen's (κc) and Fleiss' kappa (κf) values were calculated between the consensus of the two groups and among the raters, respectively. RESULTS: Both groups reached a consensus in the majority of cases (74%-100%) with slight to perfect intergroup (κc=0.049-1.000) and no to substantial intragroup (κf=-0.083 to 0.660) agreements. For gastric neoplasia, Korean pathologists relied heavily on cytoarchitectural atypia, whereas the US pathologists focused on stromal invasion when diagnosing adenocarcinoma. For colorectal neoplasia, the Korean pathologists identified concurrent intramucosal carcinoma when diagnosing invasive adenocarcinoma, while the presence of desmoplasia was a prerequisite for the diagnosis of invasive adenocarcinoma for the US pathologists. CONCLUSIONS: For GI neoplasia biopsy interpretation, the diagnostic approach of Korean pathologists is similar to that of Eastern/Japanese pathologists. Consensus outperformed kappa statistics in capturing the magnitude of inter-rater and intergroup reliability, highlighting the potential benefit of consensus meetings to decrease the gap between Western and Eastern diagnostic approaches.

Rainwater-Removal Image Conversion Learning with Training Pair Augmentation.

In this study, we proposed an image conversion method that efficiently removes raindrops on a camera lens from an image using a deep learning technique. The proposed method effectively presents a raindrop-removed image using the Pix2pix generative adversarial network (GAN) model, which can understand the characteristics of two images in terms of newly formed images of different domains. The learning method based on the captured image has the disadvantage that a large amount of data is required for learning and that unnecessary noise is generated owing to the nature of the learning model. In particular, obtaining sufficient original and raindrops images is the most important aspect of learning. Therefore, we proposed a method that efficiently obtains learning data by generating virtual water-drop image data and effectively identifying it using a convolutional neural network (CNN).

Combined Deep Learning Techniques for Mandibular Fracture Diagnosis Assistance.

Mandibular fractures are the most common fractures in dentistry. Since diagnosing a mandibular fracture is difficult when only panoramic radiographic images are used, most doctors use cone beam computed tomography (CBCT) to identify the patient's fracture location. In this study, considering the diagnosis of mandibular fractures using the combined deep learning technique, YOLO and U-Net were used as auxiliary diagnostic methods to detect the location of mandibular fractures based on panoramic images without CBCT. In a previous study, mandibular fracture diagnosis was performed using YOLO learning; in the detection performance result of the YOLOv4-based mandibular fracture diagnosis module, the precision score was approximately 97%, indicating that there was almost no misdiagnosis. In particular, fractures in the symphysis, body, angle, and ramus tend to be distributed in the middle of the mandible. Owing to the irregular fracture types and overlapping location information, the recall score was approximately 79%, which increased the detection of undiagnosed fractures. In many cases, fractures that are clearly visible to the human eye cannot be grasped. To overcome these shortcomings, the number of undiagnosed fractures can be reduced using a combination of the U-Net and YOLOv4 learning modules. U-Net is advantageous for the segmentation of fractures spread over a wide area because it performs semantic segmentation. Consequently, the undiagnosed case in the middle of the mandible, where YOLO was weak, was somewhat supplemented by the U-Net module. The precision score of the combined module was 95%, similar to that of the previous method, and the recall score improved to 87%, as the number of undiagnosed cases was reduced. Through this study, the performance of a deep learning method that can be used for the diagnosis of the mandibular bone has been improved, and it is anticipated that as an auxiliary diagnostic inspection device, it will assist dentists in making diagnoses.

Growth Pattern of Hepatic Metastasis as a Prognostic Index Reflecting Liver Metastasis-Associated Survival in Breast Cancer Liver Metastasis.

Breast cancer with liver metastasis (BCLM) frequently cause hepatic failure owing to extensive liver metastasis compared to other cancers; however, there are no clinicopathologic or radiologic parameters for estimating BCLM prognosis. We analyzed the relationship between radiologic and clinicopathologic characteristics with survival outcomes in BCLM. During 2009-2019, baseline and final abdomen computed tomography or liver magnetic resonance imaging of BCLM patients were reviewed. Liver metastasis patterns were classified as oligometastasis (≤3 metastatic lesions), non-confluent or confluent mass formation, infiltration, and pseudocirrhosis. Thirty-one surgical or biopsy specimens for liver metastasis were immunostained for L1 adhesion molecule (L1CAM), Yes-associated protein 1/Transcriptional co-activator with PDZ-binding motif (YAP/TAZ), and ß1-integrin. Out of 156 patients, 77 initially had oligometastasis, 58 had nonconfluent mass formation, 14 had confluent mass formation, and 7 had infiltrative liver metastasis. Confluent or infiltrative liver metastasis showed inferior liver metastasis-associated survival (LMOS) compared to others (p = 0.001). Positive staining for L1CAM and YAP/TAZ was associated with inferior survival, and YAP/TAZ was related to final liver metastasis. Initial hepatic metastasis was associated with LMOS, especially confluent mass formation, and infiltrative liver metastasis pattern was associated with poor survival. Positive staining for YAP/TAZ and L1CAM was associated with inferior LMOS, and YAP/TAZ was related to final liver metastasis.

Tone Image Classification and Weighted Learning for Visible and NIR Image Fusion.

In this paper, to improve the slow processing speed of the rule-based visible and NIR (near-infrared) image synthesis method, we present a fast image fusion method using DenseFuse, one of the CNN (convolutional neural network)-based image synthesis methods. The proposed method applies a raster scan algorithm to secure visible and NIR datasets for effective learning and presents a dataset classification method using luminance and variance. Additionally, in this paper, a method for synthesizing a feature map in a fusion layer is presented and compared with the method for synthesizing a feature map in other fusion layers. The proposed method learns the superior image quality of the rule-based image synthesis method and shows a clear synthesized image with better visibility than other existing learning-based image synthesis methods. Compared with the rule-based image synthesis method used as the target image, the proposed method has an advantage in processing speed by reducing the processing time to three times or more.

Deep Learning for Automatic Subclassification of Gastric Carcinoma Using Whole-Slide Histopathology Images.

Histomorphologic types of gastric cancer (GC) have significant prognostic values that should be considered during treatment planning. Because the thorough quantitative review of a tissue slide is a laborious task for pathologists, deep learning (DL) can be a useful tool to support pathologic workflow. In the present study, a fully automated approach was applied to distinguish differentiated/undifferentiated and non-mucinous/mucinous tumor types in GC tissue whole-slide images from The Cancer Genome Atlas (TCGA) stomach adenocarcinoma dataset (TCGA-STAD). By classifying small patches of tissue images into differentiated/undifferentiated and non-mucinous/mucinous tumor tissues, the relative proportion of GC tissue subtypes can be easily quantified. Furthermore, the distribution of different tissue subtypes can be clearly visualized. The patch-level areas under the curves for the receiver operating characteristic curves for the differentiated/undifferentiated and non-mucinous/mucinous classifiers were 0.932 and 0.979, respectively. We also validated the classifiers on our own GC datasets and confirmed that the generalizability of the classifiers is excellent. The results indicate that the DL-based tissue classifier could be a useful tool for the quantitative analysis of cancer tissue slides. By combining DL-based classifiers for various molecular and morphologic variations in tissue slides, the heterogeneity of tumor tissues can be unveiled more efficiently.

Automatic Detection of Mandibular Fractures in Panoramic Radiographs Using Deep Learning.

Mandibular fracture is one of the most frequent injuries in oral and maxillo-facial surgery. Radiologists diagnose mandibular fractures using panoramic radiography and cone-beam computed tomography (CBCT). Panoramic radiography is a conventional imaging modality, which is less complicated than CBCT. This paper proposes the diagnosis method of mandibular fractures in a panoramic radiograph based on a deep learning system without the intervention of radiologists. The deep learning system used has a one-stage detection called you only look once (YOLO). To improve detection accuracy, panoramic radiographs as input images are augmented using gamma modulation, multi-bounding boxes, single-scale luminance adaptation transform, and multi-scale luminance adaptation transform methods. Our results showed better detection performance than the conventional method using YOLO-based deep learning. Hence, it will be helpful for radiologists to double-check the diagnosis of mandibular fractures.

Interpretation of surficial shear crack propagation mechanisms in bending for Zn or AlSi coated hot press forming steels.

The bending angle at the peak load is regarded as the most important parameter for evaluating bending properties of hot-press-forming (HPF) steels. However, it is not a mechanics-based parameter for the bending criterion, and the data interpretation is difficult because bending criteria in relation with microstructures and associated bending mechanisms have not been verified yet. In this study, effects of coating and baking treatments on bending angles at the peak load of three kinds of 1470 MPa-grade HPF steels were investigated by interrupted three-point bending tests coupled with direct microstructural observation. According to direct observations of sequential cracking processes of V-shaped crack (V-crack), bending procedures were classified into four stages: (1) formation of small V-crack, (2) increase in number and size of V-cracks, (3) initiation of shear-crack propagation from the V-crack tip, and (4) further propagation and opening of the shear crack. The minimum bending angle required for initiating the shear-crack propagation from the V-crack tip was defined as a critical angle, which meant the boundary between the 2nd and 3rd stages. The present bending behavior related with critical bending angle and V-cracking could be interpreted similarly by the fracture-mechanics concept, i.e., the initiation of shear-crack propagation.

Preferential Expression of Programmed Death Ligand 1 Protein in Tumor-Associated Macrophages and Its Potential Role in Immunotherapy for Hepatocellular Carcinoma.

A predictive biomarker of immune checkpoint inhibitor (ICI)-based treatments in hepatocellular carcinoma (HCC) has not been clearly demonstrated. In this study, we focused on the infiltration and programmed death ligand 1 (PD-L1) expression of tumor-associated macrophages (TAMs) in the tumor microenvironment of HCC. Immunohistochemistry demonstrated that PD-L1 was preferentially expressed on CD68+ macrophages in the tumor microenvironment of HCC, suggestive of its expression in TAMs rather than in T cells or tumor cells (P < 0.05). A co-culture experiment using activated T cells and M2 macrophages confirmed a significant increase in T cell functionality after the pretreatment of M2 macrophages with anti-PD-L1. Syngeneic mouse model experiments demonstrated that TAMs expressed PD-L1 and tumors treated with anti-PD-L1 showed smaller diameters than those treated with IgG. In these mice, anti-PD-L1 treatment increased activation markers in intratumoral CD8+ T cells and reduced the size of the TAM population. Regarding nivolumab-treated patients, three of eight patients responded to the anti-PD-1 treatment. The percentage of Ki-67-positive CD4+ and CD8+ T cells was higher in responders than non-responders after nivolumab. Overall, PD-L1 expression on TAMs may be targeted by immune-based HCC treatment, and ICI treatment results in the reinvigoration of exhausted CD8+ T cells in HCC.

Effects of finish rolling temperature and yield ratio on variations in yield strength after pipe-forming of API-X65 line-pipe steels.

Flattened plates often show the lower or higher yield strength than initial leveled plates because tensile and compressive strains are repeatedly experienced at outer and inner walls during the pipe-forming and flattening, but reasons for the yield-strength variation after the pipe-forming are not sufficiently verified yet. In this study, ten line-pipe steels were fabricated by controlling alloying elements and finish rolling temperatures (FRTs), and the yield strength of pipe-flattened steel plates was predicted by using cyclic simulation tests, based on competing contributions of Bauschinger effect (BE) and strain hardening (SH) effect quantified from yield drop (YD) and yield rise (YR) parameters, respectively. High-FRT-treated steels (H steels) showed the lower BE and the higher SH than low-FRT-treated steels (L steels), thereby resulting in the smaller yield-strength reduction. This lower BE in the H steels was caused by the lower total boundary density, while the higher SH was caused by the higher fraction of granular bainite. According to the SH analyses between the YR parameters obtained from cyclic simulation tests and the yield ratios obtained from ordinary tensile tests, the decrease in yield-strength reduction with decreasing yield ratio was not attributed to the increase in ordinary tensile SH but to the increase in YR parameter.

Yield-strength prediction of flattened steel pipes by competing Bauschinger effect and strain hardening during pipe-forming.

Since flattened steel sheets often show the unexpectedly lower or higher yield strength than leveled sheets, unceasing efforts have been made to accurately predict the yield strength in pipe-forming industries. In the present investigation, the yield strength of line-pipe or casing-pipe steels was predicted by competing Bauschinger effect and strain hardening occurred during the pipe-forming. Yield drop (YD) and yield rise (YR) parameters were newly defined from cyclic simulation analyses of outer and inner walls of pipes to express more reasonably the Bauschinger effect and strain hardening. The YD increased abruptly until the pre-strain of about 1%, and then saturated, while the YR increased linearly with increasing pre-strain. By combining the YD and YR, the variation in yield strength (Δσ) showed a down-and-up behavior as the Bauschinger effect and strain hardening were dominant at low and high pre-strains, respectively, and plausibly explained the relationship of Δσ and piping strain used in pipe-forming industries. According to the microstructural analyses related to the down-and-up Δσ behavior, the polygonal ferrite reduced the yield-strength reduction in the low pre-strain range, whereas the granular bainite or pearlite expanded it. This yield strength prediction coupled with microstructural analyses provide a good idea for designing and reliably predicting the yield strength of in various steel pipes.

Synergetic strengthening of layered steel sheet investigated using an in situ neutron diffraction tensile test.

Synergetic strengthening induced by plastic strain incompatibility at the interface, and the resulting extra geometrically necessary dislocations (GNDs) generated during plastic deformation, were investigated to understand the origin of extra strength in heterogeneous structured (HS) materials. The mechanism of extra GND generation in twinning-induced plasticity (TWIP)-interstitial free (IF) steel layered sheet was quantitatively analyzed by conducting in situ neutron scattering tensile test. Load partitioning due to the different mechanical properties between the TWIP-steel core and IF-steel sheath at the TWIP/IF interface was observed during the in situ tensile testing. Because of the plastic strain incompatibility from load partitioning, extra GNDs are generated and saturate during tensile deformation. The extra GNDs can be correlated with the back-stress evolution of the HS materials, which contributes to the strength of layered materials. Because of the back-stress evolution caused by load partitioning, the strength of TWIP-IF layered steel is higher than the strength estimated by the rule-of-mixtures. This finding offers a mechanism by which extra GNDs are generated during load partitioning and shows how they contribute to the mechanical properties of HS materials.

Effects of strain rate on room- and cryogenic-temperature compressive properties in metastable V10Cr10Fe45Co35 high-entropy alloy.

Quasi-static and dynamic compressive properties of an FCC-based metastable HEA (composition; V10Cr10Fe45Co35 (at.%)) showing both Transformation Induced Plasticity (TRIP) and TWinning Induced Plasticity (TWIP) were investigated at room and cryogenic temperatures. During the quasi-static and dynamic compression at room temperature, the FCC to BCC TRIP occurred inside FCC grains, and resulted in very high strain-hardening rate and consequently maximum compressive strength over 1.6 GPa. The dynamic compressive strength was higher by 240 MPa than the quasi-static strength because of strain-rate-hardening effect, and kept increasing with a high strain-hardening rate as the twinning became activated. The cryogenic-temperature strength was higher than the room-temperature strength as the FCC to BCC TRIP amount increased by the decrease in stability of FCC phase with decreasing temperature. Under dynamic loading at cryogenic temperature, twins were not formed because the increase in SFE due to adiabatic heating might not be enough to reach the TWIP regime. However, the dynamically compressed specimen showed the higher strength than the quasi-statically compressed specimen as the strain-rate-hardening effect was added with the TRIP.

Effects of Mo addition on crack tip opening displacement (CTOD) in heat affected zones (HAZs) of high-strength low-alloy (HSLA) steels.

Effects of Mo addition on microstructures and crack tip opening displacement (CTOD) in heat affected zones (HAZs) of three high-strength low-alloy (HSLA) steels were investigated in this study, and the correlation between them was explained by fracture mechanisms related with martensite-austenite constituent (MA) characteristics. The coarse-grained HAZ (CGHAZ) consisted of acicular ferrite (AF), granular bainite (GB), and bainitic ferrite (BF), whereas the inter-critically heated HAZ (ICHAZ) consisted of quasi-polygonal ferrite (QPF), GB, and MA. Since Mo promoted the formation of GB, BF, and MA and prevented the formation of AF and QPF, the CTOD decreased in both HAZs with increasing Mo content. According to the interrupted three-point bending test results of the ICHAZ where many MAs were distributed in the QPF or GB matrix, many voids were observed mainly at MA/QPF interfaces, which implied that the void initiation at the interfaces was a major fracture mechanism. The atomic probe data of MAs indicated the segregation of C, Mn, Mo, and P at MA/QPF interfaces, which could result in the easy MA/matrix interfacial debonding to initiate voids. Thus, characteristics of MA/QPF interfaces might affect more importantly the CTOD than the MA volume fraction or size.

Study of Bauschinger effect of acicular ferrite and polygonal ferrite through ex-situ interrupted bending tests in API X80 linepipe steels.

Linepipe steels complexly consisted of low-temperature transformation microstructures of bainitic ferrite, granular bainite, and acicular ferrite (AF) as well as polygonal ferrite (PF) which individually affect the Bauschinger effect occurring during the pipe-forming. In this study, microscopic analyses of electron back-scattered diffraction (EBSD) coupled with tension-compression and interrupted bending tests were performed for verification of the Bauschinger effect of AF and PF working as major microstructures in single-phase- and two-phase-rolled API X80 steels, respectively. With respect to microstructural effects on Bauschinger effect, the reduction in mobile dislocation density during the flattening was smaller in the AF than in the PF. However, the dislocation pile-up at low-angle substructures and high-angle grain boundaries was more frequently observed, thereby leading to the higher back stress and Bauschinger effect in the AF. Boundary kernel average misorientation (KAM) profile played a critical role in determining the Bauschinger effect because they were closely related with the back stress. Thus, the Bauschinger effect was higher in the single-phase-rolled steel than in the two-phase-rolled steel. The present ex-situ interrupted bending methods coupled with EBSD analyses are outstanding ones for the detailed explanation of Bauschinger effect and provide an important idea for the yield strength designs of linepipe steels.

Use of the Ion AmpliSeq Cancer Hotspot Panel in clinical molecular pathology laboratories for analysis of solid tumours: With emphasis on validation with relevant single molecular pathology tests and the Oncomine Focus Assay.

Targeted application of next-generation sequencing (NGS) technology allows detection of specific mutations that can provide treatment opportunities for cancer patients. We evaluated the applicability of the Ion AmpliSeq Cancer Hotspot Panel V2 (CHV2) using formalin-fixed, paraffin-embedded (FFPE) tissue of clinical specimens. Thirty-five FFPE tumour samples with known mutational status were collected from four different hospitals and sequenced with CHV2 using an Ion Chef System and Ion S5 XL system. Out of 35 cases, seven were sequenced with Oncomine focus Assay Panel for comparison. For the limit of detection test, we used an FFPE reference standard, a cell line that included an engineered 50% EGFR T790 M in an RKO cell line background. Coverage analysis results including number of mapped reads, on target percent, mean depth, and uniformity were not different according to hospitals. Sensitivity for mutation detection down to 3% was demonstrated. NGS results showed 100% concordance with the results from single molecular pathology tests Assay in 30 cases with 24 known positive mutations and 14 known negative mutations, and another NGS panel of the Oncomine focus in seven cases. The CHV2 NGS test for solid tumours using Ion chef system and S5 XL system in clinical molecular pathology laboratories for analysis of solid tumours could be routinely used and could replace some single molecular pathology tests after a stringent and thorough validation process.

Interpretation of dynamic tensile behavior by austenite stability in ferrite-austenite duplex lightweight steels.

Phenomena occurring in duplex lightweight steels under dynamic loading are hardly investigated, although its understanding is essentially needed in applications of automotive steels. In this study, quasi-static and dynamic tensile properties of duplex lightweight steels were investigated by focusing on how TRIP and TWIP mechanisms were varied under the quasi-static and dynamic loading conditions. As the annealing temperature increased, the grain size and volume fraction of austenite increased, thereby gradually decreasing austenite stability. The strain-hardening rate curves displayed a multiple-stage strain-hardening behavior, which was closely related with deformation mechanisms. Under the dynamic loading, the temperature rise due to adiabatic heating raised the austenite stability, which resulted in the reduction in the TRIP amount. Though the 950 °C-annealed specimen having the lowest austenite stability showed the very low ductility and strength under the quasi-static loading, it exhibited the tensile elongation up to 54% as well as high strain-hardening rate and tensile strength (1038 MPa) due to appropriate austenite stability under dynamic loading. Since dynamic properties of the present duplex lightweight steels show the excellent strength-ductility combination as well as continuously high strain hardening, they can be sufficiently applied to automotive steel sheets demanded for stronger vehicle bodies and safety enhancement.