Search

Background: Brain atrophy represents a final common pathway for pathological processes in patients with cerebral small vessel disease (CSVD) and is now recognized as a strong independent predictor of clinical status and progression. The mechanism underlying brain atrophy in patients with CSVD is not yet fully comprehended. This study aims to investigate the association of morphologic features of intracranial distal arteries (A2, M2, P2 and more distal) with different brain structures [gray matter volume (GMV), white matter volume (WMV), and cerebrospinal fluid volume (CSFV)]. Furthermore, we also examined whether a correlation existed between these cerebrovascular characteristics and GMV in different brain regions. Method: A total of 39 participants were eventually enrolled. The morphologic features of intracranial distal arteries based on TOF-MRA were extracted and quantified using the intracranial artery feature extraction technique (iCafe). The brain 3D-T1 images were segmented into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using the "Segment" tool in CAT12 for the voxel-based morphometry (VBM) analysis. Univariable and multivariable linear regression models were used to investigate the relationship between these cerebrovascular features and different brain structures. Partial correlation analysis with a one-tailed method was used to evaluate the relationship between these cerebrovascular features and GMV in different brain regions. Results: Our findings indicate that both distal artery length and density were positively correlated with GM fraction in CSVD patients, regardless of whether univariable or multivariable linear regression analyses were performed. In addition, distal artery length (ß = -0.428, p = 0.007) and density (ß = -0.337, p = 0.036) were also found to be negative associated with CSF fraction, although this relationship disappeared after adjusting for potential confounders. Additional adjustment for the effect of WMHs volume did not change these results. In subgroup anasysis, we found that participants in the highest distal artery length tertile had significantly higher GM fraction and lower CSF fraction level than participants in the lowest distal artery length tertile. In partial correlation analysis, we also found that these cerebrovascular characteristics associated with regional GMV, especially subcortical nuclear. Conclusion: The morphologic features of intracranial distal arteries, including artery length, density and average tortuosity, measured from 3D-TOF MRA, are associated with generalized or focal atrophy indexes of CSVD. [ABSTRACT FROM AUTHOR]

Objectives: The association between preoperative D-dimer with morphologic features and surgical outcomes of acute type A aortic dissection is still unclear., Methods: 430 acute type A aortic dissection patients who underwent total arch replacement and frozen elephant trunk in Beijing Anzhen Hospital of Capital Medical University between January 2016 and December 2020 were enrolled in the present study. Patients were divided into higher D-dimer (>2307 ng/ml) group and lower D-dimer (≤2307 ng/ml) group. We compared the extent of dissection and branch artery perfusion patterns between the 2 groups. The restricted cubic spline was performed to assess the association between D-dimer with the extent of dissection and major adverse events after surgery., Results: Among 430 patients, there were 45 (10.47%) in-hospital mortality and 156 (36.28%) major adverse events. Patients with higher D-dimer had bigger dissection extension length and false lumen perimeter in ascending aorta, thoracic descending aorta, diaphragmatic, coeliac trunk and renal artery level. For the branch artery perfusion patterns, patients with higher D-dimer had a higher proportion of malperfusion among the innominate artery, right renal artery and both side iliac arteries, a higher proportion of dissected intercostal artery/all intercostal arteries >0.5 (43.46% vs 29.63%, P = 0.003). The restricted cubic spline linear regression model revealed a nonlinear association between lnD-dimer with extension length and false lumen perimeter (all P for overall and P for nonlinearity <0.001 except false lumen perimeter in ascending aorta level). The restricted cubic spline logistic regression model revealed a linear association between lnD-dimer with major adverse events (P for overall <0.001, P for nonlinearity = 0.637). The association between lnD-dimer and major adverse events was still significant in the fully adjusted logistic regression model with computed tomography angiography characteristics [odds ratio (95% confidence interval) =1.388 (1.137, 1.695), P = 0.001]., Conclusions: Preoperative D-dimer strongly and positively correlates with the extent of dissection and major adverse events of acute type A aortic dissection after total arch replacement and frozen elephant trunk. D-dimer seems to be a supplement that indicates the severity of aortic dissection to aortic computed tomography angiography., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery.)

ObjectiveThe aim of this study was to develop and compare multimodal models for predicting outcomes after endovascular abdominal aortic aneurysm repair (EVAR) based on morphological, deep learning (DL), and radiomic features.MethodsWe retrospectively reviewed 979 patients (January 2010—December 2019) with infrarenal abdominal aortic aneurysms (AAAs) who underwent elective EVAR procedures. A total of 486 patients (January 2010–December 2015) were used for morphological feature model development and optimization. Univariable and multivariable analyses were conducted to determine significant morphological features of EVAR-related severe adverse events (SAEs) and to build a morphological feature model based on different machine learning algorithms. Subsequently, to develop the morphological feature model more easily and better compare with other modal models, 340 patients of AAA with intraluminal thrombosis (ILT) were used for automatic segmentation of ILT based on deep convolutional neural networks (DCNNs). Notably, 493 patients (January 2016–December 2019) were used for the development and comparison of multimodal models (optimized morphological feature, DL, and radiomic models). Of note, 80% of patients were classified as the training set and 20% of patients were classified as the test set. The area under the curve (AUC) was used to evaluate the predictive abilities of different modal models.ResultsThe mean age of the patients was 69.9 years, the mean follow-up was 54 months, and 307 (31.4%) patients experienced SAEs. Statistical analysis revealed that short neck, angulated neck, conical neck, ILT, ILT percentage ≥51.6%, luminal calcification, double iliac sign, and common iliac artery index ≥1.255 were associated with SAEs. The morphological feature model based on the support vector machine had a better predictive performance with an AUC of 0.76, an accuracy of 0.76, and an F1 score of 0.82. Our DCNN model achieved a mean intersection over union score of more than 90.78% for the segmentation of ILT and AAA aortic lumen. The multimodal model result showed that the radiomic model based on logistics regression had better predictive performance (AUC 0.93, accuracy 0.86, and F1 score 0.91) than the optimized morphological feature model (AUC 0.62, accuracy 0.69, and F1 score 0.81) and the DL model (AUC 0.82, accuracy 0.85, and F1 score 0.89).ConclusionThe radiomic model has better predictive performance for patient status after EVAR. The morphological feature model and DL model have their own advantages and could also be used to predict outcomes after EVAR.

Introduction. The relevance of the study lies in the fact that the Udmurt written monuments are studied only partially at the moment. Today more than 400 names of pre-revolutionary Udmurt monuments are known, but most of them are still not described. An analysis of written monuments is necessary, because they provide important information for language reconstruction, and besides that, they help to determine the chronology of linguistic phenomena. Materials and Methods. The description of morphological characteristics in the article is based on the previously identified graphic and phonetic features of the translation of «God’s law» in the Udmurt language. It involved the method of comparing the linguistic material of the work with the data of the literary language and modern Udmurt dialects. Results and Discussion. As a result of the analysis of «God’s law» in the Udmurt language, we revealed some features in the design of morphological indicators of plural, possessiveness, some case and verb forms, as well as pronouns. Conclusion. A comparison of the linguistic data of the “God’s Law” with the literary language and modern Udmurt dialects confirmed the hypothesis regarding the dialectic affiliation of the written source.

Introduction: Intracranial aneurysms (IAs) are a common vascular pathology and are associated with a risk of rupture, which is often fatal. Aneurysm growth is considered a surrogate of rupture risk; therefore, the study aimed to develop and evaluate prediction models of future artificial intelligence (AI) growth based on baseline aneurysm morphology as a computer-aided treatment decision support.Materials and methods: Follow-up CT angiography (CTA) and magnetic resonance angiography (MRA) angiograms of 39 patients with 44 IAs were classified by an expert as growing and stable (25/19). From the angiograms vascular surface meshes were extracted and the aneurysm shape was characterized by established morphologic features and novel deep shape features. The features corresponding to the baseline aneurysms were used to predict future aneurysm growth using univariate thresholding, multivariate random forest and multi-layer perceptron (MLP) learning, and deep shape learning based on the PointNet++ model.Results: The proposed deep shape feature learning method achieved an accuracy of 0.82 (sensitivity = 0.96, specificity = 0.63), while the multivariate learning and univariate thresholding methods were inferior with an accuracy of up to 0.68 and 0.63, respectively.Conclusion: High-performing classification of future growing IAs renders the proposed deep shape features learning approach as the key enabling tool to manage rupture risk in the “no treatment” paradigm of patient follow-up imaging.

Introduction: Intracranial aneurysms (IAs) are a common vascular pathology and are associated with a risk of rupture, which is often fatal. Aneurysm growth is considered a surrogate of rupture risk; therefore, the study aimed to develop and evaluate prediction models of future artificial intelligence (AI) growth based on baseline aneurysm morphology as a computer-aided treatment decision support. Materials and methods: Follow-up CT angiography (CTA) and magnetic resonance angiography (MRA) angiograms of 39 patients with 44 IAs were classified by an expert as growing and stable (25/19). From the angiograms vascular surface meshes were extracted and the aneurysm shape was characterized by established morphologic features and novel deep shape features. The features corresponding to the baseline aneurysms were used to predict future aneurysm growth using univariate thresholding, multivariate random forest and multi-layer perceptron (MLP) learning, and deep shape learning based on the PointNet++ model. Results: The proposed deep shape feature learning method achieved an accuracy of 0.82 (sensitivity = 0.96, specificity = 0.63), while the multivariate learning and univariate thresholding methods were inferior with an accuracy of up to 0.68 and 0.63, respectively. Conclusion: High-performing classification of future growing IAs renders the proposed deep shape features learning approach as the key enabling tool to manage rupture risk in the "no treatment" paradigm of patient follow-up imaging. [ABSTRACT FROM AUTHOR]

Objective: Aneurysm rupture risk can be assessed by its morphologic and hemodynamics features extracted based on angiographic images. Feature extraction entails aneurysm isolation, typically by manually positioning a cutting plane (MCP). To eliminate intra- and inter-rater variabilities, we propose automatic cutting plane (ACP) positioning based on the analysis of vascular surface mesh. Methods: Innovative Hough-like and multi-hypothesis-based detection of aneurysm center, parent vessel inlets, and centerlines were proposed. These were used for initialization and iterative ACP positioning by geometry-inspired cost function optimization. For validation and baseline comparison, we tested MCP and manual neck curve-based isolation. Isolated aneurysm morphology was characterized by size, dome height, aspect ratio, and nonsphericity index. Results: Methods were applied to 55 intracranial saccular aneurysms from two sites, involving 3-D digital subtraction angiography, computed tomography angiography, and magnetic resonance angiography modalities. Isolation based on ACP resulted in smaller average inter-curve distances (AICDs), compared to those obtained by MCP. One case had AICD higher than 1.0 mm, while 90% of cases had AICD $< $ 0.5 mm. Intra- and inter-rater AICD variability of manual neck curves was higher compared to MCP, validating its robustness for clinical purposes. Conclusion: The ACP method achieved high accuracy and reliability of aneurysm isolation, also confirmed by expert visual analysis. So extracted morphologic features were in good agreement with MCP-based ones, therefore, ACP has great potential for aneurysm morphology and hemodynamics quantification in clinical applications. Significance: The novel method is angiographic modality agnostic; it delivers repeatable isolation important in follow-up aneurysm assessment; its performance is comparable to MCP; and re-evaluation is fast and simple. [ABSTRACT FROM AUTHOR]

Potmarigold, scientifically known as Calendula officinalis L., has shown great medicinal properties, in addition to its use in landscapes. Because of this and sustainable agricultural development, and in order to explore the effect of different fertilizing methods, an experiment was performed, in which the effects of biological phosphate fertilizer, Barvar-2, and NPK fertilizer, as conventional chemical fertilizers, on the growth characteristics and the amount of phosphorous in plant tissue of Potmarigold were compared with different ratios separately and in combination. This research was conducted in the fields of the Department of Agriculture in Ramin Faculty of Agriculture and Natural Resources in Khuzestan, Iran, in cropping season 2012-2013. This factorial experiment was carried out in a randomized complete block design with three replications and 27 experimental plots. The factors included phosphate biofertilizer in 3 levels [zero(a1), seed treatment(a2) and road(a3)] and complete fertilizer, NPK, on 3 levels [ zero(b1), 150(b2) and 300 Kg/hectar(b3)]. Studies have shown the maximum numbers of flowers (161.995) and leaves (717.17) per plant were found in co-application of chemical fertilizer. Also the maximum height were found in the combination of the second level of NPK fertilizer (106.6 cm). But the highest P content of the tissuewere found in control treatment (0.002 mg/gr). The results of this research showed that the combined use of seed treatment of phosphate biofertilizer with the second level of the complete fertilizer, NPK, resulted in the improvement of the measured traits, and can thus be recommended in order to increase productivity.

Purpose. To characterize the morphometric and morphologic peculiarities of peled grown in ponds of the aquaculture farms “Okonsk” and “Korop” for creating the initial brood stock for its further use for broadening species diversity in fish farms of Ukraine. Methodology. The study materials were the young-of-the-year and yearlings of peled obtained from the eggs imported in March 2008 from Russian Federation. According to Pravdin’s method, 27 plastic features, which are used most frequently for biological and systematic analyses, have been examined. The analysis of plastic features was carried out in the system of absolute values and in the index system – as percentages of the body length by Smith. Based on the analysis of the features, we examined their mean values (M± m), deviation (δ), and coefficient of variation (Cv). Findings. Based on the obtained data and available literature data, we carried out a comparative analysis of morphometric features of young-of-the-year peled grown in pond conditions of Polissya and Prykarpattya. An analysis of plastic and meristic features of yearlings with young-of-the-years has been conducted. A comparative analysis of the morphometric features of the yearlings reared in the conditions of Polissya with those of native water bodies from literature data has been carried out.With an increase in the body length in experimental fish, there is a decrease in the highest and lowest body depth values, anterodorsal distance, head and eye lengths, an increase in the values of pectoventral, postdorsal, anteanal distance and the dorsal fin height. Compared to fish from native water bodies, the examined fish are characterized by an increase in the snout length, eye diameter, head length, caudal peduncle length; a decrease in the anteanal, anteroventral, ventral distances, length of the base and height of the dorsal and abdominal fins. Originality. For the first time we carried out works on the study of the peculiarities of peled growth based on morphometric features in the conditions of their combined rearing in the Polissya and Prykarpattya zones. The obtained results will allow widening our knowledge on the topics of peled culture in pond farms in Ukraine. Practical value. The obtained results showed the plasticity of peled in the conditions of their combined rearing in the Polissya and Prykarpattya zones of Ukraine that will contribute to the creation of local brood stocks of peled.

Objective: The main goal of this study was to develop an automatic method based on supervised learning methods, able to distinguish healthy from pathologic arterial pulse wave (APW), and those two from noisy waveforms (non-relevant segments of the signal), from the data acquired during a clinical examination with a novel optical system.Materials and Methods: The APW dataset analysed was composed by signals acquired in a clinical environment from a total of 213 subjects, including healthy volunteers and non-healthy patients. The signals were parameterised by means of 39pulse features: morphologic, time domain statistics, cross-correlation features, wavelet features. Multiclass Support Vector Machine Recursive Feature Elimination (SVM RFE) method was used to select the most relevant features. A comparative study was performed in order to evaluate the performance of the two classifiers: Support Vector Machine (SVM) and Artificial Neural Network (ANN).Results and Discussion: SVM achieved a statistically significant better performance for this problem with an average accuracy of 0.9917±0.0024 and a F-Measure of 0.9925±0.0019, in comparison with ANN, which reached the values of 0.9847±0.0032 and 0.9852±0.0031 for Accuracy and F-Measure, respectively. A significant difference was observed between the performances obtained with SVM classifier using a different number of features from the original set available.Conclusion: The comparison between SVM and NN allowed reassert the higher performance of SVM. The results obtained in this study showed the potential of the proposed method to differentiate those three important signal outcomes (healthy, pathologic and noise) and to reduce bias associated with clinical diagnosis of cardiovascular disease using APW. [ABSTRACT FROM AUTHOR]

Background: Brain atrophy represents a final common pathway for pathological processes in patients with cerebral small vessel disease (CSVD) and is now recognized as a strong independent predictor of clinical status and progression. The mechanism underlying brain atrophy in patients with CSVD is not yet fully comprehended. This study aims to investigate the association of morphologic features of intracranial distal arteries (A2, M2, P2 and more distal) with different brain structures [gray matter volume (GMV), white matter volume (WMV), and cerebrospinal fluid volume (CSFV)]. Furthermore, we also examined whether a correlation existed between these cerebrovascular characteristics and GMV in different brain regions., Method: A total of 39 participants were eventually enrolled. The morphologic features of intracranial distal arteries based on TOF-MRA were extracted and quantified using the intracranial artery feature extraction technique (iCafe). The brain 3D-T1 images were segmented into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using the "Segment" tool in CAT12 for the voxel-based morphometry (VBM) analysis. Univariable and multivariable linear regression models were used to investigate the relationship between these cerebrovascular features and different brain structures. Partial correlation analysis with a one-tailed method was used to evaluate the relationship between these cerebrovascular features and GMV in different brain regions., Results: Our findings indicate that both distal artery length and density were positively correlated with GM fraction in CSVD patients, regardless of whether univariable or multivariable linear regression analyses were performed. In addition, distal artery length ( β  = -0.428, p  = 0.007) and density ( β  = -0.337, p  = 0.036) were also found to be negative associated with CSF fraction, although this relationship disappeared after adjusting for potential confounders. Additional adjustment for the effect of WMHs volume did not change these results. In subgroup anasysis, we found that participants in the highest distal artery length tertile had significantly higher GM fraction and lower CSF fraction level than participants in the lowest distal artery length tertile. In partial correlation analysis, we also found that these cerebrovascular characteristics associated with regional GMV, especially subcortical nuclear., Conclusion: The morphologic features of intracranial distal arteries, including artery length, density and average tortuosity, measured from 3D-TOF MRA, are associated with generalized or focal atrophy indexes of CSVD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Cheng, Teng, Jia, Xu, Yang, Li, Ling, Liu, Li, Li, Guo, Geng, Guo and Zhang.)

Breast cancer is one of the most common malignancies among women and considered as the first caise of mortality in females suffering from malignant processes.axillary lymph node metastasis (ALNM)is the most important predictor of survival in patient with breast carcinoma.the purpose of this study was to determine the association between the incidence of ALNM and morphologic criteria by univariate and multivariate analysis.the authors reviwed data from 180 patients with breast carcinoma,who have been treated by modified radical mastectomy in hospitals of Kerman during 1989 to 1998.approximately 130 patients (72%) had axillary lymph nodes metastasis,but 30 patients (28%) had no metastasis,multivariate analysis identified four factors as independent predictors of ALNM,such as lymphatic/vascular invasion,perineural invasion,tumoral necrosis and histologic grade,(p=

Aiming to evaluate the development of seedlings of Schinus terebinthifolius under different irrigation depth, an experiment was installed in a greenhouse. The experimental design used was randomized block consisting of 4 treatments with 3 blocks. The irrigation depths evaluated were 8, 10, 12 and 14 mm daily, respectively T1, T2, T3 and T4. Seedling production was performed in tubes with 280 cm³ filled with pine bark basis substrate and fertilizer. The development of the seedlings, were evaluated by the following characteristics: height of aerial part (APA), diameter at breast height (D),dried mass weight of roots (PMSR), dried mass weight of aerial part (PMSPA), total dried mass (MST) and relation (h/d). The treatment T3 presented the best results in relation to the appraised variables, followed by T2. The Schinus terebenthifolius needs a daily sheet of water of around 10 mm, which is smaller than other pioneer species. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to develop and compare multimodal models for predicting outcomes after endovascular abdominal aortic aneurysm repair (EVAR) based on morphological, deep learning (DL), and radiomic features., Methods: We retrospectively reviewed 979 patients (January 2010-December 2019) with infrarenal abdominal aortic aneurysms (AAAs) who underwent elective EVAR procedures. A total of 486 patients (January 2010-December 2015) were used for morphological feature model development and optimization. Univariable and multivariable analyses were conducted to determine significant morphological features of EVAR-related severe adverse events (SAEs) and to build a morphological feature model based on different machine learning algorithms. Subsequently, to develop the morphological feature model more easily and better compare with other modal models, 340 patients of AAA with intraluminal thrombosis (ILT) were used for automatic segmentation of ILT based on deep convolutional neural networks (DCNNs). Notably, 493 patients (January 2016-December 2019) were used for the development and comparison of multimodal models (optimized morphological feature, DL, and radiomic models). Of note, 80% of patients were classified as the training set and 20% of patients were classified as the test set. The area under the curve (AUC) was used to evaluate the predictive abilities of different modal models., Results: The mean age of the patients was 69.9 years, the mean follow-up was 54 months, and 307 (31.4%) patients experienced SAEs. Statistical analysis revealed that short neck, angulated neck, conical neck, ILT, ILT percentage ≥51.6%, luminal calcification, double iliac sign, and common iliac artery index ≥1.255 were associated with SAEs. The morphological feature model based on the support vector machine had a better predictive performance with an AUC of 0.76, an accuracy of 0.76, and an F1 score of 0.82. Our DCNN model achieved a mean intersection over union score of more than 90.78% for the segmentation of ILT and AAA aortic lumen. The multimodal model result showed that the radiomic model based on logistics regression had better predictive performance (AUC 0.93, accuracy 0.86, and F1 score 0.91) than the optimized morphological feature model (AUC 0.62, accuracy 0.69, and F1 score 0.81) and the DL model (AUC 0.82, accuracy 0.85, and F1 score 0.89)., Conclusion: The radiomic model has better predictive performance for patient status after EVAR. The morphological feature model and DL model have their own advantages and could also be used to predict outcomes after EVAR., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor ZL is currently organizing a Research Topic with WF., (Copyright © 2022 Wang, Zhou, Ding, Li, Zhou, Shi and Fu.)

Multiple endocrine neoplasia type 1 (MEN-1) is an inherited syndrome which is characterized by the occurrence of neoplastic lesions in the parathyroids, the pancreas, duodenum, anterior pituitary and, less commonly, also in the stomach, thymus and lung. Its genetic defect has recently been identified and appears to involve a new type of tumour suppressor gene called mu on chromosome 11q13. In this overview, we will summarize the morphological features of the MEN-1 phenotype, discuss its clinicopathologic profile and prognosis and outline the recent findings on the molecular pathology of this syndrome. [ABSTRACT FROM AUTHOR]

Background: Magnetic resonance imaging (MRI) is currently the standard investigation for suspected perianal diseases. Carcinoma arising from anal fistula is very rare, and early diagnosis is often difficult., Aim: To describe and summarize the MRI findings of carcinoma arising from anal fistula., Methods: In this retrospective study, records of ten patients diagnosed with carcinoma arising from anal fistula and confirmed by surgery ( n = 7) or biopsy ( n = 3) between June 2006 and August 2018 were analyzed. All patients underwent preoperative pelvic MRI. Morphologic features, signal characteristics, fistula between the mass and the anus, contrast enhancement of mass, signal and enhancement of peritumoral areas, and regional lymphadenopathy were assessed., Results: All ten tumors were solitary (8 mucinous adenocarcinomas and 2 adenocarcinomas). The maximum diameter of the tumors ranged from 3.4 cm to 12.4 cm (median: 4.15 cm; mean: 5.68 cm). Eight patients had a fistula between the mass and the anus. Contrast enhancement of the peritumoral areas was noted in three (3/5) patients. Perirectal or inguinal lymphadenopathy was noted in seven patients. Most lesions of mucinous adenocarcinoma were multiloculated and cauliflower-like, with a thin capsule and focally unclear boundary. They were markedly hyperintense on fat-suppressed T2WI, slightly hyperintense with focal hyperintensity on diffusion-weighted imaging (DWI), and hyperintense with focal hypointensity on apparent diffusion coefficient (ADC) map, with progressive mesh-like contrast enhancement. Adenocarcinomas had an infiltrative margin without a capsule and appeared heterogeneously hyperintense or slightly hyperintense on fat-suppressed T2WI, hyperintense on DWI, and hypointense on ADC map, with persistent heterogeneous enhancement., Conclusion: Our study highlighted several characteristic and potentially helpful MRI findings to diagnose carcinomas arising from anal fistula., Competing Interests: Conflict-of-interest statement: The authors declare that they have no conflict of interest., (©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.)

Background/aims: Brain and bone metastases are common in patients with lung cancer. The development of metastasis is associated with poor survival in lung cancer patients. Although tumor morphologic features on radiographs are routinely assessed for differentiation between benign and malignant lung nodules, they are not used to predict metastasis. We assessed morphologic features of pulmonary adenocarcinomas with brain/bone metastasis on computed tomography (CT) to identify related factors for metastasis., Methods: We performed a retrospective analysis of initial chest CT findings (size, type of contour, percentage of necrosis, enhancement, presence or absence of calcification, and air cavity) from 2009 to 2010 of patients with brain or bone metastasis and compared the findings with those of patients without metastases., Results: In total, 128 patients were included (78 men, 52 women; mean age 69 years; range, 36 to 87). Nineteen patients had brain metastases and 32 had bone metastases. Morphologic features associated with brain metastasis included size ≥ 50 mm (odds ratio [OR], 3.37; 95% confidence interval [CI], 1.24 to 9.17; p = 0.013), necrosis ≥ 30% (OR, 4.51; 95% CI, 1.62 to 12.55; p =0.002), and presence of calcification (OR, 3.97; 95% CI, 1.16 to 13.55; p = 0.035). Morphologic features associated with bone metastasis included necrosis ≥ 30% (OR, 4.639; 95% CI, 1.98 to 10.82; p < 0.001) and T 3 to 4 stage (OR, 2.53; 95% CI, 1.07 to 6.00; p = 0.031)., Conclusions: We found that necrosis ≥ 30% was associated with pulmonary adenocarcinoma with brain and bone metastasis at initial chest CT morphologic feature. To validate these results, further research should be conducted.

Clear cell carcinoma of the endometrium (CCC) is an uncommon histotype whose analyses have generally been hampered by its rarity and issues of interobserver diagnostic variability. In this study, we analyzed the clinicopathologic features of 50 CCCs that were assembled from multiple institutions and which we considered to be morphologically unambiguous after a rigorous review process for diagnostic accuracy. Forty-four (88%) of the 50 CCC cases showed an admixture of the classic architectural patterns (glandular, papillary, solid and cystic in decreasing order of prevalence). Mitotic indices were variable but were generally low: 60% of cases had a mitotic index of 3 or lower. The predominant cell type lining glands and papillae was invariably hobnail and/or cuboidal. Stratification of nuclei (greater than 3 cells) or columnar cells on glands and papillae were uncommon and never diffusely present. 82% of cases showed an admixture of polygonal cells with clear and eosinophilic cytoplasm; only clear cells were present in 4% and only eosinophilic cells were present in 10%. Hobnail cells were common, being identifiable in 86% of cases, and being diffuse in 60%. Only 2 cases had a predominance of nuclear grade 3 cells. Psammoma, hyaline and targetoid bodies were identified in 32%, 52% and 20% of cases respectively. Clear cell endometrial intraepithelial carcinoma was identified in 41.7% of cases with evaluable background endometrium. The 5-year progression free survival (PFS) for the entire cohort was 61%, and was 88%, 75%, 22% and 28.6% for stages I to IV respectively. On univariate analyses, age >65 years, advanced FIGO stage, and the presence of any lymph node metastases were associated with reduced PFS (p=0.02, 0.002, and 0.002 respectively). On multivariate analyses, the only variable associated with reduced PFS was age >65 years. The 5-year overall survival (OS) for the entire cohort was 78%, and was 94%, 87.5%, 66.7%, and 42.8% for stages I to IV respectively. On univariate analyses, the following factors were associated with reduced OS: age >65 years (p=0.04), advanced FIGO stage (p=0.003), distant metastases (p=0.003), myometrial invasion >30% (p=0.01), a mitotic index >4 (p=0.014), and a specific architectural pattern (at least 10% of the tumor composed of solid masses or individual infiltrating tumor cells, p=0.02). On multivariate analyses, only age >65 years and advanced stage were associated with reduced OS (p=0.023 and 0.022 respectively). In summary, endometrial CCC has a wide morphologic spectrum that is detailed and illustrated herein, but also has core cytoarchitectural features that are of high diagnostic utility. Morphologically unambiguous CCC apparently have patient outcomes that are more favorable than has previously been reported, indicating that ambiguous tumors should be classified separately. The existence of morphologically ambiguous clear-cell rich carcinomas that do not fit the conventional histotypic groupings, is a likely reflection of the biologic complexity of endometrial carcinomas in general; these cases should be reported descriptively, and studied separately from conventional CCC.