A New Breakpoint to Classify 3D Voxels in MRI: A Space Transform Strategy with 3t2FTS-v2 and Its Application for ResNet50-Based Categorization of Brain Tumors.

Three-dimensional (3D) image analyses are frequently applied to perform classification tasks. Herein, 3D-based machine learning systems are generally used/generated by examining two designs: a 3D-based deep learning model or a 3D-based task-specific framework. However, except for a new approach named 3t2FTS, a promising feature transform operating from 3D to two-dimensional (2D) space has not been efficiently investigated for classification applications in 3D magnetic resonance imaging (3D MRI). In other words, a state-of-the-art feature transform strategy is not available that achieves high accuracy and provides the adaptation of 2D-based deep learning models for 3D MRI-based classification. With this aim, this paper presents a new version of the 3t2FTS approach (3t2FTS-v2) to apply a transfer learning model for tumor categorization of 3D MRI data. For performance evaluation, the BraTS 2017/2018 dataset is handled that involves high-grade glioma (HGG) and low-grade glioma (LGG) samples in four different sequences/phases. 3t2FTS-v2 is proposed to effectively transform the features from 3D to 2D space by using two textural features: first-order statistics (FOS) and gray level run length matrix (GLRLM). In 3t2FTS-v2, normalization analyses are assessed to be different from 3t2FTS to accurately transform the space information apart from the usage of GLRLM features. The ResNet50 architecture is preferred to fulfill the HGG/LGG classification due to its remarkable performance in tumor grading. As a result, for the classification of 3D data, the proposed model achieves a 99.64% accuracy by guiding the literature about the importance of 3t2FTS-v2 that can be utilized not only for tumor grading but also for whole brain tissue-based disease classification.

COVID-19 discrimination framework for X-ray images by considering radiomics, selective information, feature ranking, and a novel hybrid classifier.

In medical imaging procedures for the detection of coronavirus, apart from medical tests, approval of diagnosis has special significance. Imaging procedures are also useful for detecting the damage caused by COVID-19. Chest X-ray imaging is frequently used to diagnose COVID-19 and different pneumonias. This paper presents a task-specific framework to detect coronavirus in X-ray images. Binary classification of three different labels (healthy, bacterial pneumonia, and COVID-19) was performed on two differentiated data sets in which corona is stated as positive. First-order statistics, gray level co-occurrence matrix, gray level run length matrix, and gray level size zone matrix were analyzed to form fifteen sub-data sets and to ascertain the necessary radiomics. Two normalization methods are compared to make the data meaningful. Furthermore, five feature ranking approaches (Bhattacharyya, entropy, Roc, t-test, and Wilcoxon) are mentioned to provide necessary information to a state-of-the-art classifier based on Gauss-map-based chaotic particle swarm optimization and neural networks. The proposed framework was designed according to the analyses about radiomics, normalization approaches, and filter-based feature ranking methods. In experiments, seven metrics were evaluated to objectively determine the results: accuracy, area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, g-mean, precision, and f-measure. The proposed framework showed promising scores on two X-ray-based data sets, especially with the accuracy and area under the ROC curve rates exceeding 99% for the classification of coronavirus vs. others.

A comprehensive study of brain tumour discrimination using phase combinations, feature rankings, and hybridised classifiers.

The binary categorisation of brain tumours is challenging owing to the complexities of tumours. These challenges arise because of the diversities between shape, size, and intensity features for identical types of tumours. Accordingly, framework designs should be optimised for two phenomena: feature analyses and classification. Based on the challenges and difficulty of the issue, limited information or studies exist that consider the binary classification of three-dimensional (3D) brain tumours. In this paper, the discrimination of high-grade glioma (HGG) and low-grade glioma (LGG) is accomplished by designing various frameworks based on 3D magnetic resonance imaging (3D MRI) data. Accordingly, diverse phase combinations, feature-ranking approaches, and hybrid classifiers are integrated. Feature analyses are performed to achieve remarkable performance using first-order statistics (FOS) by examining different phase combinations near the usage of single phases (T1c, FLAIR, T1, and T2) and by considering five feature-ranking approaches (Bhattacharyya, Entropy, Roc, t test, and Wilcoxon) to detect the appropriate input to the classifier. Hybrid classifiers based on neural networks (NN) are considered due to their robustness and superiority with medical pattern classification. In this study, state-of-the-art optimisation methods are used to form the hybrid classifiers: dynamic weight particle swarm optimisation (DW-PSO), chaotic dynamic weight particle swarm optimisation (CDW-PSO), and Gauss-map-based chaotic particle-swarm optimisation (GM-CPSO). The integrated frameworks, including DW-PSO-NN, CDW-PSO-NN, and GM-CPSO-NN, are evaluated on the BraTS 2017 challenge dataset involving 210 HGG and 75 LGG samples. The 2-fold cross-validation test method and seven metrics (accuracy, AUC, sensitivity, specificity, g-mean, precision, f-measure) are processed to evaluate the performance of frameworks efficiently. In experiments, the most effective framework is provided that uses FOS, data including three phase combinations, the Wilcoxon feature-ranking approach, and the GM-CPSO-NN method. Consequently, our framework achieved remarkable scores of 90.18% (accuracy), 85.62% (AUC), 95.24% (sensitivity), 76% (specificity), 85.08% (g-mean), 91.74% (precision), and 93.46% (f-measure) for HGG/LGG discrimination of 3D brain MRI data. Graphical abstract.

An extensive study for binary characterisation of adrenal tumours.

On adrenal glands, benign tumours generally change the hormone equilibrium, and malign tumours usually tend to spread to the nearby tissues and to the organs of the immune system. These features can give a trace about the type of adrenal tumours; however, they cannot be observed all the time. Different tumour types can be confused in terms of having a similar shape, size and intensity features on scans. To support the evaluation process, biopsy process is applied that includes injury and complication risks. In this study, we handle the binary characterisation of adrenal tumours by using dynamic computed tomography images. Concerning this, the usage of one more imaging modalities and biopsy process is wanted to be excluded. The used dataset consists of 8 subtypes of adrenal tumours, and it seemed as the worst-case scenario in which all handicaps are available against tumour classification. Histogram, grey level co-occurrence matrix and wavelet-based features are investigated to reveal the most effective one on the identification of adrenal tumours. Binary classification is proposed utilising four-promising algorithms that have proven oneself on the task of binary-medical pattern classification. For this purpose, optimised neural networks are examined using six dataset inspired by the aforementioned features, and an efficient framework is offered before the use of a biopsy. Accuracy, sensitivity, specificity, and AUC are used to evaluate the performance of classifiers. Consequently, malign/benign characterisation is performed by proposed framework, with success rates of 80.7%, 75%, 82.22% and 78.61% for the metrics, respectively. Graphical abstract.

A novel pipeline for adrenal tumour segmentation.

BACKGROUND AND OBJECTIVE: Adrenal tumours occur on adrenal glands surrounded by organs and osteoid. These tumours can be categorized as either functional, non-functional, malign, or benign. Depending on their appearance in the abdomen, adrenal tumours can arise from one adrenal gland (unilateral) or from both adrenal glands (bilateral) and can connect with other organs, including the liver, spleen, pancreas, etc. This connection phenomenon constitutes the most important handicap against adrenal tumour segmentation. Size change, variety of shape, diverse location, and low contrast (similar grey values between the various tissues) are other disadvantages compounding segmentation difficulty. Few studies have considered adrenal tumour segmentation, and no significant improvement has been achieved for unilateral, bilateral, adherent, or noncohesive tumour segmentation. There is also no recognised segmentation pipeline or method for adrenal tumours including different shape, size, or location information. METHODS: This study proposes an adrenal tumour segmentation (ATUS) pipeline designed to eliminate the above disadvantages for adrenal tumour segmentation. ATUS incorporates a number of image methods, including contrast limited adaptive histogram equalization, split and merge based on quadtree decomposition, mean shift segmentation, large grey level eliminator, and region growing. RESULTS: Performance assessment of ATUS was realised on 32 arterial and portal phase computed tomography images using six metrics: dice, jaccard, sensitivity, specificity, accuracy, and structural similarity index. ATUS achieved remarkable segmentation performance, and was not affected by the discussed handicaps, on particularly adherence to other organs, with success rates of 83.06%, 71.44%, 86.44%, 99.66%, 99.43%, and 98.51% for the metrics, respectively, for images including sufficient contrast uptake. CONCLUSIONS: The proposed ATUS system realises detailed adrenal tumour segmentation, and avoids known disadvantages preventing accurate segmentation.

Elimination of white Gaussian noise in arterial phase CT images to bring adrenal tumours into the forefront.

Dynamic Contrast-Enhanced Computed Tomography (DCE-CT) is applied to observe adrenal tumours in detail by utilising from the contrast matter, which generally brings the tumour into the forefront. However, DCE-CT images are generally influenced by noises that occur as the result of the trade-off between radiation doses vs. noise. Herein, this situation constitutes a challenge in the achievement of accurate tumour segmentation. In CT images, most of the noises are similar to Gaussian Noise. In this study, arterial phase CT images containing adrenal tumours are utilised, and elimination of Gaussian Noise is realised by fourteen different techniques reported in literature for the achievement of the best denoising process. In this study, the Block Matching and 3D Filtering (BM3D) algorithm typically achieve reliable Peak Signal-to-Noise Ratios (PSNR) and resolves challenges of similar techniques when addressing different levels of noise. Furthermore, BM3D obtains the best mean PSNR values among the first five techniques. BM3D outperforms to other techniques by obtaining better Total Statistical Success (TSS), CPU time and computation cost. Consequently, it prepares clearer arterial phase CT images for the next step (segmentation of adrenal tumours).

An Efficient Pipeline for Abdomen Segmentation in CT Images.

Computed tomography (CT) scans usually include some disadvantages due to the nature of the imaging procedure, and these handicaps prevent accurate abdomen segmentation. Discontinuous abdomen edges, bed section of CT, patient information, closeness between the edges of the abdomen and CT, poor contrast, and a narrow histogram can be regarded as the most important handicaps that occur in abdominal CT scans. Currently, one or more handicaps can arise and prevent technicians obtaining abdomen images through simple segmentation techniques. In other words, CT scans can include the bed section of CT, a patient's diagnostic information, low-quality abdomen edges, low-level contrast, and narrow histogram, all in one scan. These phenomena constitute a challenge, and an efficient pipeline that is unaffected by handicaps is required. In addition, analysis such as segmentation, feature selection, and classification has meaning for a real-time diagnosis system in cases where the abdomen section is directly used with a specific size. A statistical pipeline is designed in this study that is unaffected by the handicaps mentioned above. Intensity-based approaches, morphological processes, and histogram-based procedures are utilized to design an efficient structure. Performance evaluation is realized in experiments on 58 CT images (16 training, 16 test, and 26 validation) that include the abdomen and one or more disadvantage(s). The first part of the data (16 training images) is used to detect the pipeline's optimum parameters, while the second and third parts are utilized to evaluate and to confirm the segmentation performance. The segmentation results are presented as the means of six performance metrics. Thus, the proposed method achieves remarkable average rates for training/test/validation of 98.95/99.36/99.57% (jaccard), 99.47/99.67/99.79% (dice), 100/99.91/99.91% (sensitivity), 98.47/99.23/99.85% (specificity), 99.38/99.63/99.87% (classification accuracy), and 98.98/99.45/99.66% (precision). In summary, a statistical pipeline performing the task of abdomen segmentation is achieved that is not affected by the disadvantages, and the most detailed abdomen segmentation study is performed for the use before organ and tumor segmentation, feature extraction, and classification.

Premarital screening of 466 Mediterranean women for serum ferritin, vitamin B12, and folate concentrations.

BACKGROUND/AIM: Iron, folate, and vitamin B12 serum levels are closely related with dietary habits and have an essential role in the healthy development of a fetus. We aimed to investigate hemoglobin, ferritin, folate, and vitamin B12 levels in preconceptional women in an area where a plant-based diet referred to as Mediterranean cuisine is commonly used. MATERIALS AND METHODS: The study population included 466 women between the ages of 18 and 45 years admitted for thalassemia screening. Sociodemographic variables and history of menometrorrhagia, pica, and dietary habits were collected. Serum vitamin B12, folate, ferritin, and hemoglobin levels were measured. Ferritin of <12µg/L, vitamin B12 of <200 pg/mL, and folate of <4 ng/mL were accepted as deficiencies. Hemoglobin level of <12 g/dL was classified as anemia. RESULTS: Polymenorrhea was present in 11.7% and hypermenorrhea in 24.8% of women. Anemia was detected in 24.9% and thalassemia trait in 3.0% of women. Low ferritin levels were observed in 46.1%, vitamin B12 in 21.6%, and folate in 3.4% of women. In the group with low vitamin B12, decreased meat consumption was more prevalent (27.5% vs. 16.9%; P = 0.019). CONCLUSION: Vitamin B12 and iron are the main micronutrients depleted in our community. This necessitates implementing a public health program for women consuming a Mediterranean diet.

Evaluation of retinal nerve fiber layer thickness in a patient with bilateral optic disc drusen

Optic disc drusen (ODD) is the accumulations of calcified hyaline-like material within the substance of the optic nerve head. Optic disc drusen, especially if it is bilateral, may mimic the clinical presentation of papilledema. Usually retinal nerve fiber layer (RNFL) thinning can be present in ODD. In this report we present uncommon RNFL changes in a patient with bilateral ODD. A 17-year-old male was referred by another center with a diagnosis of optic disc edema. The patient’s visual acuity, the slit-lamp examination and the intraocular pressures were normal in both eyes. On fundus examination, there were irregularly elevated discs bilaterally and the optic nerves appear with hazy disk margins. He did not have visual field defects in automated perimetry. Bilateral ODD were identified and confirmed by B-scan ultrasonography and optical coherence tomography (OCT) demonstrated 4 clock hours of RNFL thickening. Optic disc drusen may be misdiagnosed as papilledema. Thus, clinical suspicion of ODD is important in order to diagnose papilledema and prevents unnecessary interventions. Although most of eyes with ODD have normal or thinner RNFL thickness, some of these eyes can have thicker RNFL thickness.

As drusas do disco óptico (DDO) são depósitos de material hialino calcificado dentro da substância da cabeça do nervo óptico. Drusas do disco óptico, especialmente se for bilateral, podem apresentar o quadro clínico de edema de papila. Usualmente o espessamento da camada de fibras nervosas da retina (RCFN) podem estar presentes em DDO. Neste relato apresentamos o caso de um homem com 17 anos de idade que foi encaminhado por um outro centro, com o diagnóstico de edema do disco óptico. A acuidade visual do paciente, o exame de lâmpada de fenda e a pressão intraocular foram normais em ambos os olhos. No exame de fundo de olho havia discos elevados de forma irregular bilateralmente e os nervos ópticos com margens de disco nebulosas. Ele não tinha defeitos do campo visual em perimetria computadorizada. Drusas do disco óptico (DDO) bilateral foram identificados e confirmados pela ultrassonografia Bscan e tomografia de coerência óptica (TCO) que demonstraram 4 horas de relógio de RCFN com espessamento. As drusas do disco óptico podem ser diagnosticadas como papiledema. Assim, a suspeita clínica de DDO é importante a fim de evitar intervenções desnecessárias. Embora a maioria dos olhos com DDO têm espessura normal ou thinner RCFN, alguns desses olhos podem ter camada mais grossa na RCFN.

First observation of Hb Tunis [beta124(H2)Pro>Ser] in Turkey.

Hb Tunis [beta124(H2)Pro>Ser] was reported from Tunisia in 1988. This hemoglobin variant was detected by isoelectric focusing moving just ahead of Hb A. It cannot be identified by standard hemoglobin electrophoresis due to its similar mobility to Hb A. It has normal stability and oxygen affinity and does not produce any clinical symptoms. Here, we report a heterozygous Hb Tunis [beta124(H2)Pro>Ser] case discovered for the first time in Turkey in a premarital screening program. This hemoglobin variant can be identified with high performance liquid chromatography analysis confirmed with DNA sequencing. We emphasize in our study the importance of an interdisciplinary collaborative study at the provincial basis for the success of the hemoglobinopathy control program.

Addition of N-heterocyclic carbenes to imines: phenoxide assisted deprotonation of an imidazolium moiety and generation of breslow intermediates derived from imines.

Reactions between imidazolium-imine salts and base result in C-C bond formation via intermediate N-heterocyclic carbenes. In the presence of a proximal OH moiety, carbene formation occurs via intramolecular deprotonation by phenoxide. For simple imines, a reactive Breslow-type intermediate gives access to new heterocycles with the formation of six- and seven-member rings.

Hb D-Los Angeles [beta121(GH4)Glu>Gln] and Hb Beograd [beta121(GH4)Glu>Val]: Implications for their laboratory diagnosis and genetic origins.

OBJECTIVE: The aim of this study was to determine the laboratory diagnosis and genetic origins of the hemoglobin (Hb) variants, Hb D-Los Angeles and Hb Beograd observed frequently in our region. MATERIAL AND METHODS: Hb variants were investigated in one Hb D-Los Angeles and two Hb Beograd families. These families were unrelated with each other. For the determination of Hb variants, alkaline/acid electrophoresis, HPLC, DE-52 micro-column chromatography procedures were applied. Mutations were determined by non-radioactive fluorescence automated DNA sequencing. Beta globin gene cluster haplotypes were identified by RFLP analysis at seven loci known as ε-Hinc II, Gγ-Hind III, AΨß-Hind III, 5'Ψß-Hinc II, 3'Ψß-Hinc II, ß-Ava II ve 3'ß-Hinf I. RESULTS: Three novel beta globin gene cluster haplotypes were identified as in relation with Hb D-Los Angeles [--+-+++], Hb Beograd [+----++ and -+-(+/-)(+/-)+(+/-)]. These haplotypes were reported for the first time in the world population Conclusion: In this study we emphasize the importance of DNA seqeuncing and other laboratory procedures for the identification of Hb variants in premarital diagnosis. On the other hand we discuss also the genetic origins of these Hb variants.

Rare hemoglobin variant Hb Yaizu observed in Turkey.

OBJECTIVE: To determine the characteristic features of the rare hemoglobin (Hb) variant Hb Yaizu to enable laboratory diagnosis of the hemoglobin variants during screening programs. MATERIALS AND METHODS: Genomic DNA was obtained from the 4 members of a family living in Denizli province, an Aegean region of Turkey. Blood cell counts, hemoglobin composition, hemoglobin electrophoresis (both alkaline and acid), HPLC analysis, DNA sequencing and beta globin gene cluster haplotypes were done. RESULTS: Hb Yaizu carriers were apparently healthy individuals. Hb Yaizu was slightly faster than Hb S at alkaline pH, but slower than Hb S at acidic pH in hemoglobin electrophoresis. An abnormal hemoglobin peak was observed with a retention time of 4.77 min in HPLC analysis attributed to Hb Yaizu. Two members of the family were heterozygous Hb Yaizu [beta 79(EF3) Asp>Asn] confirmed by DNA sequencing. The mutation was found to be linked with the Mediterranean haplotype I [+----++]. CONCLUSION: We have presented the details of Hb Yaizu, a rare hemoglobin variant that may be important to hemoglobinopathy screening programs, although its clinical significance is unclear.

First observation of Hb D-Ouled Rabah [beta19(B1)Asn>Lys] in the Turkish population.

Hb D-Ouled Rabah [beta19(B1)Asn>Lys] is a rare hemoglobin (Hb) beta chain variant reported from Tuareg tribes in Algeria and once from China. It was suggested that Hb D-Ouled Rabah might be specific of Berber-speaking populations. Our report describes the first observation of this hemoglobin variant in the Turkish population.

Hb Beograd [beta121(GH4)Glu-->Val, GAA-->GTA] in the Turkish population.

Hb Beograd [beta121(GH4)Glu-->Val, GAA-->GTA] is a rare variant first reported in Yugoslavia and then in Turkey, Australia and New Zealand. We report two further unrelated cases from Turkey. The importance of identifying Hb Beograd at the molecular level, especially in regions where Hb D-Los Angeles [beta121(GH4)Glu-->Gln, GAA-->CAA] is prevalent, is emphasized.

Fam-Ti catalyzed enantioselective alkynylation of aldehydes.

Ferrocenyl-substituted aziridinylmethanol (Fam-1) has been used as a chiral catalyst with titanium for enantioselective alkynylation of aromatic, heteroaromatic, aliphatic, and alpha,beta-unsaturated aldehydes to give the corresponding propargylic alcohols in up to 96% yield and 96% ee. The ligand can be prepared easily and recycled.

Beta globin gene cluster haplotypes of abnormal hemoglobins observed in Turkey.

Since the first observation of hemoglobin S (Hb S) in Turkey by Aksoy, the number of hemoglobin variants reported was increased. Beta globin gene cluster haplotypes are being used to determine the origin of the mutations under interest. We studied the beta globin gene cluster haplotypes for the six different abnormal hemoglobins which are Hb S, Hb D-Los Angeles, Hb G-Coushatta, Hb E, Hb E-Saskatoon and Hb J-Iran observed in Turkey. In this study, we report two novel haplotypes [- + + - - - +] and [- + - + + +] in association with the Hb G-Coushatta mutation. The haplotype for the Hb J-Iran is also reported as [- + - + + + +] for the first time in world populations from Turkey.

New zinc(II)-based catalyst for asymmetric azomethine ylide cycloaddition reactions.

[reaction: see text] A new chiral aziridino alcohol ligand for zinc(II)-catalyzed azomethine ylide cycloadditions is described. In the presence of this catalyst, N-arylidene glycine methyl esters react with a variety of dipolarophiles to give substituted pyrrolidines in very good to excellent chemical yields and up to 95% ee. The absolute sense of asymmetric induction appears to be dipolarophile-dependent.

Molecular identification of a rare hemoglobin variant, Hb J-Iran [beta77(EF1)His->Asp], in Denizli province of Turkey.

Hb J-Iran [beta77(EF1)His-Asp], a rare hemoglobin variant that does not present health problems, was reported for the first time in the Turkish population in 1986. Our case is the fourth case reported in Turkey and the first case from the Denizli province.

High incidence of Hb D-Los Angeles [beta121(GH4)Glu-->Gln] in Denizli Province, Aegean region of Turkey.

Denizli Province is located in the inner part of the Aegean region of Turkey and is one of the target areas for premarital screening. Here we report the abnormal hemoglobins (Hbs) observed during a premarital screening program in our region. According to our results, Hb D-Los Angeles [beta1211(GH4)Glu-->Gln (GAA-->CAA] (also known as D-Punjab, D-North Carolina, D-Portugal, Oak Ridge and D-Chicago), is the most frequent abnormal Hb in this region.