Browsing by Subject "Hydrocephalus"

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Open Access
Choroid Plexus Papillomas in two siblings: Case report
(2009) Okay, O.; Dağlıoğlu, E.; Yakıcıer, Cengiz; Üren, Deniz; Dalgıç, A.; Ergüngör, F.
Choroid plexus papilloma (CPP) is a rare, benign epithelial brain tumor of the nervous system seen particularly in infants. Familial cases are extremely uncommon. Some other form of malignant tumors was noted in the relatives of patients with CPPs, and some genetic defects regarding this coincidence were reported in the literature. These neoplasms are occasionally bilateral and hydrocephalus is an associated sign in most of the cases. We report three lateral ventricle CPPs in two siblings, at the age of 7 month and 2 years respectively. All tumors were resected with parietotemporal craniotomy and a superior temporal sulcus approach to the lateral ventricle. To avoid a concomitant need of ventriculoperitoneal shunt insertion, external ventricular drainage was inserted for a week in the postoperative period relieving symptoms of hydrocephalus. Search for a hereditary defect in the p53 gene of the second infant (7 months old) revealed no mutation. Postoperative courses were uneventful and the patients were followed for three years without any recurrence. Bilateral CPPS are rare and unusual in two siblings. A genetic predisposition such as the p53 mutation should be investigated in bilateral CPPs in particular.
Open Access
Comparison of morphometric parameters in prediction of hydrocephalus using random forests
(Elsevier, 2020-01-01) Özgöde-Yigin, B.; Algın, Oktay; Saygılı, G.
Ventricles of the human brain enlarge with aging, neurodegenerative diseases, intrinsic, and extrinsic pathologies. The morphometric examination of neuroimages is an effective approach to assess structural changes occurring due to diseases such as hydrocephalus. In this study, we explored the effectiveness of commonly used morphological parameters in hydrocephalus diagnosis. For this purpose, the effect of six common morphometric parameters; Frontal Horns' Length (FHL), Maximum Lateral Length (MLL), Biparietal Diameter (BPD), Evans' Ratio (ER), Cella Media Ratio (CMR), and Frontal Horns’ Ratio (FHR) were compared in terms of their importance in predicting hydrocephalus using a Random Forest classifier. The experimental results demonstrated that hydrocephalus can be detected with 91.46 % accuracy using all of these measurements. The accuracy of classification using only CMR and FHL reached up to 93.33 %. In terms of individual performances, CMR and FHL were the top performers whereas BPD and FHR did not contribute as much to the overall accuracy.
Open Access
Evaluation of hydrocephalus patients with 3D-SPACE technique using variant FA mode at 3T
(Springer, 2018) Algin, O.
The major advantages of three-dimensional sampling perfection with application optimized contrasts using different flip-angle evolution (3D-SPACE) technique are its high resistance to artifacts that occurs as a result of radiofrequency or static field, the ability of providing images with sub-millimeter voxel size which allows obtaining reformatted images in any plane due to isotropic three-dimensional data with lower specific absorption rate values. That is crucial during examination of cerebrospinal-fluid containing complex structures, and the acquisition time, which is approximately 5 min for scanning of entire cranium. Recent data revealed that T2-weighted (T2W) 3D-SPACE with variant flip-angle mode (VFAM) imaging allows fast and accurate evaluation of the hydrocephalus patients during both pre- and post-operative period for monitoring the treatment. For a better assessment of these patients; radiologists and neurosurgeons should be aware of the details and implications regarding to the 3D-SPACE technique, and they should follow the updates in this field. There could be a misconception about the difference between T2W-VFAM and routine heavily T2W 3D-SPACE images. T2W 3D-SPACE with VFAM imaging is only a subtype of 3D-SPACE technique. In this review, we described the details of T2W 3D-SPACE with VFAM imaging and comprehensively reviewed its recent applications.
Open Access
Exploiting lamina terminalis appearance and motion in prediction of hydrocephalus using convolutional LSTM network
(Elsevier Masson s.r.l., 2022-08-24) Saygılı, Görkem; Özgöde Yigin, Büşra; Güney, Gökhan; Algın, Oktay
Background Evaluation of the lamina terminalis (LT) is crucial for non-invasive evaluation of the CSF diversion for the treatment of hydrocephalus. Together with deep learning algorithms, morphological and physiological analyses of the LT may play an important role in the management of hydrocephalus. Aim We aim to show that exploiting the motion of LT can contribute to the evaluation of hydrocephalus using deep learning algorithms. Methods The dataset contains 61 True-fisp data with routine sequences 37 of which are labeled as ‘hydrocephalus’ and the others as ‘normal condition’. A fifteen-year experienced neuroradiologist divided data into two groups. The first group, ‘hydrocephalus’, consists of patients with typical MRI findings (ventriculomegaly, enlargement of the third ventricular recesses and lateral ventricular horns, decreased mamillo-pontine distance, reduced frontal horn angle, thinning/elevation of the corpus callosum, and non-dilated convexity sulci), and the second group contains samples that did not show any symptoms or neurologic abnormality and labeled as ‘normal condition’. The region of interest was determined by the radiologist supervisor to cover the LT. To achieve our purpose, we used both spatial and spatio-temporal analysis with two different deep learning architectures. We utilized Convolutional Neural Networks (CNN) for spatial and Convolutional Long Short-Term Memory (ConvLSTM) models for spatio-temporal analysis using an ROI around LT on sagittal True-fisp images. Results Our results show that 80.7% classification accuracy was achieved with the ConvLSTM model exploiting LT motion, whereas 76.5% and 71.6% accuracies were obtained by the 2D CNN model using all frames, and only the first frame from only spatial information, respectively. Conclusion We suggest that the motion of the LT can be used as an additional attribute to the spatial information to evaluate the hydrocephalus.
Open Access
Feasibility of 3-dimensional sampling perfection with application optimized contrast sequence in the evaluation of patients with hydrocephalus
(Lippincott Williams and Wilkins, 2015) Kartal, M. G.; Ocakoglu, G.; Algın, Oktay
Purpose This study aimed to investigate the effectiveness and additive value of T2W 3-dimensional sampling perfection with application optimized contrast (3D-SPACE) with variant flip-angle mode in imaging of all types of hydrocephalus. Our secondary objective was to assess the reliability of 3D-SPACE sequence and correspondence of the results with phase-contrast magnetic resonance imaging (PC-MRI)-based data. Materials and Methods Forty-one patients with hydrocephalus have undergone 3-T MRI. T2W 3D-SPACE sequence has been obtained in addition to routine hydrocephalus protocol. Cerebrospinal fluid circulation, presence/type/etiology of hydrocephalus, obstruction level scores, and diagnostic levels of confidence were evaluated separately by 2 radiologists. In the first session, routine sequences with PC-MRI were evaluated, and in another session, only 3D-SPACE and 3-dimensional magnetization prepared rapid acquisition gradient echo sequences were evaluated. Results obtained in these sessions were compared with each other and those obtained in consensus session. Results Agreement values were very good for both 3D-SPACE and PC-MRI sequences (P < 0.001 for all). Also, the correlation of more experienced reader's 3D-SPACE-based scores and consensus-based scores was perfect (κ = 1, P < 0.001).The mean value of PC-MRI-based confidence scores were lower than those obtained in 3D-SPACE and consensus sessions. Conclusions T2W 3D-SPACE sequence provides morphologic cerebrospinal fluid flow data. It is a noninvasive technique providing extensive multiplanar reformatted images with a lower specific absorption rate. These advantages over PC-MRI make 3D-SPACE sequence a promising tool in management of patients with hydrocephalus. © 2015 Wolters Kluwer Health, Inc.
Open Access
In Press, Corrected Proof: Exploiting lamina terminalis appearance and motion in prediction of hydrocephalus using convolutional LSTM network
(Elsevier, 2021-02-12) Saygılı, G.; Yigin, B. Ö.; Güney, G.; Algın, Oktay
Background Evaluation of the lamina terminalis (LT) is crucial for non-invasive evaluation of the CSF diversion for the treatment of hydrocephalus. Together with deep learning algorithms, morphological and physiological analyses of the LT may play an important role in the management of hydrocephalus. Aim We aim to show that exploiting the motion of LT can contribute to the evaluation of hydrocephalus using deep learning algorithms. Methods The dataset contains 61 True-fisp data with routine sequences 37 of which are labeled as ‘hydrocephalus’ and the others as ‘normal condition’. A fifteen-year experienced neuroradiologist divided data into two groups. The first group, ‘hydrocephalus’, consists of patients with typical MRI findings (ventriculomegaly, enlargement of the third ventricular recesses and lateral ventricular horns, decreased mamillo-pontine distance, reduced frontal horn angle, thinning/elevation of the corpus callosum, and non-dilated convexity sulci), and the second group contains samples that did not show any symptoms or neurologic abnormality and labeled as ‘normal condition’. The region of interest was determined by the radiologist supervisor to cover the LT. To achieve our purpose, we used both spatial and spatio-temporal analysis with two different deep learning architectures. We utilized Convolutional Neural Networks (CNN) for spatial and Convolutional Long Short-Term Memory (ConvLSTM) models for spatio-temporal analysis using an ROI around LT on sagittal True-fisp images. Results Our results show that 80.7% classification accuracy was achieved with the ConvLSTM model exploiting LT motion, whereas 76.5% and 71.6% accuracies were obtained by the 2D CNN model using all frames, and only the first frame from only spatial information, respectively. Conclusion We suggest that the motion of the LT can be used as an additional attribute to the spatial information to evaluate the hydrocephalus.