Saccular Middle Cerebral Artery Aneurysms : State-of-the-Art Classification and Microsurgery

Background and objectives The middle cerebral artery (MCA) is the most frequent location of unruptured intracranial aneurysms (IAs). The rupture of IAs causes subarachnoid hemorrhaging (SAH) with high rates of morbidity and mortality. However, controversy remains regarding which unruptured MCA aneurysms should be prophylactically treated since treatment is not without risks. More insight when deciding upon the management of MCA aneurysms and less risky treatment options are still needed. Nevertheless, MCA aneurysms are typically classified according to their location in relation to the main MCA bifurcation despite the inconsistent and subjective nature of identifying this main branching point. This study aimed to objectively characterize the main MCA bifurcation as a key factor for the more accurate classification of MCA aneurysms (publication I), to statistically identify the topographical and morphological characteristics of MCA aneurysms which could predict an increased risk of rupture (publication II) and to technically minimize the invasiveness of the microsurgical treatment of MCA aneurysms (publication III). Methods Computerized tomography angiography (CTA) data from 1,009 consecutive patients with 1,309 MCA aneurysms constituted the basis of this study. The angiographic definition of the MCA main bifurcation (Mbif) as the starting point of the insular trunks (M2s) was the basis of its objective characterization (publication I). The morphological and topographical characteristics of MCA aneurysms were examined and compared to the aneurysm rupture status; then, univariate and multivariate logistic regression analysis were performed to determine the independent risk factors for rupture (publication II). Moreover, based on the surgical experience of Professor Juha Hernesniemi, we presented the basics principles and techniques for safely clipping MCA aneurysms through a 10 15-mm focused opening of the sylvian fissure (publication III). Results The 1,309 MCA aneurysms were classified after objectively determining the Mbif, which was the most common location for MCA aneurysms harboring 829 (63%) aneurysms. The 406 proximal middle cerebral artery (M1) aneurysms comprised 242 (60%) aneurysms at the origin of the early cortical branches (M1 ECBAs) and 164 (40%) aneurysms at the origin of the lenticulostriate arteries (M1 LSAAs). There were only 74 (6%) aneurysms distal to the Mbif. At the time of presentation, more than two-thirds of the MCA aneurysms (69%) were unruptured and 31% were ruptured. Most unruptured MCA aneurysms had a size less than 7 mm (78%), a smooth wall (80%), a height width ratio = 1 (47%) and were located at the main bifurcation (57%). Ruptured MCA aneurysms were primarily sized 7 14 mm (55%), had an irregular wall (78%), a height width ratio more than 1 (72%) and were located at the main bifurcation (77%). In addition, 38% of MCA bifurcation aneurysms, 74% of large aneurysms, 64% of aneurysms with an irregular wall and 49% of aneurysms with a height width ratio more than 1 were ruptured. In our experience, the focused sylvian opening technique for the microsurgical management of MCA aneurysms resulted in shorter operative times and less inadvertent brain and vessel manipulation. Thus, it proved to be safe and effective for the clipping of both ruptured and unruptured MCA aneurysms. Conclusions Image-based analysis of the angioarchitecture of MCA can objectively define the main MCA bifurcation and helps in classifying MCA aneurysms more accurately. The analysis of topographical and morphological characteristics of MCA aneurysms is important when deciding upon their management, where their location at the main MCA bifurcation, the wall irregularity and a less spherical geometry equate to an increased risk of rupture. Thus, the focused opening of the sylvian fissure is a practical, less invasive alternative to the classical wide sylvian opening for the microsurgical management of most MCA aneurysms.  Suomalaisessa väestössä aivovaltimopullistumat puhkeavat 2-3 kertaa herkemmin kuin muissa länsimaissa, vaikka esiintyvyydessä (2 % väestöstä) ei ole eroa. Suomessa on 1000 lukinkalvonalaista vuotoa vuosittain johtaen siihen liittyvän korkean mortaliteetin noin 500 yleensä työikäisen ihmisen menehtymiseen, mikä on kaksinkertainen määrä liikenneonnettomuuksissa menehtyneisiin nähden. Suomessa yli 40 % kaikista aivovaltimopullistumista sijaitsee keskimmäisessä aivovaltimossa (MCA) ja tyypillisesti sen päähaarautumiskohdassa. Toistaiseksi mikrokirurginen hoito on tehokkaampi hoito nimenomaan MCA-pullistumissa, koska suonensisäiseen eli endovaskulaariseen hoitoon liittyy huomattavan suuri pullistuman uudelleen täyttymisen ja uusiutumisen riski. Yksittäisen vuotamattoman pullistuman puhkeamisriskin arvioiminen on haastavaa ja täytyy suhteuttaa vuodolta ennaltaehkäisevän hoidon riskiin huomioiden potilaan ikä ja muut sairaudet. Potilaan tupakointi, kohonnut verenpaine ja naissukupuoli altistavat vuodolle, samoin pullistuman suurempi koko. Tässä väitöskirjatutkimuksessa on analysoitu vuosien 2000 ja 2009 välillä HYKS neurokirurgian klinikassa diagnosoitujen 1309 MCA-pullistumien tietokonetomografia-angiografioista (TTA) tarkemmin niiden sijainti päähaarautumiskohtaan nähden. TTA on käytännössä syrjäyttämässä diagnostiikassa perinteisen angiografian sen nopeuden, turvallisuuden sekä helpomman saatavuuden vuoksi. 1009 peräkkäin hoidettujen potilaiden TTA:n pohjalta on tehty uusi tarkempi anatominen luokitus, missä proksimaaliset MCA:n päärungon (M1) pullistumat jaettiin erikseen kahteen luokkaan, päähaarautumiskohdan ja sitä distaalisempien haarojen sijaintien lisäksi eli luokkia on aiemman kolmen sijasta neljä (osatyö I). 63 % pullistumista sijaitsi päähaarautumiskohdassa ja diagnoosihetkellä kaikista MCA-pullistumista oli 69 % vuotamattomia. Näistä suurin osa (78 %) oli alle 7 mm läpimittaisia, sileäseinäisiä (80 %), pituus-leveyssuhde oli yksi (47 %) ja sijaitsivat päähaarautumiskohdassa (57 %). Vuotaneet sen sijaan olivat suurempia 7-14 mm läpimittaisia (55 %), seinämä oli epäsäännöllinen (78 %) ja pituus-leveyssuhde oli yli yhden (72 %) ja ne sijaitsivat vielä useammin päähaarautumiskohdassa (77 %). Kaikkiaan 38 % päähaarautumiskohdan, 74 % suurista ja 64 % epäsäännöllisen seinämän omaavista ja 49 % yli yhden pituus-leveyssuhteen omaavista pullistumista oli vuotaneita (osatyö II). Nämä vuodolle altistavat seikat auttavat hoitopäätösten tekemisessä harkittaessa vuotamattoman MCA-pullistuman ennaltaehkäisevää mikrokirurgista hoitoa. Pullistumien tarkempi anatominen luokittelu helpottaa mikrokirurgisen hoidon suunnittelua ja toteuttamista mahdollisimman turvallisesti ja tehokkaasti. Tämä johtaa lyhempiin leikkausaikoihin, kun pullistumia voidaan lähestyä mahdollisimman tarkasti ja avaamalla vain vähän (10-15mm) otsa- ja ohimolohkoa erottavaa kalvoa suoraan oikeasta kohdasta ja tämä vähentää mahdollista aivokudosvaurion riskiä (osatyö III). TTA-kuvien huolellinen tarkastelu ennen leikkausta ja mahdollisten anatomisten poikkeavuuksien tunnistaminen ovat ensiarvoisen tärkeitä. Moderni neuroanestesia, potilaan pään oikea asento leikkauksen aikana sekä anatomian kolmiulotteinen hahmottaminen, ja leikkauksen aikaisen angiografian (nk ICG eli indocyaniini vihreä) mahdollistavan leikkausmikroskoopin suuri suurennos leikatessa ovat lisäksi keskeisessä asemassa onnistuneessa aivovaltimopullistumien mikrokirurgisessa hoidossa

Tel Aviv Mizrah: The potential of Iraqi cultural identity within two generations

Before immigrating to Israel, first-generation Iraqi Jews were deeply attached to their identity as Mizrahi Jews. Their mother tongue was Arabic and they had grown up in an oriental environment. Therefore, it was not easy for them to adopt the Euro-Israeli identity that the dominant Ashkenazi-European stratum in Israel compelled them to accept. Despite strong Westernizing tendencies in Israeli society, the first generation of Iraqi Jewish immigrants maintained strong links to the Iraqi customs and traditions they had acquired in Iraq, particularly with regard to the musical folklore and oriental cuisine. On the other hand, second-generation Iraqi Jews were more familiar with Israeli society than their parents; they grew up in Israel and learned Hebrew in Israeli schools along with Ashkenazi Jews and other ethnic groups. This paper establishes connections between the historical realities of Iraqi Jewish immigrants and the literary representation of their world in the trilogy Tel-Aviv Mizrah (Tel Aviv East) written in 2003 by the Iraqi Jewish author Shimon Ballas, through a comparison of Ballas's literary vision with the historical realities of Iraqi Jewish identity in Israel over the course of two generations

The Role of 3D CT Imaging in the Accurate Diagnosis of Lung Function in Coronavirus Patients

Early grading of coronavirus disease 2019 (COVID-19), as well as ventilator support machines, are prime ways to help the world fight this virus and reduce the mortality rate. To reduce the burden on physicians, we developed an automatic Computer-Aided Diagnostic (CAD) system to grade COVID-19 from Computed Tomography (CT) images. This system segments the lung region from chest CT scans using an unsupervised approach based on an appearance model, followed by 3D rotation invariant Markov–Gibbs Random Field (MGRF)-based morphological constraints. This system analyzes the segmented lung and generates precise, analytical imaging markers by estimating the MGRF-based analytical potentials. Three Gibbs energy markers were extracted from each CT scan by tuning the MGRF parameters on each lesion separately. The latter were healthy/mild, moderate, and severe lesions. To represent these markers more reliably, a Cumulative Distribution Function (CDF) was generated, then statistical markers were extracted from it, namely, 10th through 90th CDF percentiles with 10% increments. Subsequently, the three extracted markers were combined together and fed into a backpropagation neural network to make the diagnosis. The developed system was assessed on 76 COVID-19-infected patients using two metrics, namely, accuracy and Kappa. In this paper, the proposed system was trained and tested by three approaches. In the first approach, the MGRF model was trained and tested on the lungs. This approach achieved 95.83% accuracy and 93.39% kappa. In the second approach, we trained the MGRF model on the lesions and tested it on the lungs. This approach achieved 91.67% accuracy and 86.67% kappa. Finally, we trained and tested the MGRF model on lesions. It achieved 100% accuracy and 100% kappa. The results reported in this paper show the ability of the developed system to accurately grade COVID-19 lesions compared to other machine learning classifiers, such as k-Nearest Neighbor (KNN), decision tree, naïve Bayes, and random forest

Early assessment of lung function in coronavirus patients using invariant markers from chest X-rays images

The primary goal of this manuscript is to develop a computer assisted diagnostic (CAD) system to assess pulmonary function and risk of mortality in patients with coronavirus disease 2019 (COVID-19). The CAD system processes chest X-ray data and provides accurate, objective imaging markers to assist in the determination of patients with a higher risk of death and thus are more likely to require mechanical ventilation and/or more intensive clinical care.To obtain an accurate stochastic model that has the ability to detect the severity of lung infection, we develop a second-order Markov-Gibbs random field (MGRF) invariant under rigid transformation (translation or rotation of the image) as well as scale (i.e., pixel size). The parameters of the MGRF model are learned automatically, given a training set of X-ray images with affected lung regions labeled. An X-ray input to the system undergoes pre-processing to correct for non-uniformity of illumination and to delimit the boundary of the lung, using either a fully-automated segmentation routine or manual delineation provided by the radiologist, prior to the diagnosis. The steps of the proposed methodology are: (i) estimate the Gibbs energy at several different radii to describe the inhomogeneity in lung infection; (ii) compute the cumulative distribution function (CDF) as a new representation to describe the local inhomogeneity in the infected region of lung; and (iii) input the CDFs to a new neural network-based fusion system to determine whether the severity of lung infection is low or high. This approach is tested on 200 clinical X-rays from 200 COVID-19 positive patients, 100 of whom died and 100 who recovered using multiple training/testing processes including leave-one-subject-out (LOSO), tenfold, fourfold, and twofold cross-validation tests. The Gibbs energy for lung pathology was estimated at three concentric rings of increasing radii. The accuracy and Dice similarity coefficient (DSC) of the system steadily improved as the radius increased. The overall CAD system combined the estimated Gibbs energy information from all radii and achieved a sensitivity, specificity, accuracy, and DSC of 100%, 97% ± 3%, 98% ± 2%, and 98% ± 2%, respectively, by twofold cross validation. Alternative classification algorithms, including support vector machine, random forest, naive Bayes classifier, K-nearest neighbors, and decision trees all produced inferior results compared to the proposed neural network used in this CAD system. The experiments demonstrate the feasibility of the proposed system as a novel tool to objectively assess disease severity and predict mortality in COVID-19 patients. The proposed tool can assist physicians to determine which patients might require more intensive clinical care, such a mechanical respiratory support

Solar Thermal Collector Education Using Polysun Simulations Software

There are a variety of solar thermal collectors available in the market today. These collectors are typically manufactured in diverse countries and have different performance characteristics. For homeowners and commercial solar solution providers, it is important to know how these collectors will perform to ensure maximum return on investment. Therefore, engineers and technicians need to be trained into how different collectors will perform in different locations. In this article, we demonstrate how a Swiss simulations software package called Polysun can be used to accurately determine the performance of a particular system under real operating conditions. To demonstrate the accuracy of the simulations tool, we show performance comparisons with experimental results for different types of flat plate and evacuated tube solar collectors. We also show examples of exercises that can be implemented in an undergraduate course in solar thermal systems. According to our investigations, the thermal performance predicted by Polysun was in close agreement with our experimental measurements. The outcomes of our investigations can help educators make informed decisions regarding teaching solar thermal systems to undergraduates using state-of-the art simulation and visualization tools