Clinical and epidemiologic studies of defined geographic populations can serve as a means of establishing data important for the diagnosis, treatment, and counseling of patients with cleft lip and cleft palate. Several descriptive epidemiologic studies have been carried out in many countries worldwide; however, no such study has ever been performed in Pakistan. Population-based data on the incidence of cleft lip and palate were obtained from birth registry information in northern Pakistan. A total of 117 cases from 61,156 live births reported were identified. The incidence for cleft lip and/or cleft palate was 1.91 per 1000 births (one per 523 births). Cleft lip alone (42 percent) was noted more frequently than isolated cleft palate (24 percent) and combined cleft lip and palate deformities (34 percent). Boys were more commonly affected by cleft lip and cleft lip with cleft palate, whereas girls predominated in the isolated cleft palate cases. Consanguineous marriages were observed in 32 percent of parents versus 18 percent in matched controls. Only 32 percent of cleft mothers received formal prenatal counseling, monthly examinations, and regular laboratory testing during the entirety of the pregnancy. Nutritional and vitamin supplements were given to only 28 percent of mothers of cleft children versus 59 percent in matched controls. Descriptive statistics were used to assess pertinent risk factors associated with cleft lip and palate. The acquisition of incidence and associated data has generated baseline information on the magnitude of cleft lip and cleft palate in Pakistan. It is hoped that this information can be used for appropriate resource use, cleft lip and cleft palate prevention programs, and counseling programs with Pakistan-specific data.

Introduction: Being the most common primary brain tumor, glioblastoma presents as an extremely challenging malignancy to treat with dismal outcomes despite treatment. Varying molecular epidemiology of glioblastoma between patients and intra-tumoral heterogeneity explains the failure of current one-size-ts-all treatment modalities. Radiomics uses machine-learning to identify salient features of the tumor on brain imaging and promises patient speci c management in glioblastoma patients.Methods: We performed a comprehensive review of the available literature on studies investigating the role of radiomics and radiogenomics models for the diagnosis, strati cation, prognostication as well as treatment planning and monitoring of glioblastoma.Results: Classi ers based on combination of various MRI sequences, genetic information and clinical data can predict non-invasive tumor diagnosis, overall survival and treatment response with reasonable accuracy. However, the use of radiomics for glioblastoma treatment remains in infancy as larger sample sizes, standardized image acquisition and data extraction techniques are needed to develop machine learning models that can be translated effectively into clinical practice.Conclusion: Radiomics has the potential to transform the scope of glioblastoma management through personalized medicine. Glioblastoma:Glioblastoma has an incidence of 3.22 per 100,000 and a median overall survival (OS) of 14.6 months following standard treatment, which includes a combination of surgical resection, radiation therapy and chemotherapy. [1] This "one-size-ts-all" model for the treatment of glioblastoma is now being questioned following research on various pathways implied in intratumoral heterogeneity, arising as a result of genetic and epigenetic makeup, levels of protein expression, metabolic or bioenergetic behavior, microenvironment biochemistry and structural composition.[2] Consequently, features differ on histopathology and imaging across patients as well as spatially throughout a single tumor. [3,4,5] Personalized treatment protocols targeting individual patient's tumor characteristics are thus being increasingly advocated for improved success rates in glioblastoma management. [4,6,7] Radiomics And Radiogenomics:Radiomics is an emerging application of neuroimaging where advanced computational methods are used to quantitatively extract characteristics from clinical images that are too complex for a human eye to appreciate.[8,9] These imaging characteristics, called "features" re ect tumor characteristics and inner organization as well as the tumor microenvironment. [9]Radiomics is a multi-step process including the acquisition and preprocessing of images, segmentation, feature extraction and selection, and advanced statistics using machine learning (ML) algorithms (Figure 1). The pipeline of radiomics is highly

ObjectiveThe objective of the study was to assess magnetic resonance (MR) planimetric measurements and MR parkinsonism index (MRPI) in differentiating progressive supranuclear palsy (PSP) from Parkinson’s disease (PD) using 1.5 and 3 T MRI scanner.Subjects and methodsAfter ethical approval was obtained, analysis of 34 consecutive patients with PSP, 34 patients with PD and 34 healthy controls (HCs) was performed. HCs were age-matched adults without any history of neurodegenerative disease or movement disorders. Retrospective data from the past 10 years (from January 2006 to December 2015) were obtained from the Hospital Information Management System, and informed consent was obtained from all participants. The measurements of pons area–midbrain area ratio (P/M) and MCP width–superior cerebellar peduncle (SCP) width ratio (MCP/SCP) were used, and MRPI was calculated by the formula ([P/M]×[MCP/SCP]).ResultsMidbrain area and SCP width in patients with PSP (19 males, 15 females; mean age =66.7 years) were significantly (P<0.001) smaller than in patients with PD (20 males, 14 females; mean age =66.7 years) and control participants (17 males, 17 females; mean age =66.1 years). P/M and MCP/SCP were significantly higher in patients with PSP than in patients with PD and control participants. All measurements showed some overlap of values between patients with PSP and patients from PD group and control participants. MRPI value was significantly higher in patients with PSP (mean 21.00) than in patients with PD (mean 9.50; P<0.001) and control participants (mean 9.6; P<0.001), without any overlap of values among groups. No correlation was found between the duration of disease, PSP rating scale, PSP staging system and MRPI in this study. No patient with PSP received a misdiagnosis when the index was used (sensitivity and specificity, 100%).ConclusionMRPI should be made an essential part of all MRI brain reporting whenever differentiation between PD and PSP is sought for.

Epidermoid cyst of the presacral space is a rare congenital lesion of ectodermal origin. Presacral epidermoid cysts have been previously reported in women, however are extremely rare in males. We report a case of presacral epidermoid cyst in a 55-year-old male who presented to our emergency department with acute urinary retention and history of chronic constipation. A non-contrast computed tomography scan was performed with suspicion of urolithiasis, which revealed a well circumscribed low attenuation presacral mass. Magnetic resonance imaging (MRI) of the pelvis was subsequently performed to further characterize the lesion. The mass was returning hypointense T1 and hyperintense T2 signals with few foci of T2 hypointensities. There was no post-contrast enhancement; however the lesion was showing diffusion restriction, appearing hyperintense on diffusion weighted imaging (DWI) and hypointense on the corresponding apparent diffusion coefficient map. These imaging features were consistent with an epidermoid cyst. Laparotomy with complete surgical excision of the cyst and preservation of the adjacent structures was performed. The histopathology confirmed the diagnosis. This case highlights the importance of MRI with additional sequences of diffusion weighted imaging which can be helpful to differentiate, to a good degree of confidence, among different pelvic tumors, therefore obviating the need of biopsy before surgery.

Glioblastoma is an aggressive primary central nervous system tumour that usually has a poor prognosis. Generally, the typical imaging features are easily recognisable, but the behaviour of glioblastoma multiforme (GBM) can often be unusual. Several variations and heterogeneity in GBM appearance have been known to occur. In this pictorial essay, we present cases of pathologically confirmed GBM that illustrate unusual locations and atypical features on neuroimaging, and review the relevant literature. Even innocuous-looking foci, cystic lesions, meningeal-based pathology, intraventricular and infra-tentorial masses, multifocal/multicentric lesions and spinal cord abnormalities may represent GBM. We aim to highlight the atypical characteristics of glioblastoma, clarify their importance and list the potential mimickers. Although a definitive diagnosis in these rare cases of GBM warrants histopathological confirmation, an overview of the many imaging aspects may help make an early diagnosis.

Alzheimer's disease (AD) is the most common form of dementia, accounting for 50-75% of all cases, with a greater proportion of individuals affected at older age range. A single moderate or severe traumatic brain injury (TBI) is associated with accelerated aging and increased risk for dementia. The fastest growth in the elderly population is taking place in China, Pakistan, and their south Asian neighbors. Current clinical assessments are based on data collected from Caucasian populations from wealthy backgrounds giving rise to a "diversity" crisis in brain research. Pakistan is a lower-middle income country (LMIC) with an estimated one million people living with dementia. Pakistan also has an amalgamation of risk factors that lead to brain injuries such as lack of road legislations, terrorism, political instability, and domestic and sexual violence. Here, we provide an initial and current assessment of the incidence and management of dementia and TBI in Pakistan. Our review demonstrates the lack of resources in terms of speciality trained clinician staff, medical equipment, research capabilities, educational endeavors, and general awareness in the fields of dementia and TBI. Pakistan also lacks state-of-the-art assessment of dementia and its risk factors, such as neuroimaging of brain injury and aging. We provide recommendations for improvement in this arena that include the recent creation of Pakistan Brain Injury Consortium (PBIC). This consortium will enhance international collaborative efforts leading to capacity building for innovative research, clinician and research training and developing databases to bring Pakistan into the international platform for dementia and TBI research.

Objective The effectiveness of Haemophilus influenzae type b (Hib) vaccine in preventing severe pneumonia in Asian children has been questioned, and many large Asian countries yet to introduce Hib conjugate vaccine in immunization programs. The primary objective of this study was to assess Hib conjugate vaccine effectiveness (VE) on radiologically-confirmed pneumonia in children born after introduction of Hib conjugate vaccine in Pakistan. Study design A matched case-control study enrolled cases of radiologically-confirmed pneumonia in several hospitals serving low-income populations during 2009–2011. Cases were matched by age and season with 3 hospital and 5 neighborhood controls. Pneumonia was diagnosed using standardized World Health Organization criteria for chest radiograph interpretation. Matched OR were estimated for VE. Results A total of 1027 children with radiologically-confirmed pneumonia were enrolled; 975 cases, 2925 hospital controls, and 4875 neighborhood controls were analyzed. The coverage for 3 doses of diphtheria-tetanus-pertussis-hepatitis B-Hib conjugate vaccine was 13.7%, 18%, and 22.7% in cases, hospital controls and neighborhood controls, respectively. Estimated Hib VE for radiologically-confirmed pneumonia was 62% with 3 doses of vaccine using hospital controls and 70% using neighborhood controls. Conclusions Hib conjugate vaccine prevented a significant fraction of radiologically-confirmed pneumonia in children in Pakistan. Maximizing impact on child survival needs improved immunization coverage.

Objective:To evaluate the diagnostic accuracy of multidetector 64-slice computed tomography (MDCT) in the diagnosis and differentiation of benign and malignant ovarian masses using histopathology and surgical findings as the gold standard.Material and methods:This study was conducted in Aga Khan University Hospital, Karachi, Pakistan. Data was reviewed retrospectively from 1 November 2008 to 12 December 2009. One hundred patients found to have ovarian masses on CT scan were included in the study. CT scan was performed in all these patients after administration of oral and IV contrast. Ovarian masses were classified as benign and malignant on scan findings. Imaging findings were compared with histopathologic results and surgical findings. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of MDCT were calculated.Results:MDCT was found to have 97% sensitivity, 91% specificity, and an accuracy of 96% in the differentiation of benign and malignant ovarian masses, while PPV and NPV were 97% and 91%, respectively.Conclusion:MDCT imaging offers a safe, accurate and noninvasive modality to differentiate between benign and malignant ovarian masses.