The objective of this report is to present a case of Graves’ thyrotoxicosis-induced cardiomyopathy. This is a case of a 26 year old woman that presented with severe symptomatic congestive heart failure and was subsequently diagnosed with dilated cardiomyopathy secondary to Graves’ disease. Despite an initial left ventricular systolic ejection fraction of 20% on echocardiography, treatment with anti-thyroid agents led to rapid improvement of her clinical status and normalization of her ejection fraction. The proposed mechanisms underlying the development of systolic dysfunction in thyrotoxicosis are discussed and the literature on similar cases previously reported is highlighted. Cardiomyopathy should be considered even in young patients with Graves’ thyrotoxicosis.

Background Allergic rhinitis (AR) is characterized by mucosal inflammation that leads to a variety of symptoms, such as nasal congestion, rhinorrhea, and sneezing. This rhinitis is triggered by inhalation of allergens, such as pollen, and this condition has a negative impact on the quality of life. AR was shown to be associated with a number of co‐morbidities, including hypothyroidism, asthma, and chronic sinusitis. Objective This study aimed to assess AR‐associated comorbidities in patients presenting symptoms and paranasal sinus computed tomography (CT) scan findings in Taif City, Saudi Arabia. Methods This cross‐sectional study evaluated medical and radiological records of AR patients retrospectively from the period of December 2018 to September 2019 in Al‐Hada Armed Forces Military Hospital, Taif City, Saudi Arabia. Results A total of 103 AR patients with a mean age of 39.0 ± 15.6 years with 55.3% males and 44.7% females. The three most common associated comorbidities in allergic rhinitis patients were chronic sinusitis (28.2%), hypothyroidism (21.4%), and asthma (8.7%). Nasal obstruction (30.1%) was the symptom most frequently presented by all patients. Mucosal thickening occurred most frequently in patients with associated chronic sinusitis, while bilateral osteomeatal complex obliteration was observed mostly in asthmatic patients, and bony boundary thinning was more prevalent among patients with associated hypothyroidism. Conclusion The gender distribution of AR was 10% more common among males; however, the most common three comorbidites in allergic rhinitis patients were chronic sinusitis, hypothyroidism, and asthma, and most of those patients were females. Hypothyroidism can be a hidden predisposing factor for AR, while chronic sinusitis can be caused by AR due to secretion stasis or immune system activation.

Lung cancer is one of the most profound causes of cancer‐related deaths in the world. Early detection is known to significantly improve the chances of survival. Several detection and diagnostic methods are used for this purpose. CT is one of the most widely used non‐invasive medical imaging modalities in this domain. The biggest challenge faced by radiologists in this case is detection and diagnosis of cancerous lung nodules. The growth of ground glass opacity (GGO) lesions is an indication of malignancy. However, GGO is difficult to capture for physicians as it manifests in the form of tiny, faint shadows. This research paper proposes an approach for aiding GGO identification in CT lung images for improved lung cancer prognosis. In the proposed approach, morphological reconstruction is used for segmentation. Once the region of interest (ROI) is extracted, statistical analysis using mean, standard deviation, variance, entropy, skewness, kurtosis, minimum grey scale value, maximum grey scale value and range is performed. The same statistical measures are determined for normal lung and distribution plot is drawn for comparison. It is observed that maximum grey‐scale value demonstrates minimum overlap of approximately 7.4%. To reduce this, a joint feature by summing values of feature mean, skewness, and maximum grey‐scale value was used. This approach reduced the overlap to approximately 1.32%. Lastly, ANN was used for classification of GGO and non‐GGO lung tissue with an achieved accuracy of 99.5%.

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