Feasibility study of relative renal function assessment by contrast-enhanced abdominal CT in comparison to 99mTc-MAG3 renal scintigraphy

Objective: To determine the feasibility of using contrast-enhanced abdominal CT to assess relative renal function. Materials and Methods: This retrospective study reviewed data from 32 patients who had had investigations by contrast-enhanced abdominal CT and 99mTc-MAG3 renal scintigraphy, within a period of not more than 30 days. Post-processing CT images of kidneys were by manual segmentation and calculated to interpret the relative renal function. Results: There was strong correlation between CT derived relative renal function and 99mTc-MAG3 renal scintigraphy (r = 0.971, p < 0.001) and no statistically significant difference in renal function between the two techniques (p = 0.572). Conclusion: Contrast-enhanced abdominal CT can determine relative renal function as accurately as renal scintigraphy. It is an appropriate alternative method, especially in hospitals where renal scintigraphy is not available.

Download Full-text

1905: The Effect of Percutaneous Nephrolithotripsy (PCNL) on Renal Function: Assessment with Quantitative Spect of TC 99M-DMSA (QDMSA) Renal Scintigraphy

The Journal of Urology ◽

10.1016/s0022-5347(18)39097-9 ◽

2004 ◽

Vol 171 (4S) ◽

pp. 503-503

Author(s):

Boaz Moskovitz ◽

Vladimir Sopov ◽

Sarel Halachmi ◽

Michael Mullerad ◽

Yusef Barbara ◽

...

Keyword(s):

Renal Function ◽

Renal Scintigraphy ◽

Quantitative Spect ◽

Percutaneous Nephrolithotripsy ◽

Function Assessment

Download Full-text

Glycaemic Control after Metformin Discontinuation in Diabetic Patients with a Declining Renal Function

Journal of Diabetes Research ◽

10.1155/2017/2769819 ◽

2017 ◽

Vol 2017 ◽

pp. 1-6 ◽

Cited By ~ 1

Author(s):

Theresa Leyco ◽

Davin Ryanputra ◽

Ray Peh ◽

Alexphil Ponce ◽

Chin Meng Khoo

Keyword(s):

Chronic Kidney Disease ◽

Renal Function ◽

Body Weight ◽

Retrospective Study ◽

Glycaemic Control ◽

Tertiary Hospital ◽

Diabetic Patients ◽

Diabetes Clinic ◽

Significant Difference

Metformin is contraindicated in diabetic patients with declining renal function. This study examined the glycaemic control in diabetic patients with chronic kidney disease when metformin was discontinued. This was a retrospective study. We screened 2032 diabetic patients who attended the Diabetes Clinic at a tertiary hospital between 1 September 2014 and 30 September 2015. We analyzed the data on 69 patients whom metformin was discontinued due to declining renal function and had a complete 6-month follow-up. There was no significant difference in the HbA1c and body weight at 6-month follow-up compared to baseline after metformin discontinuation. The eGFR was significantly lower at 6-month follow-up compared to baseline. Upon metformin discontinuation, the majority of patients had their diabetes medication uptitrated (in particular insulin or sulphonylurea). Patients with an improved glycaemia at 6-month follow-up had further declined in eGFR compared to patients with worsened glycaemia. 17% of the study patients experienced hypoglycaemia. Upon metformin discontinuation, glycaemic control could be optimised with uptitration but should be balanced against the risk of hypoglycaemia. Further improvement in the glycaemic control might indicate further deterioration in the renal function.

Download Full-text

CT facilitates improved diagnosis of adult intestinal malrotation: a 7-year retrospective study based on 332 cases

Insights into Imaging ◽

10.1186/s13244-021-00999-3 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Ziman Xiong ◽

Yaqi Shen ◽

John N. Morelli ◽

Zhen Li ◽

Xuemei Hu ◽

...

Keyword(s):

Retrospective Study ◽

Mesenteric Artery ◽

Superior Mesenteric Vein ◽

Clinical Information ◽

Classification Criteria ◽

Intestinal Malrotation ◽

Abdominal Ct ◽

Asymptomatic Patients ◽

Significant Difference ◽

The Right

Abstract Objective To classify adult intestinal malrotation by CT. Methods This retrospective study enrolled adults diagnosed with intestinal malrotation who underwent abdominal CT at our institution between June 1, 2013, and August 30, 2020. All patients’ clinical information was recorded. Patients were divided into groups undergoing surgical and conservative management. The duodenum (nonrotation, partial rotation, and malrotation), jejunum, cecum, and the superior mesenteric artery/superior mesenteric vein relationship were reviewed on the CT images of each patient, and classification criteria developed based on the first three items. For each patient, each item was assessed separately by three radiologists. Consensus was required from at least two of them. Results A total of 332 eligible patients (218 men and 114 women; mean age 51.0 ± 15.3 years) were ultimately included and classified into ten types of malrotation. Duodenal partial rotation was present in most (73.2%, 243/332) with only 25% (83/332) demonstrating nonrotation. The jejunum was located in the right abdomen in 98.2% (326/332) of cases, and an ectopic cecum was found in only 12% (40/332, 29 cases with a left cecum, 7 pelvic, and 4 at midline). Asymptomatic patients comprised 56.6% (188/332) of cases, much higher than that in previous studies (17%, n = 82, p < .001), comprised mainly of patients with duodenal partial rotation (80.3%, 151/188). In 91 patients with detailed clinical data available (12 managed surgically and 79 conservatively), a significant difference in malrotation CT categorization was identified (p = .016). Conclusions CT enables greater detection of asymptomatic intestinal malrotation, enabling classification into multiple potentially clinically relevant subtypes.

Download Full-text

An Artificial Intelligence Hypothetical Approach for Masseter Muscle Segmentation on Ultrasonography in Patients With Bruxism

Journal of Advanced Oral Research ◽

10.1177/23202068211005611 ◽

2021 ◽

pp. 232020682110056

Author(s):

Kaan Orhan ◽

Gokhan Yazici ◽

Mehmet Eray Kolsuz ◽

Nihan Kafa ◽

Ibrahim Sevki Bayrakdar ◽

...

Keyword(s):

Neural Network ◽

Artificial Intelligence ◽

Retrospective Study ◽

Masseter Muscle ◽

Area Under The Curve ◽

Muscle Thickness ◽

Human Observer ◽

Manual Segmentation ◽

Significant Difference ◽

Muscle Segmentation

Aim: The present study is aimed to assess the segmentation success of an artificial intelligence (AI) system based on the deep convolutional neural network (D-CNN) method for the segmentation of masseter muscles on ultrasonography (USG) images. Materials and Methods: This retrospective study was carried out by using the radiology archive of the Department of Oral and Maxillofacial Radiology of the Faculty of Dentistry in Ankara University. A total of 195 anonymized USG images were used in this retrospective study. The deep learning process was performed using U-net, Pyramid Scene Parsing Network (PSPNet), and Fuzzy Petri Net (FPN) architectures. Muscle thickness was assessed using USG by manual segmentation and measurements using USG’s software. The neural network model (CranioCatch, Eskisehir-Turkey) was then used to determine the muscles, following automatic measurements of the muscles. Accuracy, ROC area under the curve (AUC), and Precision-Recall Curves (PRC) AUC were calculated in the test dataset and compare a human observer and the AI model. Manual segmentation and measurements were compared statistically with AI ( P < .05). The Mann–Whitney U test was used to analyze whether there is a statistically significant difference between the predicted values and the actual values. Results: The AI models detected and segmented all test muscle data for FPN and U-net, while only two cases of muscles were not detected by PSPNet (false negatives). Accuracies of FPN, PSPNet, and U-net were estimated as 0.985, 0.947, and 0.969, respectively. Receiver operating characteristic scores of FPN, PSPNet, and U-net were estimated as 0.977, 0.934, and 0.969, respectively. The D-CNN measurements of the muscles were similar to manual measurements. There was no significant difference between the two measurement methods in three groups ( P > .05). Conclusion: The proposed AI system approach for the analysis of USG images seems to be promising for automatic masseter muscle segmentation and measurement of thickness. This method can help surgeons, radiologists, and other professionals such as physical therapists in evaluating the time correctly and saving time for diagnosis.

Download Full-text