The Experts below are selected from a list of 2583 Experts worldwide ranked by ideXlab platform
Sidney C. Smith - One of the best experts on this subject based on the ideXlab platform.
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Subacute ventricular free-wall rupture presenting as tamponade without frank Hemopericardium.
Catheterization and cardiovascular diagnosis, 1998Co-Authors: David A. Tate, Joseph J. Lawton, Guy Degent, Sidney C. SmithAbstract:Ventricular free-wall rupture is a well-known catastrophic complication of acute myocardial infarction. A significant number of patients present in a subacute fashion and can be successfully treated with surgery if diagnosed promptly. We present a case of subacute free-wall rupture that occurred after an undiagnosed myocardial infarction. The findings at pericardiocentesis were unusual in that the fluid was sanguinous but not frank Hemopericardium. This patient represents the first known reported case to present without frank Hemopericardium who survived and was successfully treated surgically. The absence of frank Hemopericardium should not exclude the diagnosis of free-wall rupture. Cathet. Cardiovasc. Diagn. 44:417–419, 1998. © 1998 Wiley-Liss, Inc.
Garyfalia Ampanozi - One of the best experts on this subject based on the ideXlab platform.
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Automatic detection of hemorrhagic pericardial effusion on PMCT using deep learning - a feasibility study
Forensic Science Medicine and Pathology, 2017Co-Authors: Lars C. Ebert, Till Sieberth, Anja Leipner, Michael Thali, Jakob Heimer, Wolf Schweitzer, Garyfalia AmpanoziAbstract:Post mortem computed tomography (PMCT) can be used as a triage tool to better identify cases with a possibly non-natural cause of death, especially when high caseloads make it impossible to perform autopsies on all cases. Substantial data can be generated by modern medical scanners, especially in a forensic setting where the entire body is documented at high resolution. A solution for the resulting issues could be the use of deep learning techniques for automatic analysis of radiological images. In this article, we wanted to test the feasibility of such methods for forensic imaging by hypothesizing that deep learning methods can detect and segment a Hemopericardium in PMCT. For deep learning image analysis software, we used the ViDi Suite 2.0. We retrospectively selected 28 cases with, and 24 cases without, Hemopericardium. Based on these data, we trained two separate deep learning networks. The first one classified images into Hemopericardium/not Hemopericardium, and the second one segmented the blood content. We randomly selected 50% of the data for training and 50% for validation. This process was repeated 20 times. The best performing classification network classified all cases of Hemopericardium from the validation images correctly with only a few false positives. The best performing segmentation network would tend to underestimate the amount of blood in the pericardium, which is the case for most networks. This is the first study that shows that deep learning has potential for automated image analysis of radiological images in forensic medicine.
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Differentiation of Hemopericardium due to ruptured myocardial infarction or aortic dissection on unenhanced postmortem computed tomography
Forensic Science Medicine and Pathology, 2017Co-Authors: Garyfalia Ampanozi, Michael Thali, Wolf Schweitzer, Patricia M. Flach, Thomas D. Ruder, Laura Filograna, Lars C. EbertAbstract:The aim of the study was to evaluate unenhanced postmortem computed tomography (PMCT) in cases of non-traumatic Hemopericardium by establishing the sensitivity, specificity and accuracy of diagnostic criteria for the differentiation between aortic dissection and myocardial wall rupture due to infarction. Twenty six cases were identified as suitable for evaluation, of which ruptured aortic dissection could be identified as the underlying cause of Hemopericardium in 50% of the cases, and myocardial wall rupture also in 50% of the cases. All cases underwent a PMCT and 24 of the cases also underwent one or more additional examinations: a subsequent autopsy, or a postmortem magnetic resonance (PMMR), or a PMCT angiography (PMCTA), or combinations of the above. Two radiologists evaluated the PMCT images and classified each case as “aortic dissection”, “myocardial wall rupture” or “undetermined”. Quantification of the pericardial blood was carried out using segmentation techniques. 17 of 26 cases were correctly identified, either as aortic dissections or myocardial ruptures, by both readers. 7 of 13 myocardial wall ruptures were identified by both readers, whereas both readers identified correctly 10 of 13 aortic dissection cases. Taking into account the responses of both readers, specificity was 100% for both causes of Hemopericardium and sensitivity as well as accuracy was higher for aortic dissections than myocardial wall ruptures (72.7% and 87.5% vs 53.8% and 75% respectively). Pericardial blood volumes were constantly higher in the aortic dissection group, but a statistical significance of these differences could not be proven, since the small count of cases did not allow for statistical tests. This study showed that diagnostic criteria for the differentiation between ruptured aortic dissection and myocardial wall rupture due to infarction are highly specific and accurate.
Lars C. Ebert - One of the best experts on this subject based on the ideXlab platform.
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Automatic detection of hemorrhagic pericardial effusion on PMCT using deep learning - a feasibility study
Forensic Science Medicine and Pathology, 2017Co-Authors: Lars C. Ebert, Till Sieberth, Anja Leipner, Michael Thali, Jakob Heimer, Wolf Schweitzer, Garyfalia AmpanoziAbstract:Post mortem computed tomography (PMCT) can be used as a triage tool to better identify cases with a possibly non-natural cause of death, especially when high caseloads make it impossible to perform autopsies on all cases. Substantial data can be generated by modern medical scanners, especially in a forensic setting where the entire body is documented at high resolution. A solution for the resulting issues could be the use of deep learning techniques for automatic analysis of radiological images. In this article, we wanted to test the feasibility of such methods for forensic imaging by hypothesizing that deep learning methods can detect and segment a Hemopericardium in PMCT. For deep learning image analysis software, we used the ViDi Suite 2.0. We retrospectively selected 28 cases with, and 24 cases without, Hemopericardium. Based on these data, we trained two separate deep learning networks. The first one classified images into Hemopericardium/not Hemopericardium, and the second one segmented the blood content. We randomly selected 50% of the data for training and 50% for validation. This process was repeated 20 times. The best performing classification network classified all cases of Hemopericardium from the validation images correctly with only a few false positives. The best performing segmentation network would tend to underestimate the amount of blood in the pericardium, which is the case for most networks. This is the first study that shows that deep learning has potential for automated image analysis of radiological images in forensic medicine.
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Differentiation of Hemopericardium due to ruptured myocardial infarction or aortic dissection on unenhanced postmortem computed tomography
Forensic Science Medicine and Pathology, 2017Co-Authors: Garyfalia Ampanozi, Michael Thali, Wolf Schweitzer, Patricia M. Flach, Thomas D. Ruder, Laura Filograna, Lars C. EbertAbstract:The aim of the study was to evaluate unenhanced postmortem computed tomography (PMCT) in cases of non-traumatic Hemopericardium by establishing the sensitivity, specificity and accuracy of diagnostic criteria for the differentiation between aortic dissection and myocardial wall rupture due to infarction. Twenty six cases were identified as suitable for evaluation, of which ruptured aortic dissection could be identified as the underlying cause of Hemopericardium in 50% of the cases, and myocardial wall rupture also in 50% of the cases. All cases underwent a PMCT and 24 of the cases also underwent one or more additional examinations: a subsequent autopsy, or a postmortem magnetic resonance (PMMR), or a PMCT angiography (PMCTA), or combinations of the above. Two radiologists evaluated the PMCT images and classified each case as “aortic dissection”, “myocardial wall rupture” or “undetermined”. Quantification of the pericardial blood was carried out using segmentation techniques. 17 of 26 cases were correctly identified, either as aortic dissections or myocardial ruptures, by both readers. 7 of 13 myocardial wall ruptures were identified by both readers, whereas both readers identified correctly 10 of 13 aortic dissection cases. Taking into account the responses of both readers, specificity was 100% for both causes of Hemopericardium and sensitivity as well as accuracy was higher for aortic dissections than myocardial wall ruptures (72.7% and 87.5% vs 53.8% and 75% respectively). Pericardial blood volumes were constantly higher in the aortic dissection group, but a statistical significance of these differences could not be proven, since the small count of cases did not allow for statistical tests. This study showed that diagnostic criteria for the differentiation between ruptured aortic dissection and myocardial wall rupture due to infarction are highly specific and accurate.
Andrew J. Nicol - One of the best experts on this subject based on the ideXlab platform.
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Sternotomy or drainage for a Hemopericardium after penetrating trauma: a randomized controlled trial.
Annals of surgery, 2014Co-Authors: Andrew J. Nicol, Pradeep H. Navsaria, Martijn Hommes, Chad G. Ball, Sorin Edu, Delawir KahnAbstract:Objective:To determine if stable patients with a Hemopericardium detected after penetrating chest trauma can be safely managed with pericardial drainage alone.Background:The current international practice is to perform a sternotomy and cardiac repair if a Hemopericardium is detected after penetratin
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Haemopericardium in stable patients after penetrating injury: is subxiphoid pericardial window and drainage enough? A prospective study.
Injury-international Journal of The Care of The Injured, 2005Co-Authors: Pradeep H. Navsaria, Andrew J. NicolAbstract:Summary Aim: This prospective study was undertaken to evaluate whether stable patients with haemopericardium could safely be managed with subxiphoid pericardial window (SPW) and drainage only. Patients and methods: From July to December 2001, all stable patients with haemopericardium diagnosed by SPW, who did not have immediate active bleeding, were subjected to sternotomy to grade the injury using the American Association for the Surgery of Trauma (AAST)-cardiac injury score. The data of all patients with penetrating cardiac injuries for the year 2001 is presented to place into perspective the spectrum of cardiac injuries seen. Results: Fourteen patients qualified for inclusion into the study. Ten (71.4%) patients had Grade I–III cardiac injuries. These could have safely been managed by SPW and drainage alone. The remaining four patients with Grade IV injuries showed no active bleeding at the time of sternotomy. During the first half of the year, seven patients diagnosed with haemopericardium were managed with SPW and drainage only. These seven patients showed no procedure-related complications and were well at 2-week follow-up. Ten patients presented with acute cardiac tamponade. There was a single death in the latter group. Conclusion: This preliminary prospective study, though limited by small numbers, shows that 10/14 (71%) of stable patients with haemopericardium had unnecessary non-therapeutic sternotomy and could have safely been managed with SPW and drainage only. Further prospective, randomised studies are required to confirm the good outlook.
N. K. Tumram - One of the best experts on this subject based on the ideXlab platform.
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Hemopericardium with Subdural Hemorrhage: A Rare Case
Journal of Indian Academy of Forensic Medicine, 2014Co-Authors: S. B. Bhoi, D. K. Shinde, K. S. Chandekar, N.p. Mahajan, N. K. TumramAbstract:The incidence of simultaneous occurrence of intracranial hemorrhage and Hemopericardium due to the rupture of a dissecting aneurysm is very rare. We describe an autopsy case of a 52-year-old male with hypertension who died suddenly. He had been treated for hypertension. During post-mortem examination we found pericardial cavity filled with blood and blood clots. This Hemopericardium was due to rupture of dissecting aortic aneurysm. Ascending aorta shows ruptured dissecting aortic aneurysm [De Bakey type 2]. Intramural hematoma present in the wall of ascending aorta. Histologically, the wall of the aneurysm revealed cystic medial necrosis, which appears to idiopathic in nature. There was also evidence of subdural hemorrhage. After analyzing the findings the opinion as to the cause of death was “Hemopericardium due to rupture of dissecting aortic aneurysm along with intracranial bleeding”. As per our view in present case the subdural hemorrhage was occurred after the rupture of dissecting aortic aneurysm when the venous pressure increases, leading to the rupture of bridging vein in subdural space.