Significant differences in postmortem heart weight before and after dissection using the short-axis dissecting method

Correctly assessing heart weight can be critical at postmortem examination. The current international guidelines advocate using the short-axis method in dissecting the heart and the heart weighed when the blood is emptied. However, it did not specify at what point the heart should be weighed or how the blood should be emptied. This study compared heart weights at three different time points during the heart examination (immediately after dissecting out of the pericardial sac with blood still in chambers, blood washed/removed from heart chambers without the heart opened, and the heart completely opened, blood emptied, and pad dried). This was to illustrate the variation in measurement and potential errors when the heart is weighed at different time of dissection. The results show that there were statistical and clinical significant differences between the heart weights at each weighing points. We recommend the heart to be completely dissected with any blood and residual washing/rinsing water emptied before being weighed. Although performed in this study, the effect of pad drying the heart on heart weight was not explored and was a limitation in this study

Identifying fatal head injuries on postmortem computed tomography using convolutional neural network/deep learning : a feasibility study

Postmortem computed tomography (PMCT) is a relatively recent advancement in forensic pathology practice that has been increasingly used as an ancillary investigation and screening tool. One area of clinical CT imaging that has garnered a lot of research interest recently is the area of “artificial intelligence” (AI), such as in screening and computer-assisted diagnostics. This feasibility study investigated the application of convolutional neural network, a form of deep learning AI, to PMCT head imaging in differentiating fatal head injury from controls. PMCT images of a transverse section of the head at the level of the frontal sinus from 25 cases of fatal head injury were combined with 25 nonhead-injury controls and divided into training and testing datasets. A convolutional neural network was constructed using Keras and was trained against the training data before being assessed against the testing dataset. The results of this study demonstrated an accuracy of between 70% and 92.5%, with difficulties in recognizing subarachnoid hemorrhage and in distinguishing congested vessels and prominent falx from head injury. These results are promising for potential applications as a screening tool or in computer-assisted diagnostics in the future

Identifying gross post-mortem organ images using a pre-trained convolutional neural network

Identifying organs/tissue and pathology on radiological and microscopic images can be performed using convolutional neural networks (CNN). However, there are scant studies on applying CNN to post-mortem gross images of visceral organs. This proof-of-concept study used 537 gross post-mortem images of dissected brain, heart, lung, liver, spleen, and kidney, which were randomly divided into a training and teaching datasets for the pre-trained CNN Xception. The CNN was trained using the training dataset and subsequently tested on the testing dataset. The overall accuracies were >95% percent for both training and testing datasets and have an F1 score of >0.95 for all dissected organs. This study showed that small datasets of post-mortem images can be classified with a very high accuracy using a pre-trained CNN. This novel area has the potential for future application in data mining, education and teaching, case review, research, quality assurance, auditing purposes, and identifying pathology

Significant Differences in PostMortem Heart Weight Before and After Dissection Using the Short‐Axis Dissecting Method

Correctly assessing heart weight can be critical at postmortem examination. The current international guidelines advocate using the short-axis method in dissecting the heart and the heart weighed when the blood is emptied. However, it did not specify at what point the heart should be weighed or how the blood should be emptied. This study compared heart weights at three different time points during the heart examination (immediately after dissecting out of the pericardial sac with blood still in chambers, blood washed/removed from heart chambers without the heart opened, and the heart completely opened, blood emptied, and pad dried). This was to illustrate the variation in measurement and potential errors when the heart is weighed at different time of dissection. The results show that there were statistical and clinical significant differences between the heart weights at each weighing points. We recommend the heart to be completely dissected with any blood and residual washing/rinsing water emptied before being weighed. Although performed in this study, the effect of pad drying the heart on heart weight was not explored and was a limitation in this study

Differences between central and peripheral postmortem tryptase levels

Postmortem tryptase is a commonly used biochemical test to aid in the diagnosis of fatal anaphylaxis, which is currently recommended to be sampled from peripheral (femoral) veins because of a research showing comparatively elevated levels from central blood sources. Previous studies have used nonstandardized or nondocumented sampling methods; however, more recent research demonstrates that tryptase levels may vary depending on the sampling method. This study used the recommended sampling method of aspirating the femoral vein after clamping and compared in a pairwise comparison with aspiration of central venous and arterial blood sources (inferior vena cava and aorta) in 2 groups of 25 nonanaphylactic deaths. We found no statistically significant differences in postmortem tryptase between central and femoral vein blood; however, sporadic outliers in central blood (particularly aortic blood reaching levels above documented cutoffs for fatal anaphylaxis) were observed. Our findings provide evidence for the existing recommendations that femoral vein blood remains the preferred sample for postmortem tryptase over central blood

Levels of haemolysis have no effect on femoral vein post-mortem tryptase levels

Haemolysis is reported to be an artefact that may alter post-mortem tryptase levels. However, previous studies did not sample peripheral blood using newly standardised methods. Recent studies have shown that some previously recognised peri- and post-mortem confounders can be muted by careful sample collection with first clamping and then sampling the femoral vein. This prospective study investigated the relationship between the degree of haemolysis of the blood samples and femoral vein post-mortem tryptase levels when sampled using this recommended method. Seventy consecutive post-mortem tryptase levels in non-anaphylactic deaths were compared to the degree of haemolysis of these samples, and results showed no significant correlation between them. The mean post-mortem tryptase level was 9.5 μg/L. This study demonstrated that the effects of haemolysis on femoral vein post-mortem tryptase was negligible when the blood was sampled using the recommended sampling method. Future studies on post-mortem tryptase as well as other typically used blood markers in forensics are recommended to adopt this method of blood sampling in routine practice

Using vitreous humour and cerebrospinal fluid electrolytes in estimating post-mortem interval : an exploratory study

Many previous studies have investigated the use of post-mortem biochemistry to estimate the post-mortem interval (PMI). Vitreous humour (VH) potassium and sodium/chloride levels are well recognized to increase and decrease, respectively, in the post-mortem period but have limited ability in estimating PMI. Cerebrospinal fluid (CSF) is described to have different post-mortem biochemical properties than VH, but is not well studied in relation to estimating PMI. This exploratory study examined 20 paired cases of VH and CSF to investigate their use in estimating PMI. Linear univariate analysis showed Na+, Cl− and K+ in VH and CSF share similar trends, but only K+ in VH and CSF collected via lumbar puncture (LP) showed a significant regression coefficient (p < 0.01). In subsequent linear multivariate analysis, the coefficient for K+ in VH remained positive and significant but not for K+ in CSF. Only minor improvement was observed in the multivariate analysis. Our study showed changes in analytes in VH and CSF follow similar trends. K+ in VH is most accurate in estimating the PMI, with no significant improvement in accuracy when K+ in CSF is combined. Thus, the role of CSF electrolytes in estimating PMI may be very limited

Classifying microscopic acute and old myocardial infarction using convolutional neural networks

Convolutional neural network (CNN) has advanced in recent years and translated from research into medical practice, most notably in clinical radiology and histopathology. Research on CNNs in forensic/postmortem pathology is almost exclusive to postmortem computed tomography despite the wealth of research into CNNs in surgical/anatomical histopathology. This study was carried out to investigate whether CNNs are able to identify and age myocardial infarction (a common example of forensic/postmortem histopathology) from histology slides. As a proof of concept, this study compared 4 CNNs commonly used in surgical/anatomical histopathology to identify normal myocardium from myocardial infarction. A total of 150 images of the myocardium (50 images each for normal myocardium, acute myocardial infarction, and old myocardial infarction) were used to train and test each CNN. One of the CNNs used (InceptionResNet v2) was able to show a greater than 95% accuracy in classifying normal myocardium from acute and old myocardial infarction. The result of this study is promising and demonstrates that CNN technology has potential applications as a screening and computer-assisted diagnostics tool in forensic/postmortem histopathology

Classifying Microscopic Acute and Old Myocardial Infarction Using Convolutional Neural Networks

Convolutional neural network (CNN) has advanced in recent years and translated from research into medical practice, most notably in clinical radiology and histopathology. Research on CNNs in forensic/postmortem pathology is almost exclusive to postmortem computed tomography despite the wealth of research into CNNs in surgical/anatomical histopathology. This study was carried out to investigate whether CNNs are able to identify and age myocardial infarction (a common example of forensic/postmortem histopathology) from histology slides. As a proof of concept, this study compared 4 CNNs commonly used in surgical/anatomical histopathology to identify normal myocardium from myocardial infarction. A total of 150 images of the myocardium (50 images each for normal myocardium, acute myocardial infarction, and old myocardial infarction) were used to train and test each CNN. One of the CNNs used (InceptionResNet v2) was able to show a greater than 95% accuracy in classifying normal myocardium from acute and old myocardial infarction. The result of this study is promising and demonstrates that CNN technology has potential applications as a screening and computer-assisted diagnostics tool in forensic/postmortem histopathology