Recent Advances in Forensic Medicine

Introduction

There is transformative advancement in forensic medicine in recent years with technological development and innovations leading to enhanced scope, precision and efficiency of medicolegal investigations. Innovative methods such as non-invasive postmortem examination (Virtopsy), artificial intelligence (AI)-based technologies and robotics redefined after-death analysis (Shavchikista) and crime scene reconstruction. ¹ It facilitates to minimise human bias with standardisation and more precise results.

The integration of advanced technologies for improvement in efficiency and accuracy of forensic investigations such as AI-driven imaging techniques, multi-detector computer tomography (MDCT) and non-invasive virtual autopsy have made revolutionary change towards identification of injuries and finding the cause of death. But there are many ethical, legal and operational challenges in the adoption and implementation of these advanced technologies. ² AI-based non-invasive autopsies are going to provide a culturally sensitive alternative to traditional autopsies with enhanced diagnostic precision and accuracy using advanced imaging modalities.^{3, 4}

The rapid and mobile DNA technology platforms provide prompt identification in time-sensitive situations such as mass disasters and border security operations. The technological integration of AI in Virtopsy, along with other advanced imaging techniques for non-invasive autopsies, enhances DNA analysis and evidence evaluation. These developments, combined with rapid, mobile DNA platforms, enable faster identification and facilitate crime investigations.^{5, 6}

However, there are significant challenges in implementation of these techniques such as the high cost of technologically advanced equipment, algorithmic biases, less control data, data standardisation and data privacy issues, lack of standardised forensic imaging protocol, legal barriers and so on. There is promising future potential for cross-cultural, national and international forensic collaborations with the use of advanced technologies and AI in forensic medicine. ⁷

Recent Advances in Forensic Medicine

Advancements in AI, Imaging and Other Technologies

The integration advanced imaging technology and AI in forensic medicine has led to significant advancement in the field. The advancement significantly increased the accuracy and efficiency of forensic investigations and minimised human biases. These advancements include:

• AI-driven imaging: Techniques like MDCT, 3D postmortem CT angiography (PMCTA) and AI-driven imaging revolutionised injury identification and finding causes of death.^{2, 3, 5}

• Digital forensics: AI improved the analysis of digital evidence through advanced automation and intelligence. ⁸

• Digital facial reconstruction: The modern computer-based facial recognition system is the advanced equivalent of the older facial recognition technique and provides a powerful tool for human identification in large datasets. ⁸

• Virtopsy: It provides two-dimensional and three-dimensional processing techniques, combining surface and in vivo information with geometrically realistic records. It also combines the finite elements for computer-simulated dynamic simulation studies. AI-based techniques are useful in crime scene reconstruction and postmortem CT examinations.^{5, 6}

• Phenotype prediction: AI is useful to predict the physical traits of a person from their deoxyribose nucleic acid (DNA).

• Next generation sequencing: It is a ground-breaking forensic technology which analyses DNA with more details.

• Omics techniques: These techniques include micro–biome, proteomics, metabolomics, transcriptomics and genomics. These techniques are useful in comprehensive and systemic study of biological samples.^{9, 10}

• Microbiome analysis: The microbiome, that is, the collection of microbes including viruses, bacteria, fungi and their genes that occur naturally in our body, are the unique biomarker for human identification. Microbiome analysis leads to an increase in the accuracy for individual identification and geographical origin using AI. Microbiome applications are useful in forensic analysis of bite marks, sexual assault cases, geographical identification, person identification and postmortem analysis. ¹¹

Benefits of AI Imaging in Forensic Medicine

• Improved efficiency and diagnostic accuracy: With AI algorithms, the analysis of medical images can be done speedily and accurately surpassing human capabilities.

• Enhanced image quality: With advanced technology contributing image enhancement, better decision making and advanced crime predictions can be made.

• Precise disease detection and cause of death: Sometimes the subtle pattern and anomalies may be missed by human eyes leading to errors of judgement and delayed/non-detection of disease. This may be overcome by an AI-based approach which facilities accurate detection of disease and underlying conditions leading to death.

• Automation of routine tasks: AI can automate routine repetitive tasks, and time and resources can be utilized appropriately. AI also has ability to automate tasks like DNA profiling, postmortem imaging and toxicology analysis.

Advancement in Forensic Toxicology

Recently, there has been a significant advancement in toxicology towards understanding and mitigating the effects of toxins on humans and the environment. New technology is developing with new approaches of toxin detection. ¹² These are as follows:

• Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 and gene editing: The CISPER-Cas9 technology used for DNA modifications at specific locations using enzyme Cas9 which enables addition, removal or alteration of genetic material. This evolving novel technology can be used in biotechnology, medicine and agriculture. It facilitates understanding toxin mechanisms and developing precise therapies.

• Next Generation Identification (NGI): The Federal Bureau of Investigation (FBI) has developed the largest electronic repository of biometric information and criminal history information in the world called NGI. It incorporates various biometric modalities like facial recognition, palm prints, fingerprints, iris scans and voice prints in investigating criminal activities including terrorism, cybercrime and civil rights violations.

• 3D microfluidic liver models: Drug-induced liver injury is a major health concern leading to acute liver failure and further fatal complications. There is improved drug development and safety testing with innovative models like the OrganoPlate which enable high-throughput compounds for toxicity screening.

• Computational tools: Human and ecological exposures to chemical substances can be assessed using computational tools which enhance the risk assessment and safety evaluations of toxins.

• Personalised clinical toxicology: Studying the individual differences in toxin metabolism and response using advanced technology becomes easier for researchers because they facilitate the development of personalised clinical toxicology.

• Toxin research and applications: Innovative methods of treating cardiovascular diseases and pain management with marine toxins, such as tetrodotoxin and ω-conotoxins; pest management strategies using bacterial toxins, like Bt Cry toxins; chronic kidney disease and colorectal cancer management using uremic toxins, such as indoxyl sulphate, are under investigation.

• Advanced forensic analysis: Development of rapid, mobile DNA platforms for faster identification in the field of forensic toxicology will be helpful. Compressive data on the effect of toxins is being gathered using metabolomics and toxicogenomics.

• AI in toxicology: AI is being applied to clinical toxicology for predicting toxicity effects, optimising risk assessments, identifying patterns and personalised management. Innovations in toxicity risk assessment further facilitates personalised therapy development, safety precautions and environmental protection.

Challenges in Adoption and Implementation of Technological Advancements

There is global demand for accurate, efficient and timely forensic evaluations and use of the modern advanced techniques facilitates the same. However, there are multiple challenges in the adoption and implementation of these technologies.

Some important challenges includes the lack of appropriate standardised algorithms leading to algorithmic biases, ¹³ various ethical and legal concerns as there are no standardised guidelines of the ethical use of AI and advanced technology, ¹⁴ issues related to data privacy and confidentiality, ¹⁵ there may be over reliance on machines and self-clinical conscience and the power of decision making may be loosed. Finally, there is no appropriate uniform framework for legal admissibility of the results and AI interpretability in the court of law.

There are operational and resource related barriers such as technical infrastructure, trained personnel scarcity, high equipment cost and cybersecurity. ¹⁶ There is need for interdisciplinary collaborations and training with integrated efforts by professionals such as forensic experts, radiologists, pathologists and technological experts. ¹⁷ Cultural adaptability with need of society and global collaboration may further facilitate smooth implementations of newer innovations. ¹⁸

Future Directions

• There is a need to develop transparent and user-friendly AI algorithms. For this, the datasets need to be developed and improved. With training and awareness, we can further reduce human error and biases.

• Collaboration amongst the experts of various fields, such as forensic, legal and AI, will facilitate its smooth implementation. There is a need to establish standard protocol with appropriate legal and regulatory framework for the use of AI-based forensic applications.

Conclusions

Recent advances in forensic imaging technology have the potential to revolutionise forensic investigations and after-death analysis. Further, AI-driven algorithms help to augment DNA mixture interpretation and phenotype prediction. They give automated evidence evaluation results. In spite of these advancements, multiple challenges related to validation, standardisation and ethical scrutiny continue to affect the reliability of these technologies in the judicial system. There is a need for robust validation and standardisation to ensure their admissibility in a court of law. The operational, financial, ethical and legal challenges need to be dealt with collaboration on the interdisciplinary, national and international levels by formulating standardised guidelines with robust validation to ensure their admissibility in a court of law.