Diagnostic accuracy of postmortem MRI for musculoskeletal abnormalities in fetuses and children
Owen J Arthurs1, Sudhin Thayyil, Shea Addison
1Department of Radiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK; Institute of Child Health, UCL, London, UK.
Objectives:
The aim of this study was to compare the diagnostic accuracy of postmortem magnetic resonance (PMMR) imaging specifically for musculoskeletal pathology in fetuses and children, compared with conventional autopsy, with radiographic and histopathology assessment.
Methods:
Institutional ethics approval and parental consent was obtained. A total of 400 cases underwent PMMR using a 1.5 T Siemens Avanto MR scanner before conventional autopsy. PMMR images and autopsy findings were reported blinded to the other data, respectively.
Results:
A total of 400 cases were reported, with 277 (69%) fetuses (185 ≤24 weeks' gestation and 92 >24 weeks' gestation) and 123 children (42 newborns aged <1 month, 53 infants ≤12 months and 28 children ≤16 years). Musculoskeletal (MSK) abnormalities were found at autopsy in 47/400 (11.7%). Overall sensitivity and specificity (with 95% confidence interval) of PMMR for MSK pathology were 51.1% (37.0, 65.0) and 98.2% (96.2, 99.2), with positive and negative predictive values of 79.3% (61.6, 90.2) and 93.8% (90.8, 95.9), respectively. Overall accuracy between PMMR and autopsy for MSK abnormalities was 92.7% (89.7, 94.9). In some cases, PMMR detected MSK abnormalities not routinely examined for or detected at traditional autopsy.
Conclusion:
Minimally invasive autopsy has good diagnostic accuracy for the exclusion of MSK abnormalities, but sensitivity is relatively poor. When PMMR is used with clinical examination and skeletal radiographs, all skeletal and soft tissue abnormalities of clinical significance are likely to be detected, even if not directly relevant to the cause of death.
Insights
Postmortem MRI (PMMR) shows good accuracy for excluding fetal and pediatric musculoskeletal abnormalities. While PMMR sensitivity is low, combining it with clinical exams and radiographs detects significant skeletal and soft tissue issues.
Area of Science:
- Forensic pathology
- Pediatric radiology
- Medical imaging
Background:
- Conventional autopsy is the standard for investigating fetal and pediatric deaths.
- Musculoskeletal (MSK) abnormalities can be challenging to detect and assess via traditional autopsy methods.
- Advanced imaging techniques like postmortem MRI (PMMR) offer potential for improved diagnostic accuracy.
Purpose of the Study:
- To compare the diagnostic accuracy of PMMR for musculoskeletal pathology in fetuses and children against conventional autopsy.
- To evaluate PMMR's effectiveness when combined with radiographic and histopathology assessments.
- To determine the sensitivity, specificity, and overall accuracy of PMMR in identifying MSK abnormalities.
Main Methods:
- A total of 400 cases (277 fetuses, 123 children) underwent PMMR using a 1.5T MRI scanner prior to conventional autopsy.
- PMMR images and autopsy findings were analyzed independently by blinded reviewers.
- Data included gestational age, age at death, and presence/absence of MSK abnormalities.
Main Results:
- Musculoskeletal abnormalities were identified in 11.7% of cases at autopsy.
- PMMR demonstrated high specificity (98.2%) but relatively low sensitivity (51.1%) for detecting MSK pathology.
- Overall diagnostic accuracy of PMMR for MSK abnormalities was 92.7%, with some abnormalities detected only by PMMR.
Conclusions:
- PMMR is valuable for excluding MSK abnormalities in minimally invasive autopsies.
- The sensitivity of PMMR alone for MSK pathology is limited.
- Integrating PMMR with clinical examination and skeletal radiography enhances the detection of clinically significant skeletal and soft tissue abnormalities.
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Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...


