Forensic age assessment of the knee: proposal of a new classification system using two-dimensional ultrasound volumes and comparison to MRI.

OBJECTIVES: To assess epiphyseal growth plate closure of the knee for forensic age estimation using an ultrasound (US)-based method and to compare the findings with MRI. METHODS: Thirty-three healthy male individuals (age, 14.4-19.3 years) were prospectively evaluated for epiphyseal growth plate closure of the right knee by recordings of two-dimensional US volumes and a high-resolution T1-weighted MRI sequence. The degree of epiphyseal growth plate closure was rated independently by two readers for each method using a modality specific three-point scale that differentiates between an open physis (S1), a partially closed physis (S2), and a closed physis (S3). RESULTS: The inter-rater agreement was high for the US (Cohen's kappa (CK): femur 95.2%, tibia 81.3%, fibula 86.3%) and the MRI method (CK: femur 70.2%, tibia 90.8%, fibula 79.8%). The degree of growth plate closure associated positively with advancing age. The US system showed a clearer separation of median ages with lower overlap than the MRI system. Open growth plates on minors (< S3 on femur and tibia) were identified by US with higher sensitivity (1.0 vs. 0.7) and slightly lower specificity (0.7 vs. 0.85) compared with MRI. The examination time was substantially shorter on US than on MRI (2.65 ± 0.91 min vs. 24.72 ± 2.72 min; p < 0.001). CONCLUSIONS: The US method for evaluation of growth plate closure of the knee can reliably assign male individuals to different ossification stages and identifies minors with high accuracy. More studies with larger numbers are needed to further evaluate this method. KEY POINTS: • US is feasible to determine the degree of epiphyseal growth plate closure of the knee, shows a high degree of reliability, and is comparable to MRI. • US of the knee can detect open growth plates on male minors with high accuracy. • US of the knee may be used as a fast, non-invasive imaging tool for forensic age estimation to identify male minors.

Automated age estimation of young individuals based on 3D knee MRI using deep learning.

Age estimation is a crucial element of forensic medicine to assess the chronological age of living individuals without or lacking valid legal documentation. Methods used in practice are labor-intensive, subjective, and frequently comprise radiation exposure. Recently, also non-invasive methods using magnetic resonance imaging (MRI) have evaluated and confirmed a correlation between growth plate ossification in long bones and the chronological age of young subjects. However, automated and user-independent approaches are required to perform reliable assessments on large datasets. The aim of this study was to develop a fully automated and computer-based method for age estimation based on 3D knee MRIs using machine learning. The proposed solution is based on three parts: image-preprocessing, bone segmentation, and age estimation. A total of 185 coronal and 404 sagittal MR volumes from Caucasian male subjects in the age range of 13 and 21 years were available. The best result of the fivefold cross-validation was a mean absolute error of 0.67 ± 0.49 years in age regression and an accuracy of 90.9%, a sensitivity of 88.6%, and a specificity of 94.2% in classification (18-year age limit) using a combination of convolutional neural networks and tree-based machine learning algorithms. The potential of deep learning for age estimation is reflected in the results and can be further improved if it is trained on even larger and more diverse datasets.

A 2-year follow-up MRI study for the evaluation of an age estimation method based on knee bone development.

Age estimation is an actual topic in the area of forensic medicine with a special focus on the age limits of 16 and 18 years. Current research on this topic relies on retrospective data of inhomogeneous populations relating to sex, age range, and socioeconomic status. In this work, we present a 2-year follow-up study for the evaluation of an age estimation method on a prospective magnetic resonance imaging (MRI) knee data collective of a homogeneous population. The study includes 40 male subjects from northern Germany aged 14 to 21 years. Three MRI examinations were evenly acquired within 2 years for each subject. As a first evaluation, a three-stage system was used to assess the ossification status of the knee (I:"open", II:"partially ossified", III:"fully ossified"). Three raters assessed the growth plate of the distal femur, proximal tibia, and proximal fibula based on central 2D slices. A good inter-rater agreement was attained (κ = 0.84). All subjects younger than 18 years were rated as stage I and had a cumulative knee score (SKJ) ≤ 5. Based on the follow-up datasets, new parameters quantifying the intra-individual ossification process were calculated. The results of this follow-up analysis show a different start, end, and speed of each growth plate's maturation as well as an ossification peak for individuals at the age of 16. The generated MRI database provides new insights into the ossification process over time and serves as a basis for further evaluations of age estimation methods.

Automated segmentation of the knee for age assessment in 3D MR images using convolutional neural networks.

Age assessment is used to estimate the chronological age of an individual who lacks legal documentation. Recent studies indicate that the ossification degree of the growth plates in the knee joint correlates with chronological age of adolescents and young adults. To verify this hypothesis, a high number of datasets need to be analysed. An approach which enables an automated detection and analysis of the bone structures may be necessary to handle large datasets. The purpose of this study was to develop a fully automatic 2D knee segmentation based on 3D MR images using convolutional neural networks. A total of 76 datasets were available and divided into a training set (74%), a validation set (13%) and a test set (13%). Multiple preprocessing steps were applied to correct image intensity values and to reduce the image size. Image augmentation was employed to virtually increase the dataset size for training. The proposed architecture for the segmentation task resembles the encoder-decoder model type used for the U-Net. The trained network achieved a dice similarity coefficient score of 98% compared to the manual segmentations and an intersection over union of 96%. The precision and recall of the model were balanced, and the error was only 1.2%. No overfitting was observed during training. As a proof of concept, the predicted segmentations were used for the age estimation of 145 subjects. Initial results show the potential of this approach attaining a mean absolute error of 0.48 ± 0.32 years for a test set of 14 subjects. The proposed automated segmentation can contribute to faster, reproducible and potentially more reliable age estimation in the future.

Acute versus Chronic Myocardial Infarction: Diagnostic Accuracy of Quantitative Native T1 and T2 Mapping versus Assessment of Edema on Standard T2-weighted Cardiovascular MR Images for Differentiation.

Purpose To analyze the diagnostic accuracy of native T1 and T2 mapping compared with visual and quantitative assessment of edema on T2-weighted cardiac magnetic resonance (MR) images to differentiate between acute and chronic myocardial infarction. Materials and Methods This study had institutional ethics committee approval. Written informed consent was obtained from 67 consecutive patients (57 years ± 12; 78% men) with a first acute myocardial infarction, who were prospectively enrolled between April 2011 and June 2015. Four serial 1.5-T MR imaging examinations were performed at 8 days ± 5, 7 weeks ± 2, 3 months ± 0.5, and 6 months ± 1.4 after infarction and included T2-weighted, native T1/T2 mapping, and late gadolinium enhancement MR imaging. Complete follow-up data were obtained in 42 patients. Regional native T1/T2 relaxation time, T2-weighted ratio, and extracellular volume were serially measured in infarcted and remote myocardium. Receiver operating characteristic (ROC) analysis was used to determine the diagnostic accuracy of the MR imaging parameters for discriminating between acute and chronic myocardial infarction. Results Native T1 of infarcted myocardium decreased from 1286 msec ± 99 at baseline to 1077 msec ± 50 at 6 months (P < .0001), whereas T2 decreased from 84 msec ± 10 to 58 msec ± 4 (P < .0001). The T2-weighted ratio decreased from 4.1 ± 1.0 to 2.4 ± 0.6 (P < .0001). Of all the MR imaging parameters obtained, native T1 and T2 yielded the best areas under the ROC curve (AUCs) of 0.975 and 0.979, respectively, for differentiating between acute and chronic myocardial infarction. Visual analysis of the presence of edema at standard T2-weighted cardiac MR imaging resulted in an inferior AUC of 0.863 (P < .01). Conclusion Native T1 and T2 of infarcted myocardium are excellent discriminators between acute and chronic myocardial infarction and are superior to all other MR imaging parameters. Online supplemental material is available for this article.

Prediction of the estimated 5-year risk of sudden cardiac death and syncope or non-sustained ventricular tachycardia in patients with hypertrophic cardiomyopathy using late gadolinium enhancement and extracellular volume CMR.

OBJECTIVES: To evaluate the ability of late gadolinium enhancement (LGE) and mapping cardiac magnetic resonance (CMR) including native T1 and global extracellular volume (ECV) to identify hypertrophic cardiomyopathy (HCM) patients at risk for sudden cardiac death (SCD) and to predict syncope or non-sustained ventricular tachycardia (VT). METHODS: A 1.5-T CMR was performed in 73 HCM patients and 16 controls. LGE size was quantified using the 3SD, 5SD and full width at half maximum (FWHM) method. T1 and ECV maps were generated by a 3(3)5 modified Look-Locker inversion recovery sequence. Receiver-operating curve analysis evaluated the best parameter to identify patients with increased SCD risk ≥4% and patients with syncope or non-sustained VT. RESULTS: Global ECV was the best predictor of SCD risk with an area under the curve (AUC) of 0.83. LGE size was significantly inferior to global ECV with an AUC of 0.68, 0.70 and 0.70 (all P < 0.05) for 3SD-, 5SD- and FWHM-LGE, respectively. Combined use of the SCD risk score and global ECV significantly improved the diagnostic accuracy to identify HCM patients with syncope or non-sustained VT. CONCLUSIONS: Combined use of the SCD risk score and global ECV has the potential to improve HCM patient selection, benefiting most implantable cardioverter defibrillators. KEY POINTS: • Global ECV identified the best HCM patients with increased SCD risk. • Global ECV performed equally well compared to a SCD risk score. • Combined use of the SCD risk score and global ECV improved test accuracy. • Combined use potentially improves selection of HCM patients for ICD implantation.

Serum Matrix Metalloproteinases as Quantitative Biomarkers for Myocardial Fibrosis and Sudden Cardiac Death Risk Stratification in Patients With Hypertrophic Cardiomyopathy.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is associated with an increased risk of sudden cardiac death due to ventricular tachycardia (VT), and myocardial fibrosis reflects an important risk factor. Several matrix metalloproteinases (MMPs) and procollagen N-terminal propeptides (PNPs) are involved in collagen turnover and discussed as fibrosis biomarkers. We aimed to identify biomarkers that correlate with myocardial fibrosis in late-gadolinium-enhancement cardiac magnetic resonance imaging (LGE-CMR) and/or cardiac events (syncope, VT) in HCM patients. METHODS AND RESULTS: In 54 HCM patients (age 55.9 ± 14.3 y, 50% female) fibrosis was quantified by LGE-CMR. Serum concentrations of MMP-1, -2, -3, -9, and tissue inhibitor of MMP (TIMP) 1 were analyzed by means of enzyme-linked immunosorbent assay and PINP, PIIINP, and type I collagen C-terminal telopeptide (ICTP) concentrations by radioimmunoassay. MMP-9 was associated with fibrosis in LGE-CMR (mean increase 0.66 g/unit MMP9 [95% confidence interval [CI] 0.50-0.82]; P < .001) and with cardiac events in women (odds ratio [OR] 1.07 [1.01-1.12], P = .01) but not in men. Increased MMP-2 levels in women were associated with lower fibrosis (0.05 [-0.09 to -0.01]; P = .015). MMP-3 levels were positively associated with cardiac events (OR 1.13 [1.05-1.22]; P = .001) independently from fibrosis and sex. No association was detected for MMP-1, TIMP-1, PNPs, and ICTP. CONCLUSIONS: These data suggest that MMP-9 is a useful biomarker for fibrosis and cardiac events in female HCM patients, whereas MMP-3 is associated with a higher event rate independent from fibrosis and sex.

[Reconstructive investigations and identification measures in unknown soldiers of the Second World War]. / Rekonstruktive Untersuchungen und Identifikationsmassnahmen bei unbekannten Soldaten aus dem Zweiten Weltkrieg.

The article reports on the exhumation and identification of unknown soldiers from the Second World War. With the help of medicolegal investigation and reconstruction methods an American pilot presumably murdered by a shot to the head (lynch law) and an interned Italian soldier could be identified after about 70 years and brought back home.

Cardiovascular magnetic resonance demonstrates reversible atrial dysfunction after catheter ablation of persistent atrial fibrillation.

INTRODUCTION: There is a paucity of data on atrial injury following ablation of persistent atrial fibrillation (AF). This study aimed at assessing reversibility of atrial dysfunction after successful persistent AF ablation using cardiovascular magnetic resonance (CMR). METHODS AND RESULTS: CMR was performed during sinus rhythm (SR) in 20 consecutive patients with persistent AF at baseline (BL) within 24 hours after ablation and after 6-month follow-up (FU). Catheter ablation included atrial substrate modification using the stepwise approach following pulmonary vein isolation (PVI) in order to attempt termination of persistent AF. Active left (LA) and right atrial (RA) function were quantified by calculating the active emptying fraction (AEF) from transvalvular flow profiles using velocity encoded (VENC) CMR. LA appendage (LAA) function was quantified by measurements of peak a-wave velocities from flow profiles perpendicular to the LAA orifice. Peri-atrial edema was assessed using black-blood T2 -weighted CMR. A significant improvement was found in LA-AEF from 18 (12-26)% at BL to 25 (22-35)% at FU (P = 0.0001). Furthermore, RA-AEF significantly increased from 31 (19-35)% at BL to 40 (35-51)% at FU (P < 0.0001). A significant improvement was also found for LAA a-wave velocities from 45 (31-65) cm/s at BL to 62 (49-75) cm/s at FU (P < 0.01). The area of peri-atrial edema on T2 -weighted CMR decreased from 1393 (1098-1797) mm(2) at BL to 24 (1-92) mm(2) at FU (P < 0.0001). CONCLUSION: CMR demonstrates reversibility of LA, LAA, and RA dysfunction associated with resorption of peri-atrial edema in patients with SR after persistent AF ablation.

4D blood flow visualization fusing 3D and 4D MRA image sequences.

PURPOSE: To present and evaluate the feasibility of a novel automatic method for generating 4D blood flow visualizations fusing high spatial resolution 3D and time-resolved (4D) magnetic resonance angiography (MRA) datasets. MATERIALS AND METHODS: In a first step, the cerebrovascular system is segmented in the 3D MRA dataset and a surface model is computed. The hemodynamic information is extracted from the 4D MRA dataset and transferred to the surface model using rigid registration where it can be visualized color-coded or dynamically over time. The presented method was evaluated using software phantoms and 20 clinical datasets from patients with an arteriovenous malformation. Clinical evaluation was performed by comparison of Spetzler-Martin scores determined from the 4D blood flow visualizations and corresponding digital subtraction angiographies. RESULTS: The performed software phantom validation showed that the presented method is capable of producing reliable visualization results for vessels with a minimum diameter of 2 mm for which a mean temporal error of 0.27 seconds was achieved. The clinical evaluation based on 20 datasets comparing the 4D visualization to DSA images revealed an excellent interrater reliability. CONCLUSION: The presented method enables an improved combined representation of blood flow and anatomy while reducing the time needed for clinical rating.