Identification score for robust and secure identification using ante- and post-mortem skull CT scans

--Manuscript Draft--

<table><tr><td>Manuscript Number:</td><td>IJLM-D-24-00068R3</td></tr><tr><td>Full Title:</td><td>Identification score for robust and secure identification using ante- and post-mortem skull CT scans</td></tr><tr><td>Article Type:</td><td>Original Article</td></tr><tr><td>Corresponding Author:</td><td>Joseph Benzakoun<br>GHU Paris: Groupe Hospitalier Universitaire Paris psychiatrie & neurosciences<br>FRANCE</td></tr><tr><td>Corresponding Author Secondary Information:</td><td></td></tr><tr><td>Corresponding Author's Institution:</td><td>GHU Paris: Groupe Hospitalier Universitaire Paris psychiatrie & neurosciences</td></tr><tr><td>Corresponding Author's Secondary Institution:</td><td></td></tr><tr><td>First Author:</td><td>Marie-Edith Richard, M.D.</td></tr><tr><td>First Author Secondary Information:</td><td></td></tr><tr><td>Order of Authors:</td><td>Marie-Edith Richard, M.D.<br>Corentin Provost<br>Tania Delabarde<br>Pauline Iorio<br>Yves Menu<br>Ghazi Hmeydia<br>Bertrand Ludes<br>Catherine Oppenheim<br>Joseph Benzakoun</td></tr><tr><td>Order of Authors Secondary Information:</td><td></td></tr><tr><td>Funding Information:</td><td></td></tr><tr><td>Abstract:</td><td>Due to their unique anatomy, paranasal sinuses have been used for comparative identification between post-mortem CT (PMCT) and ante-mortem CT (AMCT). However, data security issues arise when transferring raw AMCT images of a suspected identity. The aim of this study was to derive and validate an identification score based on CT slices extracted from successive CTs for the identification of subjects.<br>For derivation procedure, we included patients who underwent two successive AMCTs at ≥1-year interval (n=98), and 4 radiologists individually assessed similarity of prespecified CT slices (centered on ethmoid, frontal sinus and Left Semi-Circular Canal). Predictive values were calculated for all combinations of number of readers and slices, and the optimal compromise, termed IDScore, was selected.<br>For validation, we included PMCTs performed between 2018 and 2022 with available comparative head AMCTs (n=27). For each PMCT, 5 comparison procedures were performed: 1 concordant (with corresponding AMCT) and 4 discordant (with randomly selected AMCTs). Two radiologists evaluated similarity of ethmoid and frontal CT slices with a score ranging from -2 to +2. IDScore was defined as the sum of these slice scores, averaged between the two readers. In the 135 comparison procedures, IDScore using predetermined thresholds (positive identification for IDScore >+2, negative identification for IDScore <-1) allowed a perfect discrimination between identical subjects (Sensitivity=100%, Specificity=100%). IDScore could be used for</td></tr></table>
<figure><img src="image_1.png" /></figure>

# Identification score for robust and secure identification using ante- and post-mortem skull CT scans

Marie-Edith Richard (1,2), Corentin Provost (1,2), Tania Delabarde (3,4,5), Pauline Iorio (6,7), Yves Menu (6,7), Ghazi Hmeydia (1,2), Bertrand Ludes (3,4,5), Catherine Oppenheim (1,2), Joseph Benzakoun (1,2)

1. Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, F-75014 Paris, France

2. Service de Radiologie, GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne, F-75014 Paris, France

3. Institut Médico-Légal de Paris, Paris, France

4. Université Paris Cité, UMR8045 BABEL, CNRS, Paris, France

5. Pôle universitaire d'imagerie post-mortem, Université Paris Cité, Paris, France

6. Department of Radiology, Hôpital Saint-Antoine, APHP, Paris, France

7. Paris Sorbonne Université, Paris, France

Joseph Benzakoun
ORCID 0000-0002-0733-0104

j.benzakoun@ghu-paris.fr

Service de Radiologie
GHU Paris Psychiatrie et Neurosciences, Site Sainte-Anne, F-75014 Paris

1, Rue Cabanis
75014 Paris

<footnote>* corresponding author:</footnote>
**Abstract**

Due to their unique anatomy, paranasal sinuses have been used for comparative identification between post-mortem CT (PMCT) and ante-mortem CT (AMCT). However, data security issues arise when transferring raw AMCT images of a suspected identity. The aim of this study was to derive and validate an identification score based on CT slices extracted from successive CTs for the identification of subjects.

For derivation procedure, we included patients who underwent two successive AMCTs at ≥1-year interval (n=98), and 4 radiologists individually assessed similarity of prespecified CT slices (centered on ethmoid, frontal sinus and Left Semi-Circular Canal). Predictive values were calculated for all combinations of number of readers and slices, and the optimal compromise, termed IDScore, was selected.

For validation, we included PMCTs performed between 2018 and 2022 with available comparative head AMCTs (n=27). For each PMCT, 5 comparison procedures were performed: 1 concordant (with corresponding AMCT) and 4 discordant (with randomly selected AMCTs). Two radiologists evaluated similarity of ethmoid and frontal CT slices with a score ranging from -2 to +2. IDScore was defined as the sum of these slice scores, averaged between the two readers. In the 135 comparison procedures, IDScore using predetermined thresholds (positive identification for IDScore >+2, negative identification for IDScore <-1) allowed a perfect discrimination between identical subjects (Sensitivity=100%, Specificity=100%). IDScore could be used for remote identification of a subject with no need to access to the complete raw AMCT images, hence helping to overcome ethical and regulatory issues to access AMCT of a suspected identity.

**Keywords:** Computed tomography, Human identification, Sinus, Forensic radiology

**Trial registration:** F20220729161623 on Health Data Hub, registered on 29 July 2022

**Statements and Declarations**

* The authors did not receive support from any organization for the submitted work.

* The authors have no relevant financial or non-financial interests to disclose.

**Availability of data and material:** No

**Code availability:** Not Applicable
**Introduction**

Identification is a major issue in forensic context. International recommendations have been made by Interpol to positively match identification, in particular in disaster victim identification [1]. The criteria for positive identification are based on primary methods consisting of friction ridge analysis, odontology and DNA analysis and secondary methods mostly based on personal data and medical findings [2]. Forensic imaging, especially computed tomography is currently increasingly used [3]. It provides information on death causes [4, 5] but can also be used for identification, to get biological characteristics such as age, sex and stature [6, 7]. It also provides information on medical status, such as surgery history with orthopedic implants, fractures or metastases [6].

As imaging has an important value in medical fields, many people undergo imaging exams during their life [8]. This is a useful value for radiological identification consisting in ante- and post mortem imaging comparison, based on conventional radiographs, computed tomography or MRI images [9–11].

The paranasal sinuses consist of four distinct sinuses located within the skull: 1/ the frontal sinus, located behind the supraciliary arches within the frontal bone, 2/ the maxillary sinus located within the maxillary bone, 3/the ethmoid sinus located within the ethmoid bone and divided into anterior, middle, and posterior groups of ethmoid air cells, 4/ the sphenoid sinus, which can be restricted to the sphenoid body or can extend to the greater wings of the sphenoid [12].

Paranasal sinuses have already been used for identification as their anatomy vary for each individual [13]. Previous studies showed that a comparative approach between ante-mortem (AMCT) and post-mortem CT (PMCT) using predetermined reconstruction plans [14], is highly reliable for standardized plane reformation [15]. The performances of this reformative sections for identifying one subject among others remains to be evaluated. More recent approaches entail the use of 3D volume superimposition [16] to determine sinus uniqueness and its potential in personal identification.

However, few studies have proposed a precise comparison protocol and evaluated its reliability [17].
However, in clinical practice, the access to raw AMCT images of a suspected identity raises several ethical and regulatory issues: 1/ if the identity is unconfirmed and thus death of the subject to which belongs AMCT data is not confirmed, transferring images without patient's consent may be prohibited due to regulations such as General Data Protection Regulation [18] or Health Insurance Portability and Accountability Act [19] 2/ transferring CT data of a potentially living subject over any information system, even after anonymization, does not prevent re-identification [20] using for example Volume Rendering facial reconstruction techniques [21], and is consequently associated with a personal data safety threat. Other alternatives at preserving identity such as the use of defacing software do not seem possible in this application as they may not respect the morphology of paranasal sinuses used for the identification [22]. It is thus necessary to validate a method allowing to confirm a positive identification without access to the complete raw CT volume. Analysis of anonymized 2D slices seems to be a safer alternative since it cannot be used for facial recognition.

The aim of our study was to derive an identification score (IDScore) based on standardized 2D AMCT slices issued from two consecutive head CT and to validate this score in an independent cohort using AMCT and PMCT.

## Materials and Methods

The study consisted of two steps: the first step (derivation cohort) was aimed to find best slices for the definition of the IDScore. The second step (validation cohort), was to validate this score previously obtained on a population who underwent AMCT and PMCT.

## Population

### Derivation cohort

We retrospectively screened consecutive patients who underwent head CT in our hospital between April and November 2019 in our Picture Archiving and Communication System (PACS). Inclusion criteria were: age ≥ 18 years, availability of a previous CT separated by at least one year, exams covering frontal sinus, ethmoidal sinus and petrous bone. Exclusion criteria were: refusal to participate in study, presence of recognizable changes on the studied regions, partial skull exploration. All CTs
(early and late CT) were performed onto a single scanner (Revolution Evo, 64 detectors, GE Medical Systems) with various acquisition protocols.

## Validation cohort

All PMCT performed at the Medico-Legal Institute of Paris between 2018 and 2022 were retrospectively screened for inclusion. Inclusion criteria were: age ≥ 18 years (as paranasal sinuses are fully formed at adult age) and availability of head AMCT in the local database.

All PMCT were performed onto a single scanner (LightSpeed VCT, 64 detectors, GE Medical Systems). The head region was explored using the following parameters: 120 kV, adaptive mA, 0.625 slice thickness, bone reconstruction filter. AMCT were provided by different institutions, with various acquisition parameters, and included brain CT images and sinus cone-beam CTs.

## Image preprocessing

The procedure used to obtain 2D slices from CT was the same for the derivation cohort and the validation cohort (Fig.1) at the exception of Left Semi-Circular Canal (LSCC) slice plane which was not evaluated in the validation cohort.

All CTs were manually and independently processed. CTs were loaded in a double oblique multiplanar reconstruction tool (Carestream, Philips Healthcare) and oriented along the ethmoid roof plane. The Ethmoid slice was captured on a plane parallel to the ethmoid roof and located a few millimeters below it, as soon as partial volume effect was no more visible. The Frontal slice was captured on a plane parallel to the previous plane, at the location where the frontal sinus presented its largest width. The LSCC slice was captured on a plane tangent to both LSCCs. These slices were exported in JPEG format.

No registration between CTs (early and late CT for the derivation cohort and AMCT and PMCT for the validation cohort) was performed and slices reconstruction was made in separate sessions.
The procedure was repeated for both CTs (early and late CT for the derivation cohort and AMCT and PMCT for the validation cohort) by two distinct radiologists (JB for the derivation cohort, MER for the validation cohort).

Image pre-processing time was not individually assessed, but the mean time for preparation of two CT slices was estimated at 3 minutes by the radiologist who performed the procedure in the validation cohort.

## CScore determination in the derivation cohort

All slices were presented in random order to four radiologists with respectively 1, 4, 4, and 6 years of experience. Each slice of late CT was presented against 5 early CT slices corresponding to the same orientation plane (1 slice belonging to the same patient and 4 slices chosen randomly along other patients) and the early CT slices were displayed in random order. For each early CT slice, the radiologist had to decide whether the early CT slice was identical or not to the late CT slice with a certainty score (+2 if certain, +1 if probable, 0 if unsure, -2 if different). This labelling was based on a subjective evaluation of bone anatomy, sinus shape and size, and discarded mucosal and soft tissues features. This procedure was repeated for Ethmoid, Frontal and LSCC planes in a random order. For each combination of number of readers involved (1 to 4) and number of evaluated planes (1 to 3), a Certainty Score (CScore) was defined by summing the different components across evaluated planes and readers and dividing it by the number of readers. For each CScore, we computed the negative and positive predictive values for assuming subject identification across multiple procedures. Each procedure corresponded to a different combination of readers (up to 4 readers, maximum 15 possible combinations), and evaluated planes (up to 3 planes, maximum 7 possible combinations). For each CScore, only the minimum predictive values were kept across all procedures. The best CScore and the best planes for identification were chosen by balancing predictive value, discriminative values, and labelling simplicity. This score was labeled "IDScore" and evaluated subsequently on the validation cohort.
## IDScore evaluation in validation cohort

Each PMCT was used in 5 different comparison procedures: 1 procedure compared the PMCT to the corresponding AMCT (same identity, concordant procedures) and 4 procedures compared the PMCT to a randomly selected AMCT (different identity, discordant procedures). For all the procedures, the two slices (Ethmoid and Frontal) pertaining to both the PMCT and the AMCT were concomitantly presented to the reader. Two radiologists (CP and JB), with respectively 4 and 6 years of experience, and who did not participate in slice capture, evaluated the concordance between AMCT and PMCT. Each procedure was presented to the readers, blinded to the results of the identification, in a random order. Readers had to estimate the concordance between pairs using a subjective certainty score (+2 if certain, +1 if probable, 0 if unsure, -2 if different) for each slice (Ethmoid score and Frontal score). As for CScore evaluation, this labelling was based on a subjective evaluation of bone anatomy, sinus shape and size, and discarded mucosal and soft tissues features. The sum of Frontal and Ethmoid scores was computed for each reader. IDScore₁ corresponded to the total scoring performed by the first reader and IDScore₂ by the second reader. The mean value between IDScore₁ and IDScore₂ was then computed (IDScore) for each identification procedure, ranging between -4 and +4 (-4: the two readers are certain that frontal and ethmoidal pairs are not matching, +4: the two readers are certain that pairs are matching). All scoring procedure were timed.

## Non-perfect scores analysis

For all identification procedures where the IDScore was not perfect (>-4 or <+4), the two readers re-analysed in consensus the procedure, and categorized the cause for this non-perfect score within the following causes: slice positioning variation, AMCT with impaired quality, anatomical similarity.

## Statistical analysis

All statistical analysis was performed with R version 4.1.3 with library ggroc and irr.

## Derivation cohort

Interrater agreement for the assessment of each individual plane was assessed using Intraclass Coefficient Correlation (ICC) (two-way random effects, absolute agreement). The predictive power of
each CScore for determining if two patients were the same patient was evaluated by ROC curve analysis with Area Under the Curve (AUC) computation. Positive (PPV) and negative predictive values (NPV) were computed for each CScore thresholds. Discriminative value (DV) was determined as the difference between minimum and maximum CScore for which 100% NPV and 100% PPV were achieved, or 0 if these scores were never achieved altogether. In order to keep only the most unfavorable results, minimum AUC, NPV and PPV and DV across the different combinations of number of readers and number of planes were recorded for each CScore. As most AUC were equal to 1, confidence intervals are not presented since they would be equal to 1 and thus uninformative.

Detailed analysis of CScore was performed in the models where only 1 plane was evaluated and with the best performing two planes. The CScore with best balance between sensitivity, specificity, discriminative values, and performance complexity was defined as IDScore and evaluated on the validation cohort.

## Validation cohort

Interrater agreement for the assessment of each individual plane was assessed using ICC (two-way random effects, absolute agreement). Sensibility and specificity of IDScore for determining if AMCT and PMCT belonged to the same subject in each procedure were computed using previously derived thresholds (positive identification for IDScore > +2, negative identification for IDScore < -1). Scoring durations between positive and negative identification procedures were compared using Mann-Whitney-U test. Values are expressed as median and InterQuartile Range (IQR).

## Results

### Derivation cohort

#### Subjects

Among 127 patients evaluated, 3 refused to participate in study, 26 were excluded due to obvious identifying elements such as surgical material (n=15), craniectomy (n=10) and 1 was excluded due to partial exploration. Median age among 98 included patients was 61 years (IQR 47-73) and 48 (49%)
were female. Median delay between successive CTs was 2.7 years (IQR 1.5-5.19, range 1.0-11.2 years).

## Inter-reader agreement and CScore evaluation

Inter-reader agreement for individual plane labelling was very high using frontal plane (ICC=0.990 [95%CI: 0.998-0.991]), ethmoid plane (ICC=0.994 [95%CI: 0.994-0.995]) and LSCC plane (ICC=0.902 [95%CI: 0.888-0.915]).

CScore always allowed a perfect discrimination between identical and non-identical patients (AUC=1) when 3 slices were evaluated concurrently. When evaluating only 2 slices, at least 2 readers were required to achieve a perfect discrimination. Detailed CScore threshold analysis for each combination of number of readers and number of slices is given in Fig. 2. When the CScore was evaluated on 2 readers and 3 planes, the minimum DV was high (6), with a 100% NPV for all scores under 2 and a 100% PPV for all scores above -3. When the CScore was evaluated on 3 planes, 100% PPV (no false positive) was achieved with all scores ≥ -1, independently from the number of readers.

## Planes analysis

In the models with only 1 plane was used for CScore computation, Ethmoid and Frontal planes had the best performances for robustly identifying subjects with no false positive (Table 1). When evaluating CScore with these two planes and with two readers, the minimum DV was equal to 3, with a 100% NPV for all scores under 2 and a 100% PPV for all scores above -1.

## IDScore definition

Based on previous findings, IDScore was defined as the CScore with following characteristics: 2 readers and evaluation of the following 2 planes: Ethmoid and Frontal, since their association had a good discriminative performance (DV=3). The following thresholds were chosen: no concordance for IDScore < -1, concordance for IDScore > +2 and indeterminate result for scores between -1 and +2.
# Validation cohort

## Subjects

Among 3012 decedents screened for inclusion, 47 had a previous radiological examination available for comparison, and 27 had a head CT with raw images available were included in the study. Median delay between AMCT and PMCT was 3.1 years (IQR: 0.8-4.7 years). IDScore was evaluated in 135 identification procedures (27 positive identification procedures and 108 negative identification procedures).

## Inter-reader agreement and IDScore evaluation

Inter-reader agreement for individual plane labelling was very high using frontal plane (ICC=0.966 [95%CI: 0.952-0.976]) and ethmoid plane (ICC=0.984 [95%CI: 0.978-0.989]).

IDScore allowed a perfect discrimination between identical subjects (AUC=1, Sensitivity=100%, Specificity=100%). Among 27 positive identification procedures, 14 (52%) had an IDScore = +4 and 13 (48%) had an IDScore = +3 or +3.5. Among 108 negative identification procedures, 104 (96%) had an IDScore = -4 and 4 (4%) had an IDScore = -3. No IDScore between -1 and +2 was measured.

Detailed score per reader (IDScore₁ and IDScore₂) is shown in Table 2. IDScore₁ and IDScore₂ were all <-1 or >+2, with 100% sensitivity and 100% specificity for positive identification.

## Non-perfect scores analysis

For all negative identification procedures where the IDScore was > -4 and < -1 (n=4), the origin of non-perfect scoring was attributed to an anatomical similarity between small-sized frontal sinus. In all these cases, ethmoid comparison allowed to confirm a negative identification (Fig. 3).

For positive identification procedures where the IDScore was > 2 and < 4 (n=13), the origin of non-perfect scoring was attributed to impaired AMCT quality in 2 cases (15%), slice positioning variation on Ethmoid slice in 8 cases (62%) (Fig. 4) and slice positioning variation on Frontal slice in 3 cases (23%).
## Scoring duration analysis

Positive identification procedures (n=27) took a longer time for the readers to validate as compared to negative identification procedures (n=108) (respectively 17 seconds, IQR 11.2-26.5 vs. 9.5 seconds, IQR 7.5-13.6, p<0.0001). Procedures with non-perfect IDScores (>4 and <4) (n=17) took a longer time for the readers to validate as compared to procedures with perfect IDScores (n=118) (respectively 28.5 seconds, IQR 18.5-36.5 vs. 9.5 seconds, IQR 7.5-13.5, p<0.0001).

## Discussion

This study demonstrates the possibility to use a score based on two slices centred on ethmoid and frontal sinuses from AMCT and PMCT for positive identification with 100% sensitivity and 100% specificity.

This is the first study developing and validating a reliable identification score based on two selective CT slices from AMCT and PMCT data, with a standardized procedure that can be used in routine clinic for personal identification. Our methodology for developing a reliable identification score on AMCT and PMCT data is further strengthened by the fact that we derived the IDScore on an external cohort of living subjects prior to validation, which adds to the robustness of the approach.

Previous studies have already shown the interest to use paranasal sinuses for identification. Mostly used frontal sinuses by demonstrating its uniqueness from X-Ray, 2D or 3D reconstruction from CT. Some studies used the sphenoid sinuses and maxillary sinuses [14, 23, 24]. Ruder et al. [14] showed the possibility to identify subjects based on 3 axial slices on paranasal sinuses from AMCT to 3D PMCT data with high sensitivity (84%) and specificity (100%). Their study evaluated the possibility to perform an identification procedure during a fictitious mass disaster scenario: readers had access to all PMCT and had to match PMCT with AMCT slices. This differs from our study's clinical setup, where we validated a score based on only two standardized 2D CT slices. Our proposed IDScore allows for positive identification using only these two slices on AMCT and PMCT, ensuring patient confidentiality as it is as of today impossible to identify a patient based on only two slices without additional information.
Our findings are in agreement with previous studies by Auffret et al. [23] and Deloire et al. [24] which used the sphenoid sinus for identification with a 100% accuracy. Our analysis of individual sub-scores (IDScore₁ and IDScore₂) supports the idea that the assessment by a single expert radiologist may be adequate for most cases, as in previous studies.

The rapidity of images analysis (inferior to one minute) comforts the feasibility of the proposed IDScore in routine clinic. Non-perfect scores took longer, reflecting a greater complexity in analysing the sinuses and the need for a more detailed assessment of the ethmoid labyrinth. However, other anatomical structures present in the different slices can facilitate positive identification. For instance, the internal carotid arteries can be visualized on the ethmoid slices, and any calcifications may aid in matching the slices. This could be the case in our study, as median delay between AMCT and PMCT was short (3.1 years), leading to few modifications in degenerative or senescence changes.

This short time of analysis has to be balanced with the longer time of image pre-processing. Indeed, the time for slice extraction was estimated at 3 minutes, which remains compatible with a clinical practice environment.

In our opinion, identification using this 2-slice approach seems sufficient to lift medical confidentiality and allow data transfer, but does not replace direct volume-to-volume confrontation for formal identification. From this study, we thus suggest a workflow based on this score for the remote identification of a subject with high robustness and regulatory-compatible image transfer (Fig. 5). The 2D slices can be first anonymously transferred between ante and post-mortem radiologists, thus respecting medical confidentiality and greatly reducing the risk of re-identification. In case of positive IDScore, the anonymity can then be lifted and raw images transferred over a secure channel. In case of negative or uncertain IDScore, alternative identification methods should be proposed.

This method could be used when other identification methods are unavailable, especially if primary identifiers (friction ridge analysis, odontology and DNA analysis) are unavailable. Indeed, secondary identification methods such as methods based on radiological exams are generally considered as a
second-line tool [1]. In disaster victim identification, this approach could be valuable provided that widespread access to AMCT data can be guaranteed within a short timeframe.

## Limits

The IDScore is based on two slices coming from a standardized reconstruction based on MPR, sometimes leading to co-registration errors. Previous studies have shown the reliability of using standardized protocols with good inter-rater agreement even with different professional backgrounds [15, 25]. Brun et al. developed a standardized image for personal identification with good inter and intra reliability between readers from different professional backgrounds but they did not assess the accuracy of this method for personal identification [25]. In our study, one radiologist made all the reconstructions from AMCT and PMCT, but some reconstructions showed some slice positioning variation explaining some non-perfect scores, especially on ethmoid sinus.

The delay between AMCT and PMCT was relatively short in our study, possibly leading to bias as few changes may occur during this time-lapse. Indeed, our results may not be applicable in young subjects, where paranasal sinuses are not fully formed, and may be restricted in case of intercurrent adult-life modifications such as fractures or surgery. To thoroughly assess the robustness and boundaries of the IDScore, future research should encompass a wider range of AMCT and PMCT sources with extended intervals between scans. This would allow to evaluate the impact of intercurrent events such as fractures or sinus changes due to sinus development, and their impact in the identification process.

Validation of the IDScore was made on PMCT. Severe degradation on dead subjects due to post-mortem changes could lead to non-perfect IDScore. In our validation set, we were able to correctly confirm or infirm identification in all cases. In other cases, secure online meeting between radiologists could help slice-to-slice comparison. In the end, if the uncertainty remains, other identification characteristics on CT need to be searched. Non-perfect IDScore can also occur when AMCT has impaired quality. This can happen when available AMCT consists only of thick slices reconstruction with partial volume effect.
The proposed IDScore requires two radiologists to confirm or infirm identification. This is entirely compatible with a common clinical situation where subject identity is already suspected based on contextual elements. Indeed, the pre-test probability in our study is high (1 positive identification procedure for 4 negative procedures, i.e. 20% pre-test probability) but may not reflect other situations where the identity is completely unknown. Moreover, using a subjective scoring system may be prone to confirmation bias if two random anatomies present similarities. As such, our method is impractical for clinical situations where pre-test probability is low, i.e. there is no suspected identity. Previous authors have proposed algorithms more adapted to this low-probability situation, using algorithms such as Iterative Cloud Point algorithm [26] or Deep-Learning approaches to assess the similarity between sphenoid sinus morphology [27]. The latter approach objectively assesses the similarity between sphenoid sinus morphologies by converting geometrical information into numerical feature vectors, which are then used to compare AMCT and PMCT data. Additionally, the use of numerical feature vectors facilitates long-term storage and improves patient data safety, offering practical advantages in maintaining confidentiality while supporting robust identification. This complementary approach could enhance the reliability of subject identification, particularly in complex cases where subjective assessment alone using the IDScore may be insufficient. The IDScore is indeed inherently subjective, as it is based on a visual radiological comparison of CT slices, and although this subjective approach seems realistic for clinical situations where the pre-test probability is high, automated comparison techniques could enhance the reliability of subject identification by reducing subjectivity.

This complementary approach would not only improve accuracy but also increase applicability in low-probability scenarios where numerous comparisons are required.

The IDScore validation was performed on one institution in a given time period, which may limit its generalizability. Replication studies on other institutions and in larger cohorts with more diverse populations are however needed to externally validate the IDScore and confirm its generalizability in clinic routine across different geographical regions. Expanding the number of subjects and including subjects from various forensic institutes in a multicentric, international study would increase subjects' diversity and help to verify the high intra-observer reliability across different radiological teams. Such
multi-center studies would also evaluate the IDScore's performance under varied imaging protocols,
thereby reinforcing its utility and reliability in routine clinical practice.

Conclusion

The increased use of PMCT in recent years showed its significance for identification in forensic contexts, notably when comparing with AMCT. However, the use of AMCT and PMCT for personal identification raises security and ethical considerations regarding CT data transfer of subjects whose legal death status is not yet ascertained.

This study validates an identification score based on two slices of the ethmoid and frontal sinuses,
derived from AMCT and PMCT scans and selected with a standardized procedure. The IDScore
demonstrated a perfect sensitivity and specificity for positive identification by two independent
readers. The use of a limited number of slices prevents ethical and regulatory issues, as the transfer of
complete raw AMCT images can then be made only after formal identification. The proposed IDScore
not only ensures accuracy for personal identification but also addresses ethical considerations, making
it a viable option for routine clinical use. External validation and replication of our findings are
necessary in order to confirm the robustness and generalizability of the IDScore in diverse clinical
settings. Once validated on other populations, this method could be combined with the identification
methods currently used in clinical practice to assist forensic experts in establishing a definitive
identification.
Table

<table><caption>Table 1: Minimum positive predictive value (PPV) for CScores computed for each plane</caption><thead><tr><th>Number of readers</th><th>Minimum PPV for Ethmoid plane</th><th>Minimum PPV for Frontal plane</th><th>Minimum PPV for LSCC plane</th></tr></thead><tbody><tr><td>1</td><td>1</td><td>0.99</td><td>0.89</td></tr><tr><td>2</td><td>1</td><td>1</td><td>0.98</td></tr><tr><td>3</td><td>1</td><td>1</td><td>1</td></tr><tr><td>4</td><td>1</td><td>1</td><td>1</td></tr></tbody></table>

Predictive Positive Values (PPV) for positive identification using CScore measured on each individual plane were computed across for all combinations of 4 readers. Minimum PPV are presented for category of readers number.

<table><caption>Table 2: Detailed components of the IDScore per reader</caption><thead><tr><th rowspan="2"></th><th colspan="3">IDScore<sub>1</sub></th><th colspan="4">IDScore<sub>2</sub></th><th colspan="5">IDScore</th></tr><tr><th>-4</th><th>+3</th><th>+4</th><th>-4</th><th>-2</th><th>+3</th><th>+4</th><th>-4</th><th>-3</th><th>+3</th><th>+3.5</th><th>+4</th></tr></thead><tbody><tr><th>Score</th><td>-4</td><td>+3</td><td>+4</td><td>-4</td><td>-2</td><td>+3</td><td>+4</td><td>-4</td><td>-3</td><td>+3</td><td>+3.5</td><td>+4</td></tr><tr><th>Negative identification</th><td>108</td><td>0</td><td>0</td><td>104</td><td>4</td><td>0</td><td>0</td><td>104</td><td>4</td><td>0</td><td>0</td><td>0</td></tr><tr><th>Positive identification</th><td>0</td><td>6</td><td>21</td><td>0</td><td>0</td><td>11</td><td>16</td><td>0</td><td>0</td><td>4</td><td>9</td><td>14</td></tr></tbody></table>

Results are given as a number of identification procedures (total number = 135).

IDScore<sub>1</sub> and IDScore<sub>2</sub> correspond respectively to evaluations from readers 1 and 2, computed using the sum of Frontal and Ethmoid scores. IDScore is the mean value between IDScore<sub>1</sub> and IDScore<sub>2</sub>.
Figures

<figure><img src="image_2.png" /><figcaption>**Figure 1: Procedure for slices positioning**</figcaption></figure>

All slices were positioned using double obliquity reformatting, using as reference the ethmoid roof on sagittal slice (a), and the largest width of frontal sinus on coronal slice (b). The Ethmoid slice (d) was captured 1-2 mm below the ethmoid roof (white line in a), and the Frontal slice (e) at the location where the frontal sinus was the largest. The LSCC slice (f) was captured on a plane tangent to both LSCCs (white line in c). The obtained slices d, e and f were used in the study.
<figure><img src="image_3.png" /><figcaption>**Figure 2:** Predictive values of CScores according to number of planes and readers</figcaption></figure>

For each CScore, defined by a combination of the number of planes evaluated and the readers involved, we computed the negative and positive predictive values for assuming positive identification across multiple procedures. Each procedure corresponded to a different combination of plane types (frontal, ethmoid, and/or LSCC) and readers (1, 2, 3, and/or 4). From these computations, only the minimal predictive values across all procedures were retained to generate this graph.
<figure><img src="image_4.png" /><figcaption>**Figure 3:** Example of negative identification with anatomical similarity between frontal sinuses</figcaption></figure>

Frontal slices (a, b) and Ethmoid slices (c, d) of an AMCT (a, c) and a PMCT (b, d) are presented.

Note the anatomical proximity between Frontal features (arrow in b). Obvious differences between ethmoid slices (overall shape, large left posterior cell on c) were used for negative identification.

IDScore₁ was -4, IDScore₂ was -2 and IDScore was -3.
<figure><img src="image_5.png" /><figcaption>**Figure 4: Example of positive identification with slice positioning variation**</figcaption></figure>

Frontal slices (a, b) and Ethmoid slices (c, d) of an AMCT (a, c) and a PMCT (b, d) are presented.

Note the perfect concordance between Frontal slices for septa position, but not for septa length. The posterior ethmoid cells seem much larger on c (white arrow) as compared to d due to registration error.

However, most ethmoidal features are easily recognized in the anterior ethmoid (arrow in d). IDScore1 was 3, IDScore2 was 4 and IDScore was 3.5. The slice positioning was not perfect in this example, however this underlines that the IDScore should not be used as a definitive identification method, but rather a temporary identification method in a context of high-probability identity check, enabling data transfer and definitive identification by standard volume coregistration.
<figure><img src="image_6.png" /><figcaption>**Figure 5: Proposed workflow for assessing IDScore with two radiologists**</figcaption></figure>

Anonymized Ethmoid and Frontal slices are transferred between two radiologists for computing IDScore₁ and IDScore₂. The IDScore result is then used for lifting anonymity if > 2. A secure online meeting between radiologists for slice-to-slice comparison is proposed in the cases where IDScore result is uncertain.
# Declarations

## Consent to participate

- Consent to Participate was searched with information letter to every patient screened for the derivation cohort.

- Consent to Participate could not be obtained after death for the participants used for the validation cohort.

- In accordance with French legislation, the absence of written opposition during subjects' lifetime was verified in medical records.

## Consent to publish

- No identifying information is present in the article.

## Ethics

- This study was performed in line with the principles of the Declaration of Helsinki.

- Ethical approval was waived by the local review board of GHU Paris in view of the retrospective nature of the study and all the procedures being performed were part of the routine care.

- The study was conducted under the Reference Methodology MR-004 for data protection relating to the processing of retrospective and prospective personal data implemented in the framework of research not involving the human person, and approved by our local committee under the internal registration number D22-R005. All living subjects were informed in writing and offered the possibility to withdraw from study.

- **Trial registration number:** F20220729161623 on Health Data Hub, registered on 29 July 2022

**Code availability:** Not Applicable
## Authors contributions:

All authors contributed to the study conception and design. Material preparation, data collection was performed by ME Richard and J Benzakoun. The first draft of the manuscript was written by ME Richard and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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<figure><img src="image_7.png" /></figure>
<figure><img src="image_8.png" /><figcaption>Figure2</figcaption></figure>

Minimal predictive values

Negative Predictive Value

Positive Predictive Value
<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>
<figure><img src="image_13.png" /></figure>

IDScore_Fig4.tif
<figure><img src="image_14.png" /></figure>