# Quantitative and qualitative optimisation of dosimetry in computed tomography explorations of the temporal bone using two iterative reconstruction algorithms

Olivier Legeas, David Bourhis, Marc Garetier, Adele Pennaneach, Philippe

Meriot, Julien Ognard, Douraied Ben Salem

► To cite this version:

Olivier Legeas, David Bourhis, Marc Garetier, Adele Pennaneach, Philippe Meriot, et al. Quantitative and qualitative optimisation of dosimetry in computed tomography explorations of the temporal bone using two iterative reconstruction algorithms. Neuroscience Informatics, 2021, 1 (4), pp.100017. 10.1016/j.neuri.2021.100017. hal-05228596

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Original article

# Quantitative and qualitative optimisation of dosimetry in computed tomography explorations of the temporal bone using two iterative reconstruction algorithms ☆

<figure><img src="image_2.png" /></figure>

Olivier Legeas<sup>a</sup>, David Bourhis<sup>b</sup>, Marc Garetier<sup>c</sup>, Adele Pennaneach<sup>d</sup>, Philippe Meriot<sup>a</sup>, Julien Ognard<sup>a,e,f,\*</sup>, Douraied Ben Salem<sup>a,e,f</sup>

## ARTICLE INFO

**Article history:**

Received 26 June 2021

Accepted 14 October 2021

**Keywords:**

Iterative reconstruction

Dosimetry

ASiR

SAFIRE

Temporal bone

## ABSTRACT

**Purpose:** Iterative reconstruction (IR) has recently demonstrated its ability to reduce the dose of X-rays used in the exploration of several anatomical regions. However, there is no study involving a qualitative and quantitative comparison of the various IRs available for exploring the temporal bone. The aim of this study is to analyse two IR algorithms (ASiR®, statistical iterative reconstruction and SAFIRE®, model based iterative reconstruction). **Methods:** Using a Catphan® phantom, we studied the quantitative relationship of the contrast on noise/CDTI<sub>vol</sub>/IR. We verified the absence of a reduction in spatial resolution during the use of IRs by measuring MTF<sub>50%</sub>. Based on these data we acquired a series of images on an anthropomorphic phantom with an authentic human temporal bone for each level of iteration; the purpose of this was to evaluate them qualitatively. The CDTI<sub>vol</sub> of temporal bone IRs was adjusted based on the measurements taken with the Catphan phantom in order to acquire images with a constant CNR. **Results:** The resulting measurements demonstrated a reduction in noise without a loss of spatial resolution in the two manufacturers' systems. The quantitative study by four radiologists allowed us to optimise CDTI<sub>vol</sub> and the level of iteration. This optimisation made it possible to reduce the dose in the two manufacturers' systems, and the most effective of these algorithms enabled a reduction in CDTI<sub>vol</sub> of 64.6% during explorations of the temporal bone. **Conclusion:** The two analysed iterative reconstruction algorithms responded well to the objectives of dose reduction in the exploration of the temporal bone.

© 2021 The Author(s). Published by Elsevier Masson SAS. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

## 1. Introduction

With the constant increase in the use of scans in temporal bone diseases, exposure to X-rays has become a major concern in recent years [1]. This is because this anatomical zone comprises a compact bone, with fine structures requiring high constants. Repetition of these examinations is not without risk for the development of radiation-induced cancer [2] nor without risk to the neighbouring structures, particularly the crystallin [3]. Reducing the dosimetry

simultaneously increases the noise in the image. One of the strategies adopted to reduce exposure to X-rays is to develop more effective algorithms. Filtered back-projection (FBP) was the first reconstruction technique to be developed; it has the advantage of being rapid in its calculations, but simultaneously involves substantial noise when the acquisition constants are reduced. In 2008 a new type of reconstruction was made available, making it possible to compensate for noise in a more effective way. This improved compensation enables the constants to be further reduced [2]. These algorithms are based on iterative methods that involve comparing information from raw data or from the image domain, with different denoising and image-improving methods [4]. Each manufacturer markets its own Iterative Reconstruction (IR) algorithms: adaptive statistical iterative reconstruction ASiR (General Electric (GE)), and model based iterative reconstruction (MBIR) SAFIRE (Siemens). With an initial FBP reconstruction, ASIR reduces

<footnote><sup>a</sup> Imaging Unit, University Hospital of Brest, Bd Tanguy Prigent, 29609 Brest Cedex, France</footnote>

<footnote><sup>b</sup> Radiation Physics and Protection Unit, University Hospital of Brest, Bd Tanguy Prigent, 29609 Brest Cedex, France</footnote>

<footnote><sup>c</sup> Imaging Unit, Military Teaching Hospital of Brest, Rue Colonel Fonferrier, 29240 Brest Cedex, France</footnote>

<footnote><sup>d</sup> Radiology Unit, Cornouaille Hospital of Quimper, 14Bis Avenue Yves Thépot, 29107 Quimper cedex, France</footnote>

<footnote><sup>e</sup> Laboratoire de traitement de l'information médicale—LaTIM (Inserm UMR 1101), 22, avenue Camille Desmoulins, CS 93837-29238 Brest Cedex 3, France</footnote>

<footnote><sup>f</sup> Clinical Forensic Medicine and Pathology, University Hospital of Brest, Bd Tanguy Prigent, 29609 Brest Cedex, France</footnote>

<footnote>☆ This article has been handled by another Editor, Jean-Christophe Gentric during the whole editorial process.</footnote>

<footnote>\* Corresponding author at: Medical Imaging Service, University Hospital of Cavale Blanche, Bd Tanguy Prigent, 29609 Brest Cedex, France.</footnote>

<footnote>E-mail address: julien.ognard@chu-brest.fr (J. Ognard).</footnote>
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Contrast Noise Ratio (CNR) and Relative Modulation Transfer Function (MTF) calculation. Image A: CNR calculation on the CTP 404 module. The ratio was calculated between the Teflon disc (arrow, 990 Hounsfield Units (HU)) and the base of the Catphan® at 100 HU; Image B: MTF calculation. ROI was automatically placed on each resolution pattern. Standard deviation was measured in the pattern and in the background area. For each spatial frequency (pattern) MTF was therefore calculated; Image C: MTF Polynomial fitting curve. This function was calculated to obtain a more accurate estimation of 50% of the MTF.</figcaption></figure>

<figure><img src="image_4.png" /></figure>

noise without impact on spatial nor contrast resolution through an analysis of detector response and of the statistical behaviour of CT measurements. Another algorithm, termed model-based iterative reconstruction (MBIR), which requires more reconstruction time, uses detailed models of radiation characteristics and of CT equipment. This last one uses backward and forward projections to match the reconstructed image to the acquired data iteratively according to a statistical metric [5].

Although several studies have examined the performance of these various IR algorithms [6–8], very few have evaluated and compared them using a method that is both quantitative and qualitative [9,10]. This study could also be presented as a methodology for maximising patient dose reduction and maintaining image quality using iterative reconstruction [11] for temporal bone CT examination, which requires high resolution, fewer artifacts, and lower noise levels at a thin-slice thickness of 1.0 mm [12]. In order to maximise the performance of each IR algorithm in explorations of the temporal bone, we have conducted a quantitative and qualitative comparison of the two IR algorithms: SAFIRE and ASiR.

## 2. Materials and methods

Our study involved two phases. The first phase was conducted on a phantom with scan image quality. In this phase we measured the evolution of the Contrast-to-Noise Ratio (CNR) for each IR algorithm depending on the Computed Tomography Dose Index ($CDT_{vol}$). The purpose of these measurements was to evaluate the physical denoising capacity of each IR and to establish acquisition parameters for the second phase involving the anthropomorphic phantom. The study on the anthropomorphic phantom consisted of an evaluation by four radiologists of the image quality of each manufacturer's system at each iteration degree.

### 2.1. Iterative reconstructions

All the iterative reconstructions work on the principle of comparison loops [4]. The first step of this loop involves making a volume estimation of the object in the form of an estimated sinogram. This sinogram is then compared with the raw data sinogram via:

- the use of statistical models for IRs with a statistical model

- the use of geometric and physical models modelling X-ray beams at different degrees for MBIRs (Model-Based Iterative Reconstructions)

This comparison produces a correction factor, which enables a new volume estimation of the object to be made. After several iteration loops the estimation stabilises and forms a final image. This

IR loops can intervene in the raw data domain or the image domain. The raw data domain corresponds to data from the sinogram before back-projection, and the image domain corresponds to the image after back-projection. Each manufacturer has developed its own IR algorithm comprising specific features as well as a precise functioning that is not disclosed [13]. For this study we have chosen to evaluate the SAFIRE and ASiR algorithms since they are commercially available.

### 2.2. Adaptive statistical iterative reconstruction, ASiR

In 2008 GE produced the first iterative reconstruction algorithm called ASiR. The FBP reconstruction data are used for an initial estimation of the image. Statistical regularisation methods are used in the raw data domain in order to reduce noise and preserve the contours of the image. When the reconstruction is complete, the resulting image is a weighting between FBP and ASiR. For example, 30% ASiR is a reconstruction combining 30% of the iterative image and 70% of FBP [14,15].

### 2.3. Sinogram affirmed iterative reconstruction, SAFIRE

Siemens began marketing SAFIRE in 2010. Corrections are made in the raw data domain and the image domain. This makes it possible to reduce artefacts, preserve contours and reduce image noise. Since it uses a geometric model, SAFIRE is considered an MBIR algorithm [16]. SAFIRE has five levels of “strenght” in the iterative reconstruction process, ranging from SAFIRE 1 for the weakest to SAFIRE 5 for the strongest.

### 2.4. Scanners

We used two scanners of the same generation, installed in three different hospitals: a Somatom Definition AS scanner (64 slice) (Siemens Healthcare, Forchheim, Germany) with a Sinogram Affirmed Iterative Reconstruction (SAFIRE) IR system, and a CT750 HD scanner (64 slices) (GE Healthcare, Milwaukee, MI, USA) with an Adaptive Statistical Iterative Reconstruction (ASiR) IR system.

### 2.5. Phantoms

We used a Catphan® 504 image quality phantom (The Phantom Laboratory, NY, USA). This phantom was used in the first part of the study and measured the following quantitative parameters: Contrast-to-Noise Ratio (CNR), Relative Modulation Transfer Function (MTF) corresponding to spatial resolution.

CNR was measured on the CTP 404 module (Fig. 1A). MTF was measured on the high-contrast resolution CTP 528a module with 21 groups of pairs of lines in decreasing size.
<table><caption>**Table 1**
Acquisition parameters for GE's CT750 HD and Siemens's Somatom Definition AS collimation and thickness in mm, CDTI<sub>vol</sub> in mGy.</caption><thead><tr><th>Scanner</th><th>Pitch</th><th>Collimation</th><th>Thickness</th><th>Filter</th><th>Rotation time</th><th>KiloVoltage</th><th>CDTI<sub>vol</sub></th><th>Matrix</th></tr></thead><tbody><tr><td>CT750 HD</td><td>0.531</td><td>16 × 0.625</td><td>0.625</td><td>HD ultra IQ enhance</td><td>1 s</td><td>140</td><td>17-113</td><td>512 × 512</td></tr><tr><td>Somatom definition AS</td><td>0.55</td><td>16 × 0.6</td><td>0.6</td><td>U80/V80</td><td>1 s</td><td>140</td><td>17-113</td><td>512 × 512</td></tr></tbody></table>

We then used a Rando® anthropomorphic phantom (Alderson Research Laboratories Inc, Stamford, CT, USA) for a qualitative evaluation of the image and to measure the control CNR. This phantom is made of urethane plastic (which mimics tissue) and a complete human skeleton with a preserved temporal bone (except for the ossicles).

## 2.6. Acquisition parameters (Table 1)

The imaging parameters were based on each manufacturer's "temporal bone" protocol. Adjustments were necessary to produce images that were comparable between manufacturers. The selected parameters were slice thickness as close as possible to 0.6 mm, kilovoltage of 140 kV, a 220 mm field of view for the Catphan® and 150 for the anthropomorphic phantom, a matrix of 512 × 512, and a temporal bone reconstruction filter recommended by the supplier. Tube current was adjusted so that each CTDI<sub>vol</sub> was identical. Intensity modulation was deactivated to enable a comparison exclusively of the IR algorithms. We studied the five SAFIRE degrees and we decided to conduct five series of ASiR iterative resolutions, with a series every 20% of ASIR/FBP blending.

## 2.7. Image quality and dosimetry parameters

### 2.7.1. CNR on the Catphan®

CNR evaluates image contrast over noise and was calculated as follows:

$$CNR = \frac{\Delta HU}{\sigma}$$

CNR evaluates the detectability of an object in an image and is a metric linking contrast and noise. The ratio was calculated between the Teflon disc (990 Hounsfield Units (HU)) and the base of the Catphan® at 100 HU. The selection of these discs enabled a difference of 890 HU (CNR890), corresponding to a high contrast found in the clinical exploration of the ear (Fig. 1A). The CNR was calculated automatically using the Image J® free software (V 1.48 National Institutes of Health, USA).

### 2.7.2. CNR on an anthropomorphic phantom

Using an anthropomorphic phantom, a region of interest (ROI) of 8.51 cm² was placed on the posterior cranial fossa, and a second ROI of 0.26 cm² was placed on the bone plate of the cerebellum. Each ROI was placed identically thanks to propagation in all series (software: Syngovia® version, Siemens AG, Germany).

### 2.7.3. High-contrast spatial resolution

Spatial resolution corresponds to a scanner's ability to identify small high-contrast objects, which is important in the exploration of a dense bone structure made up of multiple millimetric structures such as the temporal bone. MTF is a parameter that makes it possible to evaluate both the notion of spatial resolution and the contrast. It can be defined as the ratio of the image contrast on the object contrast at the desired spatial frequency. MTF was measured on the 528a Catphan® module using the Droege and Morin method [17]. For this method we measured increasingly weaker spatial frequencies thanks to highly contrasted patterns placed in a cyclical fashion in each module. The MTF corresponding to each

module, and therefore to a given spatial frequency, was calculated as follows:

$$MTF = \frac{contrast_{image}}{contrast_{object}}$$

The spatial frequency corresponding to MTF at 50% is a common means of expressing spatial resolution [8,18,19], and it is less exposed to noise than MTF at 10% (ref). MTF was calculated automatically using the Image J® free software (V 1.48 National Institutes of Health, USA) using a ROI automatically placed on each resolution pattern. Standard deviation was measured in the pattern and in the background area. For each spatial frequency (pattern *i*) MTF was therefore calculated as (Fig. 1B):

$$MTF(i) = \frac{\pi \sqrt{\sigma_{(i)}^2 - \sigma_{(background)}^2}}{\sqrt{2}}$$

For these results, a polynomial fitting curve was calculated (Fig. 1C) to obtain 50% of the MTF.

### 2.7.4. CDTI<sub>vol</sub>

CDTI<sub>vol</sub> is the reference dosimetric indicator in computed tomography. It corresponds to the dose in mGy equivalent to one slice for a set of given acquisition parameters [20]. CTDI was given for all possible acquisition parameters for a 16 cm diameter phantom. CTDI is measured by manufacturer for all possible parameter combinations, and controlled for standardised protocols once a year, according to French legislation. It therefore did not correspond to the dose administered to the patient but to the dose measured on the phantom. The method used to measure this dosimetry indicator is identical for all manufacturers, and thus enabled an excellent dosimetric comparison between the protocols or scanners. The CTDI<sub>100</sub> was obtained by measuring an ionisation chamber of 10 cm of the dose administered for a tube rotation. In order to take into account the inhomogeneity of the ionisation chamber, the CTDI<sub>w</sub> was weighted between the centre and the periphery of the phantom. In order to take into account the spiraled acquisition, the CTDI<sub>w</sub> was divided by the pitch and became CDTI<sub>vol</sub>: CTDI<sub>w</sub>.

## 2.8. Methods

Our method was original in that it studied and compared SAFIRE and ASiR IRs of the temporal bone using an approach that was both quantitative and qualitative.

Our objective was to use the ability of IR to produce images with less noise than FBP [19] to compensate for the increase in noise when reducing constants [18]. Since this capacity is specific to each algorithm, we determined the link between the dose, degree of iteration and CNR in the quantitative step. This step aimed to define the optimal parameters enabling IRs to maintain the image quality of MTF. These parameters were then used on the anthropomorphic phantom for a qualitative study by four radiologists.

## 2.9. Quantitative measurements

The first step was performed on a Catphan phantom. The goal was here to establish the relationship between detectability (measured by CNR890), dose (expressed by CTDIvol) and IR strength for
both manufacturer's. On the first system, we used a standard temporal bone FBP CT protocol and we stored CTDIvol. Then we manually lowered exposure 9 times. All acquisitions were reconstructed with FBP and 5 IR strength. On obtained datasets we stored CTDI and measured CNR890 and MTF50. Then, on the second system we manually set exposures so that CTDI were equal to those obtained on the first system. We also performed FBP and 5 IR strength reconstructions to measure CNR and MTF50. For each system we obtained 6 CNR = f(CTDI) functions (adjusted with a 2nd order polynomial function). CNR on FBP reconstruction at the maximum dose was stored as refCNR. On those functions we finally defined for each IR strength the CTDI that correspond to refCNR. Thus, we obtained 6 CTDI-IR strength pair, and we checked if MTF50 was at least as good as FBP reconstruction at maximum dose. The Five IR strength were noted IR1, IR2, IR3, IR4, IR5, corresponding to ASIR 20%, 40%, 60%, 80% and 100% on one hand, and SAFIRE 1, 2, 3, 4, 5 on the other hand.

## 2.10. Qualitative analysis

To visually assess the qualitative performances of the previously obtained CTDI-IR strength pair, we performed CT examinations on an anthropomorphic phantom with those parameters. This phantom is built with water equivalent plastic in which one can find a real skeleton. The CT examination is focused on temporal bones. A visual evaluation was then performed by four senior radiologists (evaluation criteria are described below) and CNR was measured in the posterior cranial fossa in order to verify its non variability between the different series.

## 2.11. Reading criteria

We selected 16 anatomical structures, specially chosen for their clinical interest and anatomical finesse. For the middle ear: atticus wall, tegmen tympani, facial nerve canal II, facial nerve canal III, posterior canal of the chorda tympani, series of mastoid cells. For the inner ear: cochlea, modiolus, spiral ganglion, cochlear fossette, homogeneity of the otic capsule, semi-circular canals, sacular and utricular nerve canals, posterior ampullary nerve canal, facial nerve canal I.

A three-point scale was established (Fig. 2): structure clearly visible: 2; partially visible (or suffering from artifacts): 1; not visible (or suffering from artifacts that may mimick disease): 0.

These series were evaluated blind and randomly by four radiologists. The scale was given to all the radiologists in order to standardise interpretations. DICOM information on constants was removed using the DicomBrowser software (V 1.5.2. NRG Lab, Washington University School of Medicine, USA). The series were presented randomly thanks to The Hat® software (V 3.0.1, Harmony Hollow Software, Covington, USA).

The reading group comprised four radiologists: two senior radiologists (observer 1 and observer 3), including a national referee on temporal imaging [7], and two junior radiologists (observer 2 and observer 4).

Reading was carried out on the same, full HD work station 1080 P. The four readers used the same Radiant® viewer (V 1.9.14 Medixant, Poznan, Poland) that allowed a 3D MPR analysis to be conducted.

## 2.12. Statistics

The statistical analysis of qualitative data was performed using the STATA/MP 13.0 software for Mac by StataCorp, USA. The responses by the four observers (from 0 to 2) regarding the 16 items (anatomical structure) of the 15 acquisitions were considered to be separate quantitative variables. The sum of the responses (total

<caption>**Table 2**</caption>

Quantitative analysis: CNR890 measured as a function of CTDI with FBP and 5 IR strength for both systems.

<table><caption>**Table 2bis**</caption><thead><tr><th>CNR890</th><th>CTDi</th><th>FBP</th><th>IR-1</th><th>IR-2</th><th>IR-3</th><th>IR-4</th><th>IR-5</th></tr></thead><tbody><tr><td rowspan="10">ASiR</td><td>113</td><td>4,3</td><td>4,8</td><td>5,2</td><td>5,8</td><td>6,6</td><td>7,4</td></tr><tr><td>104</td><td>4,1</td><td>4,6</td><td>5,0</td><td>5,6</td><td>6,4</td><td>7,2</td></tr><tr><td>93,1</td><td>3,9</td><td>4,4</td><td>4,8</td><td>5,3</td><td>5,9</td><td>6,7</td></tr><tr><td>85,9</td><td>3,8</td><td>4,2</td><td>4,6</td><td>5,1</td><td>5,7</td><td>6,4</td></tr><tr><td>70,2</td><td>3,4</td><td>3,8</td><td>4,1</td><td>4,5</td><td>5,0</td><td>5,6</td></tr><tr><td>60,1</td><td>3,2</td><td>3,5</td><td>3,8</td><td>4,2</td><td>4,6</td><td>5,1</td></tr><tr><td>50</td><td>2,9</td><td>3,2</td><td>3,4</td><td>3,8</td><td>4,1</td><td>4,6</td></tr><tr><td>36</td><td>2,5</td><td>2,7</td><td>2,9</td><td>3,2</td><td>3,5</td><td>3,9</td></tr><tr><td>26</td><td>2,2</td><td>2,3</td><td>2,5</td><td>2,7</td><td>2,9</td><td>3,2</td></tr><tr><td>17</td><td>1,7</td><td>1,9</td><td>2,0</td><td>2,2</td><td>2,4</td><td>2,7</td></tr><tr><td rowspan="10">SAFIRE</td><td>113</td><td>5,5</td><td>6,2</td><td>7,5</td><td>9,2</td><td>12,6</td><td>17,1</td></tr><tr><td>104</td><td>5,4</td><td>6,1</td><td>7,4</td><td>9,1</td><td>12,4</td><td>16,9</td></tr><tr><td>93,1</td><td>5,1</td><td>5,8</td><td>6,9</td><td>8,5</td><td>11,7</td><td>15,9</td></tr><tr><td>85,9</td><td>4,8</td><td>5,5</td><td>6,6</td><td>8,1</td><td>11,2</td><td>15,2</td></tr><tr><td>70,2</td><td>4,4</td><td>5,0</td><td>6,0</td><td>7,4</td><td>10,1</td><td>13,7</td></tr><tr><td>60,1</td><td>4,1</td><td>4,7</td><td>5,6</td><td>6,9</td><td>9,5</td><td>12,6</td></tr><tr><td>50</td><td>3,7</td><td>4,2</td><td>5,1</td><td>6,3</td><td>8,7</td><td>11,6</td></tr><tr><td>36</td><td>3,1</td><td>3,5</td><td>4,2</td><td>5,2</td><td>7,2</td><td>9,6</td></tr><tr><td>26</td><td>2,6</td><td>3,0</td><td>3,6</td><td>4,4</td><td>6,1</td><td>8,0</td></tr><tr><td>17</td><td>2,0</td><td>2,3</td><td>2,8</td><td>3,4</td><td>4,7</td><td>6,5</td></tr></tbody></table>

IRstrength-CTDi pair that enable to maintain CNRref for both reconstruction algorithms.

<table><thead><tr><th></th><th>FBP</th><th>IR-1</th><th>IR-2</th><th>IR-3</th><th>IR-4</th><th>IR-5</th></tr></thead><tbody><tr><th>ASiR</th><td>113 mGy</td><td>89 mGy</td><td>75 mGy</td><td>64 mGy</td><td>53 mGy</td><td>44 mGy</td></tr><tr><th>SAFIRE</th><td>113 mGy</td><td>83 mGy</td><td>59 mGy</td><td>40 mGy</td><td>22 mGy</td><td>11 mGy</td></tr></tbody></table>

score of 32 per observer) was related to a continuous quantitative variable. Thus, the total score and mean response was calculated for each acquisition by including all the observers. If necessary, the normality of the distribution of variables or the difference of a variable between two classes was tested using the descriptive flatness and asymmetry test, i.e. skewness and kurtosis. Bartlett's test was previously performed for each variable comparison in order to verify whether it possessed non-differing variance. Based on these data, an ANOVA variance analysis was performed in order to compare the mean responses (via their difference) between each acquisition. This calculation was combined with a Bonferroni correction for multiple comparisons. Spearman's rhô correlation coefficient was calculated between the FBP of each manufacturer in order to find a correlation between observers' responses par item. The inter-observer agreement on the qualitative measurements of each observer pair was estimated using Cohen's kappa coefficient. Several identical series were evaluated a number of times by the same observer in order to calculate inter-observer agreement. For all these tests we used a *p* of 0.05 as being significant.

# 3. Results

## 3.1. Quantitative results on the Catphan® phantom

Acquisitions were performed at different CTDIvol as follows: 113, 104, 93, 70, 60, 50, 36, 26 and 17 mGy. CNR890 measured on FBP and 5 IR-Strength reconstructions are shown in Table 2. Data was adjusted with a polynomial function CNR = f(CTDi) (Fig. 3) for FBP and each IR strength. According to those obtained functions, the CTDI that would correspond to RefCNR is shown in Table 2bis. The MTF measured on Siemens acquisitions was between the 12 and 13 PL/mm group. The MTF measured on GE acquisitions was between the 13 and 14 PL/mm group.
<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Magnified views of axial reconstructions of the anthropomorphic phantom temporal bone CT acquisitions, and corresponding readers evaluations. Images 1: Exploration of the modiolus. 1A (evaluation 2): the modiolus is correctly depicted. 1B (evaluation 1): only a part of the modiolus is correctly depicted (the arrow shows a blurred area), 1C (evaluation 0) Uncorrect depiction of the whole structure (arrow). Images 2: Evaluation of the lateral semi-circular canal. 2A (evaluation 2): the structure is fully visualised. 2B (evaluation 1): A thin hyperdense area (arrow) masks the depiction of the canal borders. 2C (evaluation 0): A more hyperdense artifact may simulate calcification (arrow). Images 3: Analysis of mastoid cells. 3A (evaluation 2): Correct appreciation of the structure. 3B (evaluation 1): Thin rectangular borders are seen (arrow). 3C (evaluation 0): More rectangular borders are seen (arrow) and blurred area that may simulate inflammatory mastoid changes (thin arrow).</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>**Fig. 3.** CNR890 measurements for each degree of iteration and each manufacturer. The curves show the evolution of CNR890 (on the Y axis) depending on CDTIvol (on the X axis). Fig. 3A shows the Siemens measurements; Fig. 3B the results for GE. IR-1 corresponds to SAFIRE 1 and ASiR 20%; IR-2 corresponds to SAFIRE 2 and ASiR 40%; IR-3 corresponds to SAFIRE 3 and ASiR 60%; IR-4 corresponds to SAFIRE 4 and ASiR 80%; IR-5 corresponds to SAFIRE 5 and ASiR 100%. CNRref corresponds to the CNR of the FBP at 113 mGy chosen as a reference.</figcaption></figure>

## 3.2. Qualitative results on the anthropomorphic phantom

### 3.2.1. Inter- and intra-observer reproducibility

Inter- and intra-observer reproducibility was calculated using Cohen's kappa coefficient. The intra-observer kappa for observer 1 was strong (0.67) that of observer 2 was moderate (0.52), that

of observer 3 was strong (0.72), and that of observer 4 was weak (0.39). The overall inter-observer kappa was moderate (0.46).

### 3.2.2. Control CNR

The control CNR calculated on the anthropomorphic phantom did not show a reduction in CNR in the three manufacturers. With
<figure><img src="image_7.png" /><figcaption>**Fig. 4.** The four observers' mean scores for each IR. 4A shows the mean scores for SAFIRE, 4B shows the mean scores for ASiR. The analysis took into account the modification/significant alteration of the variance of this score through the "strengthening" of iterative reconstruction in both group. At each level, the result of the score is compared to the corresponding one at manufacturer FBP. The point at which the reading is significantly modified is declared to correspond to the least possible clinically acceptable dose reduction (compared to FBP) and plotted as a vertical line coupled with the dose.</figcaption></figure>

<caption>**Table 3**</caption>

Results of mean scores (m) of the qualitative evaluation and differences in means (dm) of IRs compared with FBP scores. When *p* > 0.05 there is no significant degradation of IRs compared with FBP.

<table><thead><tr><th></th><th>Parameters</th><th>FBP</th><th>IR-1</th><th>IR-2</th><th>IR-3</th><th>IR-4</th><th>IR-5</th></tr></thead><tbody><tr><td rowspan="3">GE<br>(ASiR)</td><td>m</td><td>1,9</td><td>1,92</td><td>1,45</td><td>1,5</td><td>1,3</td><td>0,87</td></tr><tr><td>dm</td><td></td><td>0,016</td><td>-0,453</td><td>-0,406</td><td>-0,594</td><td>-1,031</td></tr><tr><td><i>p</i></td><td></td><td>1</td><td>&lt;0,001</td><td>&lt;0,001</td><td>&lt;0,001</td><td>&lt;0,001</td></tr><tr><td rowspan="3">SIEMENS<br>(SAFIRE)</td><td>m</td><td>1,875</td><td>1,72</td><td>1,62</td><td>1,67</td><td>1,26</td><td>1,14</td></tr><tr><td>dm</td><td></td><td>-0,156</td><td>-0,25</td><td>-0,203</td><td>-0,609</td><td>-0,734</td></tr><tr><td><i>p</i></td><td></td><td>0,844</td><td>0,035</td><td>0,198</td><td>&lt;0,001</td><td>&lt;0,001</td></tr></tbody></table>

Siemens the measured CNR increased during iterations (FBP CNR = 5.37; CNR it 5 = 8.46). With GE the measured CNR increased during iterations (FBP CNR = 4.88; CNR it 5 = 8.46). The absence of CNR degradation validates our acquisitions on the anthropomorphic phantom and enables a qualitative analysis. See Fig. 3.

### 3.2.3. Comparison of reference FBPs ($FBP_{reference}$)

We were able to compare FBP acquisitions with a CDTI<sub>vol</sub> of 113 mGy for the manufacturers Siemens, and GE using the variance analysis of scores described in II.4. The mean values in the evaluation of FBPs for the responses of the four observers were 1.87 (standard deviation: SD 0.33) for Siemens and 1.90 (SD: 0.29) for GE. The mean $FBP_{reference}$ of the two manufacturers did not differ ($p$ = 0.81). There was a significant correlation between the observers' responses per item in the $FBP_{reference}$. This was estimated using Spearman's rhô coefficient. The rhô between Siemens and GE it was 0.55 ($p$ = 0.02).

The absence of a difference in the means and the correlation of the qualitative study results enabled us to validate the absence of a difference between the two manufacturers' $FBP_{reference}$.

### 3.2.4. Comparison of each manufacturer's IRs with FBP

The mean score for each observer for each acquisition is shown in Fig. 4A for SAFIRE, Fig. 4B for ASiR.

The four observers' mean score for the FBP of Siemens was 1.875, for SAFIRE 1 it was 1.72, for SAFIRE 2 it was 1.62, for SAFIRE 3 it was 1.67, for SAFIRE 4 it was 1.26, and for SAFIRE 5 it was 1.14. The variance analysis for the series of Siemens images did not show degradation on iteration 3 with a CDTI<sub>vol</sub> of 40 mGy ($p$ = 0.198). Iteration 4 showed significant degradation ($p$ = 0.001). The second level of acquired iteration at a CDTI<sub>vol</sub> of 61 mGy showed moderate image degradation ($p$ = 0.035) (Table 3).

The four observers' mean score for the FBP of GE was 1.9, for ASiR 20% it was 1.45, for ASiR 40% it was 1.5, for ASiR 60% it was 1.31, for ASiR 80% it was 1.3, and for ASiR 100% it was 0.87. The variance analysis for the series of GE images showed degradation from the second level of iteration ($p$ < 0.001) and did not show degradation on the first level of iteration ($p$ = 1) with CDTI<sub>vol</sub> at 85 mGy (Table 3).

## 4. Discussion

This study shows that the IRs of SAFIRE and ASiR make it possible to reduce the dose of exposure to rays in explorations of the temporal bone while preserving image quality.

IRs provide images with less noise, thus making it possible to reduce the dose [4,21]. CNR is an index that mix contrast and noise. The decrease in noise in the image is specific to the functioning of each IR [14]. The results of our measurements on a Catphan® phantom confirm the differences in the effectiveness of algorithms in providing a denoised image. In our results with a constant dose, Siemens's SAFIRE 5 enabled an improvement in CNR of 212% compared with FBP. GE's ASiR<sub>100%</sub> enabled an improvement in CNR of 73% compared with FBP. This noise reduction capacity is an important asset in the reduction of patient exposure to X-rays. This is because dose reduction leads to an increase in noise in the image, which is compensated for by the denoising of IRs. Our measurements on the Catphan® phantom corroborate these data; SAFIRE has the best noise compensation compared with the other two manufacturers. SAFIRE 5 preserves the CNR<sub>reference</sub> with a reduction in CDTI<sub>vol</sub> of 90%, and GE's ASiR<sub>100%</sub> preserves the CNR<sub>reference</sub> with a reduction in CDTI<sub>vol</sub> of 63%.

Quantitatively, we can see that SAFIRE provides better contrast to noise ratio, thanks a lower noise level than ASiR. This different result can be explained by the use of comparison model in
ASiR that integrates counting statistics for photons (Poisson distribution) detected during the reconstruction process [4]. SAFIRE's higher noise compensation can be explained by its use of a geometric MBIR comparison model. This is an advanced IR algorithm that integrates the modelling of several key parameters that are absent from previous algorithm [13].

The statistical analysis of the qualitative reading enables us to verify the clinical use of the parameters determined during the first step. There is a qualitative degradation of optimised pairs with low doses and strong IRs that varies depending on the manufacturer. This shows us a qualitative limit to the optimisation of doses by IR. In our study, the optimal use of the degree of iteration and dose reduction are: Siemens: SAFIRE 3 with a CDTIvol of 40 mGy, i.e. a dose reduction of 65%; GE: ASiR 20% with a CDTIvol of 90 mGy, i.e. a dose reduction of 20%.

The difference between quantitative and qualitative measurements can be explained by a modification in the image texture at higher IR degrees [22]. Image texture is evaluated by the spectral distribution of noise (Noise Power Spectrum, NPS). Studies comparing NPS show a shift in noise frequency curves towards low frequencies [19,23,8]. This shift is proportional to the level of IR used and leads to a smoothing of the image that can disrupt the radiologist's reading at high iterations. Another explanation comes from the fact that high IRs are acquired with a low CDTIvol, implying low signal quality, and despite the capacity of IR to preserve a constant CNR, image quality is reduced. We acknowledge that IR modifies NPS and so the texture of images. The goal here was not to measure this, but to find qualitatively the limit of the use of IR associated to dose reduction. Furthermore NPS is a spectrum measured in homogeneous phantom and it is not easy to find an index that can be used to compare different reconstructions [24].

Studies comparing IRs to their FBP have revealed a dose reduction range that is similar to our results. Studies on SAFIRE show a reduction in CDTIvol of at least 33% in explorations of the encephalon [25,26]. Studies on ASiR found a 17% reduction in CDTIvol in explorations of the neck [27] and from 20 to 31% in the encephalon [14,28–30].

It has also been observed that CDTI can be reduced more substantially in other anatomical regions. Articles about SAFIRE report a dose reduction of 40 to 60% in abdominal explorations [16,31]. Articles on ASiR show a 35% reduction in the lungs [32,33], a 32-65% reduction in the abdomen [7,2], about 20% reduction in head [34], and up to 40% reduction during craniocervical angiographic CT explorations [35].

Spatial resolution is an important technical requirement in explorations of the temporal bone. This is because this anatomical zone is made up of dense bone structures often under 1 millimetre [36]. Spatial resolution depends on the filter in FBP and the technical characteristics of X-ray detectors. Filtration makes it possible to reduce noise in the image, but to the detriment of spatial resolution. Highly resolved reconstructions are filtered with very hard filters and are therefore very noisy. Our results, like those in the literature, show that IR makes it possible to reduce noise without degrading spatial resolution. This is because for each degree of iteration there is no degradation of MTF50% for a given CDTIvol [23]. In other terms, the reduction in noise by IR is not to the detriment of spatial resolution, unlike FBP [8].

One of the limits of our study arises from the fact that we were not able to evaluate these images in the context of a temporal bone disease. One of these diseases is otosclerosis [36], which most often appears in imaging in the form of an area of demineralisation of the otic capsule. This area may be very narrow, poorly contrasted, and therefore requires both high spatial resolution and a strong contrast resolution. Our results show that IR meets these requirements, and it would therefore be interesting to test these IRs on otosclerosis. Cholesteatoma, footplate diseases and traumatic le-

sions [36] require high spatial resolution and low noise; IR appears to be a reconstruction model that is perfectly adapted to these requirements. Finally, the ability of algorithms to model artefacts attached to prostheses [4] may be used in cochlear implants. The absence of ossicles in our phantom can certainly be criticised; our observations, however, show that the use of a cadaver does not completely resolve this limitation due to the stagnation of fluid in the middle ear and the rapid deterioration of the ossicular chain. In summary, the mean value of our kappa is comparable to the kappa of similar studies [14,37,28].

It is interesting to note that in order to compare IRs we could not use some of the manufacturers' specific features when exploring the temporal bone, such as Siemens's UHR mode, which enables slices of 0.3 mm (GE system didn't allow 0.3 mm slices).

It is therefore easy to understand the importance of reducing exposure to X-rays, in particularly in specific populations such as pediatric one [14,38]. In this view, new MBIR generations of IR that model the entire X-ray production/emission chain, as well as the object being studied, are being developed. GE has accordingly developed VEO [14] and Siemens has developed a new generation of MBIR called ADMIRE (Advanced Modelled Iterative Reconstruction) [39]. Unlike ASiR, SAFIRE these algorithms are currently not very widespread in clinical practice since they are not installed on the existing range of scanning apparatus but only on certain recent machines. However, they open up the prospect of greater noise reduction as well as a new dimension in the possibilities of optimisation [40].

## 5. Conclusion

The use of these two IRs in explorations of the temporal bone makes it possible to reduce exposure to X-rays while preserving image quality. The differences in performance between SAFIRE and ASiR IRs require optimisation by a given CDTIvol/iteration level pair in this article. In view of the greater capacity for dose reduction with SAFIRE, the use of more advanced MBIR models can be encouraged.

## Declaration of competing interest

No conflicts of interest.

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