Systematic Radiation Dose Reduction in Cervical Spine CT of Human Cadaveric Specimens: How Low Can We Go?

Image quality assessment in spine surgery: a comparison of intraoperative CBCT and postoperative MDCT

OBJECTIVE

To evaluate if intraoperative cone-beam CT (CBCT) provides equivalent image quality to postoperative multidetector CT (MDCT) in spine surgery, potentially eliminating unnecessary imaging and cumulative radiation exposure.

METHODS

Twenty-seven patients (16 men, 11 women; median age 39 years) treated with spinal fixation surgery were evaluated using intraoperative CBCT and postoperative MDCT. The images were independently evaluated by four neuroradiologists, utilizing a five-step Likert scale and visual grading characteristics (VGC) analysis. The area under the VGC curve (AUCVGC) quantified preferences between modalities. Intra- and inter-observer variability was evaluated using intraclass correlation coefficients (ICC). Image quality was objectively evaluated by contrast and signal-to-noise measurements (CNR, SNR).

RESULTS

In image quality, CBCT was the preferred modality in thoracolumbar spine (AUCVGC = 0.58, p < 0.001). Conversely, MDCT was preferred in cervical spine (AUCVGC = 0.38, p < 0.004). The agreement was good for inter-observer and moderate in intra-observer (ICC 0.76-0.77 vs 0.60-0.71), p < 0.001. SNR and CNR were comparable in thoracolumbar imaging, while MDCT provided superior and more consistent image quality in the cervical spine, p < 0.001.

CONCLUSION

In spine surgery, CBCT provides superior image quality for thoracolumbar imaging, while MDCT performs better for cervical imaging. Intraoperative CBCT could potentially replace postoperative MDCT in thoracolumbar spine procedures, while postoperative MDCT remains essential for cervical spine assessment.

KEY POINTS

Subjective assessment demonstrated that CBCT was the preferred modality for thoracolumbar spine imaging, while MDCT was favored for cervical spine imaging. Agreement between readers was good, while individual readings showed moderate consistency in repeated assessments. Objective assessment of image clarity and detail showed both modalities performed equally well in the thoracolumbar spine, while MDCT performed better in the cervical spine. Intraoperative CBCT proves superior to postoperative MDCT for thoracolumbar spine imaging, potentially eliminating redundant scans, and improving workflow. Postoperative MDCT remains essential for cervical spine procedures.

Technical note: An optimized protocol for standard unenhanced whole-body post-mortem Photon Counting CT imaging

In recent years, Photon-counting detector CT (PCD CT) has emerged as a new and groundbreaking technology in clinical radiology. While clinical research and practical applications of PCD-CT are constantly evolving, it has not yet been integrated into post-mortem CT (PMCT) imaging. Documented research into the potential applications of PCD CT in the field of post-mortem human forensic pathology and anatomical pathology is scarce in literature. This is despite the fact that PCD CT shows promise in expanding PMCT imaging diagnostic due to features such as ultra-high resolution and intrinsic spectral multienergy imaging. The authors have recently started scanning forensic corpses with a PCD CT to explore its possibilities and limits in the post-mortem field. In this technical note, the PCD CT acquisition and reconstruction parameters that resulted in excellent image quality in terms of noise and contrast for a slice thickness up to 0.2 mm in unenhanced whole-body examinations are presented.

Geometric accuracy of low-dose CT scans for use in shoulder musculoskeletal research applications

Computed tomography (CT) imaging is frequently employed in a variety of musculoskeletal research applications. Although research studies often use imaging protocols developed for clinical applications, lower dose protocols are likely possible when the goal is to reconstruct 3D bone models. Our purpose was to describe the dose-accuracy trade-off between incrementally lower-dose CT scans and the geometric reconstruction accuracy of the humerus, scapula, and clavicle. Six shoulder specimens were acquired and scanned using 5 helical CT protocols: 1) 120 kVp, 450 mA (full-dose); 2) 120 kVp, 120 mA; 3) 120 kVp, 100 mA; 4) 100 kVp, 100 mA; 5) 80 kVp, 80 mA. Scans were segmented and reconstructed into 3D surface meshes. Geometric error was assessed by comparing the surfaces of the low-dose meshes to the full-dose (gold standard) mesh and was described using mean absolute error, bias, precision, and worst-case error. All low-dose protocols resulted in a >70 % reduction in the effective dose. Lower dose scans resulted in higher geometric errors; however, error magnitudes were generally <0.5 mm. These data suggest that the effective dose associated with CT imaging can be substantially reduced without a significant loss of geometric reconstruction accuracy.

Influence of helical pitch and gantry rotation time on image quality and file size in ultrahigh-resolution photon-counting detector CT

The goal of this experimental study was to quantify the influence of helical pitch and gantry rotation time on image quality and file size in ultrahigh-resolution photon-counting CT (UHR-PCCT). Cervical and lumbar spine, pelvis, and upper legs of two fresh-frozen cadaveric specimens were subjected to nine dose-matched UHR-PCCT scan protocols employing a collimation of 120 × 0.2 mm with varying pitch (0.3/1.0/1.2) and rotation time (0.25/0.5/1.0 s). Image quality was analyzed independently by five radiologists and further substantiated by placing normed regions of interest to record mean signal attenuation and noise. Effective mAs, CT dose index (CTDIvol), size-specific dose estimate (SSDE), scan duration, and raw data file size were compared. Regardless of anatomical region, no significant difference was ascertained for CTDIvol (p ≥ 0.204) and SSDE (p ≥ 0.240) among protocols. While exam duration differed substantially (all p ≤ 0.016), the lowest scan time was recorded for high-pitch protocols (4.3 ± 1.0 s) and the highest for low-pitch protocols (43.6 ± 15.4 s). The combination of high helical pitch and short gantry rotation times produced the lowest perceived image quality (intraclass correlation coefficient 0.866; 95% confidence interval 0.807-0.910; p < 0.001) and highest noise. Raw data size increased with acquisition time (15.4 ± 5.0 to 235.0 ± 83.5 GByte; p ≤ 0.013). Rotation time and pitch factor have considerable influence on image quality in UHR-PCCT and must therefore be chosen deliberately for different musculoskeletal imaging tasks. In examinations with long acquisition times, raw data size increases considerably, consequently limiting clinical applicability for larger scan volumes.

Deep learning-driven diagnosis of multi-type vertebra diseases based on computed tomography images

Background

Osteoporotic vertebral compression fractures (OVCFs) are the most common type of fragility fracture. Distinguishing between OVCFs and other types of vertebra diseases, such as old fractures (OFs), Schmorl's node (SN), Kummell's disease (KD), and previous surgery (PS), is critical for subsequent surgery and treatment. Combining with advanced deep learning (DL) technologies, this study plans to develop a DL-driven diagnostic system for diagnosing multi-type vertebra diseases.

Methods

We established a large-scale dataset based on the computed tomography (CT) images of 1,051 patients with OVCFs from Luhe Hospital and used data of 46 patients from Xuanwu Hospital as alternative hospital validation dataset. Each patient underwent one examination. The dataset contained 11,417 CT slices and 19,718 manually annotated vertebrae with diseases. A two-stage DL-based system was developed to diagnose five vertebra diseases. The proposed system consisted of a vertebra detection module (VDModule) and a vertebra classification module (VCModule).

Results

The training and testing dataset for the VDModule consisted of 9,135 and 3,212 vertebrae, respectively. The VDModule using the ResNet18-based Faster region-based convolutional neural network (R-CNN) model achieved an area under the curve (AUC), false-positive (FP) rate, and false-negative (FN) rate of 0.982, 1.52%, and 1.33%, respectively, in the testing dataset. The training dataset for VCModule consisted of 14,584 and 47,604 diseased and normal vertebrae, respectively. The testing dataset consisted of 4,489 and 15,122 diseased and normal vertebrae, respectively. The ResNet50-based VCModule achieved an average sensitivity and specificity of 0.919 and 0.995, respectively, in diagnosing four kinds of vertebra diseases except for SN in the testing dataset. In the alternative hospital validation dataset, the ResNet50-based VCModule achieved an average sensitivity and specificity of 0.891 and 0.989, respectively, in diagnosing four kinds of vertebra diseases except for SN.

Conclusions

Our proposed DL system can accurately diagnose four vertebra diseases and has strong potential to facilitate the accurate and rapid diagnosis of vertebral diseases.

Effect of Deep Learning Reconstruction on Evaluating Cervical Spinal Canal Stenosis With Computed Tomography

OBJECTIVE

Magnetic resonance imaging (MRI) is commonly used to evaluate cervical spinal canal stenosis; however, some patients are ineligible for MRI. We aimed to assess the effect of deep learning reconstruction (DLR) in evaluating cervical spinal canal stenosis using computed tomography (CT) compared with hybrid iterative reconstruction (hybrid IR).

METHODS

This retrospective study included 33 patients (16 male patients; mean age, 57.7 ± 18.4 years) who underwent cervical spine CT. Images were reconstructed using DLR and hybrid IR. In the quantitative analyses, noise was recorded by placing the regions of interest on the trapezius muscle. In the qualitative analyses, 2 radiologists evaluated the depiction of structures, image noise, overall image quality, and degree of cervical canal stenosis. We additionally evaluated the agreement between MRI and CT in 15 patients for whom preoperative cervical MRI was available.

RESULTS

Image noise was less with DLR than hybrid IR in the quantitative ( P ≤ 0.0395) and subjective analyses ( P ≤ 0.0023), and the depiction of most structures was improved ( P ≤ 0.0052), which resulted in better overall quality ( P ≤ 0.0118). Interobserver agreement in the assessment of spinal canal stenosis with DLR (0.7390; 95% confidence interval [CI], 0.7189-0.7592) was superior to that with hybrid IR (0.7038; 96% CI, 0.6846-0.7229). As for the agreement between MRI and CT, significant improvement was observed for 1 reader with DLR (0.7910; 96% CI, 0.7762-0.8057) than hybrid IR (0.7536; 96% CI, 0.7383-0.7688).

CONCLUSIONS

Deep learning reconstruction provided better quality cervical spine CT images in the evaluation of cervical spinal stenosis than hybrid IR.

Ultrahigh-resolution computed tomography of the cervical spine without dose penalty employing a cadmium-telluride photon-counting detector

PURPOSE

This cadaveric study compared image quality between a third-generation dual-source CT scanner with energy-integrating detector technology (EID) and a first-generation CT system employing a photon-counting detector (PCD) for the cervical spine in ultrahigh-resolution mode.

METHODS

The cervical spine of eight formalin-fixed full-body cadaveric specimens was scanned with both CT systems using 140 kVp scan protocols matched for CTDI_vol (full-dose; low-dose; ultralow-dose; 10 mGy; 3 mGy; 1 mGy). Images were reconstructed with 1 mm slice thickness and 0.5 mm increment. Three radiologists rated overall subjective image quality based on an equidistant five-point scale with the intraclass correlation coefficient (ICC) calculated for assessment of interobserver reliability. Contrast-to-noise ratios were calculated individually for bone (CNR_bone) and muscle tissue (CNR_muscle) to provide objective criteria of image analysis.

RESULTS

Subjective image quality, as well as CNR_bone, and CNR_muscle were each superior for PCD-CT compared to EID-CT among dose-matched scan protocol pairs (all p < 0.05). Between full-dose EID-CT and low-dose PCD-CT, subjective image quality was equal (p = 0.903), while superior quantitative results regarding the latter were ascertained (both p < 0.001). Similarly, objective analysis determined higher CNR_bone, and CNR_muscle in ultralow-dose PCD-CT compared to low-dose EID-CT (both p < 0.001), while readers considered the image quality of the respective studies comparable (p > 0.99). Interobserver reliability was good, denoted by an ICC of 0.861 (95 % confidence interval: 0.788 - 0.914; p < 0.001).

CONCLUSIONS

In cervical spine examinations, both subjective and objective image quality of PCD-CT were superior to EID-CT in comparison of scan protocols with corresponding dose levels, suggesting potential for significantly reducing the radiation exposure without compromising image quality.

Feasibility analysis of high pitch cervical spine CT in uncooperative patients with acute cervical spine trauma: An initial experience

Cervical computed tomography (CT) often suffers from examination failure in uncooperative patients with acute cervical spinal trauma. Therefore, this study aimed to evaluate the feasibility of using high-pitch cervical CT (HP-CT) in such populations. A total of 95 patients with acute neck/head-neck trauma who underwent HP-CT (n = 29) or standard cervical CT (SD-CT, n = 66) from October 2020 to June 2021 were included in this study. Differences in patient characteristics between the HP-CT group and the SD-CT group were firstly compared. Then, the objective image quality based on the mean score of the signal-to-noise ratio (SNR)/contrast noise ratio (CNR) was evaluated, while double-blind five-point scoring was adopted for the subjective evaluation. Finally, radiation doses in HP-CT and SD-CT were compared. Furthermore, the Student t test and/or Mann-Whitney U test were performed to analyze differences in patient characteristics, image quality, and radiation dose between the two regimes. A total of 17 cases of cervical spine fractures were found in 95 patients, including 6 cases in the HP-CT group and 11 cases in the SD-CT group. The average age of patients who received HP-CT was higher than that of those who received SD-CT, and the scan time using HP-CT was shorter than that SD-CT. The differences were statistically significant (both, P < .05). In addition, there was no significant difference between HP-CT and SD-CT in terms of sex, body mass index, field of view (FOV), and scan length (all P > .05). The SNR/CNR at the middle and upper neck was not significantly different between HP-CT and SD-CT (all P > .05). However, the SNR/CNR at the lower neck in HP-CT was lower than that in SD-CT (all P < .05). There was no significant difference in the subjective scores between HP-CT and SD-CT images in both the soft tissue and bone window (P = .129 and 0.649, respectively). The radiation dose in HP-CT was lower than that in SD-CT (all P < .05). With a scan time reduction of 73%, radiation dose reduction of 10%, and similar image quality, high-pitch cervical CT was of feasibility to evaluate cervical spine injury in uncooperative patients with acute cervical spine trauma.

Is It Possible to Replace Conventional Radiography (CR) with a Dose Neutral Computed Tomography (CT) of the Cervical Spine in Emergency Radiology—An Experimental Cadaver Study

The purpose of this experimental study on recently deceased human cadavers was to investigate whether (I) the radiation exposure of the cervical spine CT can be reduced comparable to a dose level of conventional radiography (CR); and (II) whether and which human body parameters can be predictive for higher dose reduction potential (in this context). Materials and Methods: Seventy serial CT scans of the cervical spine of 10 human cadavers undergoing postmortem virtual autopsy were taken using stepwise decreasing upper limits of the tube current (300 mAs, 150 mAs, 110 mAs, 80 mAs, 60 mAs, 40 mAs, and 20 mAs) at 120 kVp. An additional scan acquired at a fixed tube current of 300 mAs served as a reference. Images were reconstructed with filtered back projection and the upper (C1-4) and lower (C4-7) cervical spine were evaluated by three blinded readers for image quality, regarding diagnostic value and resolution of anatomical structures according to a semiquantitative three-point-scale. Dose values and individual physical parameters were recorded. The relationship of diagnostic IQ, dose reduction level, and patients’ physical parameters were investigated. The high-contrast resolution of the applied CT protocols was tested in an additional phantom study. Results: The IQ of the upper cervical spine was diagnostic at 1.69 ± 0.58 mGy (CTDI) corresponding to 0.20 ± 0.07 mSv (effective dose) in all cadavers. IQ of the lower cervical spine was diagnostic at 4.77 ± 1.86 mGy corresponding to 0.560 ± 0.21 mSv (effective dose) in seven cadavers and at 2.60 ± 0.93 mGy corresponding to 0.31 ± 0.11 mSv in four cadavers. Significant correlation was detected for BMI (0.8366; p = 0.002548) and the anteroposterior (a.p.) chest diameter (0.8363; p = 0.002566), shoulder positioning (0.79799; p = 0.00995), and radiation exposure. Conclusions: Conventional radiography can be replaced with a nearly dose-neutral CT scan of the cervical spine.

Radiation dose levels of thoracic-lumbar spine CT in pediatric trauma patients and assessment of scan parameters for dose optimization

BACKGROUND

CT is frequently used for assessing spinal trauma in children.

OBJECTIVE

To establish the local diagnostic reference levels of spine CT examinations in pediatric spinal trauma patients and analyze scan parameters to enable dose optimization.

MATERIALS AND METHODS

In this retrospective study, we included 192 pediatric spinal trauma patients who underwent spine CT. Children were divided into two age groups: 0-10 years (group 1) and 11-17 years (group 2). Each group was subdivided into thoracic, thoracolumbar and lumbar CT groups. CT acquisition parameters (tube potential, in kilovoltage [kV]; mean tube current-time product, in milliamperes [mAs]; reference mAs; collimated slice width; tube rotation time; pitch; scan length) and radiation dose descriptors (volume CT dose index [CTDI_vol] and dose-length product [DLP]) were recorded. The CTDI_vol and DLP values of spine CTs obtained with different tube potential and collimated slice width values were compared for each group.

RESULTS

CTDI_vol and DLP values of thoracolumbar spine CTs in group 1 and lumbar spine CTs in group 2 were significantly lower in CTs acquired with low tube potential levels (P<0.05). CTDI_vol and DLP values of thoracolumbar spine CTs in both groups and lumbar spine CTs in group 2 acquired with high collimated slice width values were significantly lower than in corresponding CTs acquired with low collimated slice width values (P<0.05).

CONCLUSION

Pediatric spine CT radiation doses can be notably reduced from the manufacturers' default protocols while preserving image quality.

Can a Deep-learning Model for the Automated Detection of Vertebral Fractures Approach the Performance Level of Human Subspecialists?

BACKGROUND

Vertebral fractures are the most common osteoporotic fractures in older individuals. Recent studies suggest that the performance of artificial intelligence is equal to humans in detecting osteoporotic fractures, such as fractures of the hip, distal radius, and proximal humerus. However, whether artificial intelligence performs as well in the detection of vertebral fractures on plain lateral spine radiographs has not yet been reported.

QUESTIONS/PURPOSES

(1) What is the accuracy, sensitivity, specificity, and interobserver reliability (kappa value) of an artificial intelligence model in detecting vertebral fractures, based on Genant fracture grades, using plain lateral spine radiographs compared with values obtained by human observers? (2) Do patients' clinical data, including the anatomic location of the fracture (thoracic or lumbar spine), T-score on dual-energy x-ray absorptiometry, or fracture grade severity, affect the performance of an artificial intelligence model? (3) How does the artificial intelligence model perform on external validation?

METHODS

Between 2016 and 2018, 1019 patients older than 60 years were treated for vertebral fractures in our institution. Seventy-eight patients were excluded because of missing CT or MRI scans (24% [19]), poor image quality in plain lateral radiographs of spines (54% [42]), multiple myeloma (5% [4]), and prior spine instrumentation (17% [13]). The plain lateral radiographs of 941 patients (one radiograph per person), with a mean age of 76 ± 12 years, and 1101 vertebral fractures between T7 and L5 were retrospectively evaluated for training (n = 565), validating (n = 188), and testing (n = 188) of an artificial intelligence deep-learning model. The gold standard for diagnosis (ground truth) of a vertebral fracture is the interpretation of the CT or MRI reports by a spine surgeon and a radiologist independently. If there were any disagreements between human observers, the corresponding CT or MRI images would be rechecked by them together to reach a consensus. For the Genant classification, the injured vertebral body height was measured in the anterior, middle, and posterior third. Fractures were classified as Grade 1 (< 25%), Grade 2 (26% to 40%), or Grade 3 (> 40%). The framework of the artificial intelligence deep-learning model included object detection, data preprocessing of radiographs, and classification to detect vertebral fractures. Approximately 90 seconds was needed to complete the procedure and obtain the artificial intelligence model results when applied clinically. The accuracy, sensitivity, specificity, interobserver reliability (kappa value), receiver operating characteristic curve, and area under the curve (AUC) were analyzed. The bootstrapping method was applied to our testing dataset and external validation dataset. The accuracy, sensitivity, and specificity were used to investigate whether fracture anatomic location or T-score in dual-energy x-ray absorptiometry report affected the performance of the artificial intelligence model. The receiver operating characteristic curve and AUC were used to investigate the relationship between the performance of the artificial intelligence model and fracture grade. External validation with a similar age population and plain lateral radiographs from another medical institute was also performed to investigate the performance of the artificial intelligence model.

RESULTS

The artificial intelligence model with ensemble method demonstrated excellent accuracy (93% [773 of 830] of vertebrae), sensitivity (91% [129 of 141]), and specificity (93% [644 of 689]) for detecting vertebral fractures of the lumbar spine. The interobserver reliability (kappa value) of the artificial intelligence performance and human observers for thoracic and lumbar vertebrae were 0.72 (95% CI 0.65 to 0.80; p < 0.001) and 0.77 (95% CI 0.72 to 0.83; p < 0.001), respectively. The AUCs for Grades 1, 2, and 3 vertebral fractures were 0.919, 0.989, and 0.990, respectively. The artificial intelligence model with ensemble method demonstrated poorer performance for discriminating normal osteoporotic lumbar vertebrae, with a specificity of 91% (260 of 285) compared with nonosteoporotic lumbar vertebrae, with a specificity of 95% (222 of 234). There was a higher sensitivity 97% (60 of 62) for detecting osteoporotic (dual-energy x-ray absorptiometry T-score ≤ -2.5) lumbar vertebral fractures, implying easier detection, than for nonosteoporotic vertebral fractures (83% [39 of 47]). The artificial intelligence model also demonstrated better detection of lumbar vertebral fractures compared with detection of thoracic vertebral fractures based on the external dataset using various radiographic techniques. Based on the dataset for external validation, the overall accuracy, sensitivity, and specificity on bootstrapping method were 89%, 83%, and 95%, respectively.

CONCLUSION

The artificial intelligence model detected vertebral fractures on plain lateral radiographs with high accuracy, sensitivity, and specificity, especially for osteoporotic lumbar vertebral fractures (Genant Grades 2 and 3). The rapid reporting of results using this artificial intelligence model may improve the efficiency of diagnosing vertebral fractures. The testing model is available at http://140.113.114.104/vght_demo/corr/. One or multiple plain lateral radiographs of the spine in the Digital Imaging and Communications in Medicine format can be uploaded to see the performance of the artificial intelligence model.

LEVEL OF EVIDENCE

Level II, diagnostic study.

[Improved image quality of the cervical spine neck CT using an arm traction device]

BACKGROUND

The assessment of the cervico-thoracic junction in the neck CT is frequently hampered by streak artifacts from the shoulder girdles.

PURPOSE

To evaluate the effects of an optimized patient positioning through the use of an arm traction device.

MATERIALS AND METHODS

25 patients (age [mean ± standard deviation]: 58.9 ± 11.6 years; sex [m:f]: 15:10) underwent a neck CT using an arm traction device together. Further 25 patients underwent this in standard positioning (59.8 ± 15.2 years; 16:9). An experienced neuroradiologist determined the last free accessible vertebra on the CT scout view and assessed the image quality of the intervertebral disc space of the lower neck on a three-point grading scale. The procedure was evaluated by the medical-technical radiology assistants performing it.

RESULTS

The last free accessible vertebra on CT scout was statistically significant one vertebra lower using an arm traction device, yielding on average the sixth cervical vertebra (p = 0.010). Subjective image quality increased in all evaluated intervertebral disc spaces (median and absolute frequencies [good/middle/bad]: 1.0 [53/21/8] vs. 2.0 [41/30/24]), resulting in a statistically significant effect between the cervical vertebra 6/7 (p = 0.0041). The traction device approach was rated to be suitable for daily routine in the categories of patient's cooperation (good), comprehensibility for the patient (84%) and management for the assistants (good).

CONCLUSION

Using an arm traction device on neck CT both the accessibility of vertebra on CT scout increased and image quality of the cervico-thoracic junction improved. The simply applicable device could be favourable for cooperative patients with lower neck pathology.

Ultra-low-dose CT versus radiographs for minor spine and pelvis trauma: a Bayesian analysis of accuracy

OBJECTIVES

To compare diagnosis performance and effective dose of ultra-low-dose CT (ULD CT) versus radiographs in suspected spinal or pelvic ring or hip fracture for minor trauma.

METHODS

ULD CT, in addition to radiography, was prospectively performed in consecutive patients admitted to the emergency department for minor traumas, during working hours over 2 months. Presence of a recent fracture was assessed by two blind radiologists independently. Sensitivities and specificities were estimated using the best valuable comparator (BVC) as a reference and using a latent class model in Bayesian inference (BLCM). Dosimetric indicators were recorded and effective doses (E) were calculated using conversion coefficient.

RESULTS

Eighty areas were analyzed in 69 patients, including 22 dorsal spine, 28 lumbar spine, and 30 pelvic ring/hip. Thirty-six fractures (45%) were observed. Applying the BVC method, depending on location, ULD CT sensitivity was 80 to 100% for reader 1 and 85 to 100% for reader 2, whereas radiographic sensitivity was 60 to 85% for reader 1 and 50 to 92% for reader 2. With BLCM approach for reader 2, ULD CT sensitivity for all locations/dorsal spine/lumbar spine and pelvic ring-hip was 87.1/75.9/84.2/76.9% respectively. Corresponding radiograph sensitivity was 73.8, 54.8, 80.4, and 68.7%. Effective doses of ULD CT were similar to radiographs for dorsal and hip locations whereas for lumbar spine, ULD CT effective dose was 1.83 ± 0.59 mSv compared with 0.96 ± 0.59 mSv (p < 0.001).

CONCLUSION

Sensitivity for fracture detection was higher for ULD CT compared with radiographs with an effective dose comparable to radiographs.

KEY POINTS

• Ultra-low-dose spine and pelvis CT demonstrates better fracture detection when compared with radiographs. • The effective dose of ultra-low-dose spine and pelvis CT scan and radiographs is comparable. • Replacement of radiographs by ULD CT in daily practice for trauma patients is an option to consider and should be evaluated by a randomized trial.

Comparison of different iterative CT reconstruction techniques and filtered back projection for assessment of the medial clavicular epiphysis in forensic age estimation

PURPOSE

To assess the impact of iterative reconstruction and filtered back projection (FBP) on image quality in computed tomography (CT)-based forensic age estimation of the medial clavicular epiphysis.

METHODS AND MATERIALS

CT of the clavicle was performed in 19 patients due to forensic reasons (70 mAs/140 kVp). Raw data were reconstructed with FBP and with an iterative algorithm at level 4 and 6. Clavicular ossification stage was determined by two radiologists in consensus, firstly on FBP reconstructed images and secondly after reviewing all reconstructions including iDose 4 and 6. In addition, the 3 reconstructions were compared regarding artefacts and delineation of the meta-/epiphyseal interface. Quantitative image noise was measured.

RESULTS

Quantitative noise was lower in iDose 6 reconstructed images than in FBP (P < 0.042), but not significantly lower between iDose 4 and FBP (P = 0.127). Side by side comparison revealed lesser qualitative image noise on both iDose reconstructed images than for FBP. The meta-/epiphyseal interface delineation was rated better on both iDose levels than with FBP. In 3 of 19 patients, the clavicular ossification stage was reclassified after iterative reconstructions had been additionally reviewed.

CONCLUSION

Using iterative CT reconstruction algorithms, a reduction of image noise and an enhancement of image quality regarding the meta-/epiphyseal clavicular interface can be achieved. The study highlights the importance of image standardization as variation of reconstruction technique has impact on forensic age estimation.

Dose-optimized computed tomography of the cervical spine in patients with shoulder pull-down: Is image quality comparable with a standard dose protocol in an emergency setting?

PURPOSE

Superimposing soft tissue and bony structures in computed tomography (CT) of the cervical spine (C-spine) is a limiting factor in optimizing radiation exposure maintaining an acceptable image quality. Therefore, we assessed image quality of dose-optimized (DO) C-spine CT in patients capable of shoulder pull-down in an emergency setting.

METHODS AND MATERIALS

DO-CT (105mAs/120 kVp) of the C-spine in trauma settings was performed in patients with shoulder pull-down if C5 was not superimposed by soft tissue on the lateral topogram, otherwise standard-dose (SD)-CT (195 mAs/120 kVp) was performed. 34 DO (mean age, 68y ± 21; BMI, 24.2 kg/m² ± 3.2) and 34 SD (mean age 70y ± 19; BMI 25.7 kg/m² ± 4.4) iterative reconstructed CTs were evaluated at C2/3 and C6/7 by two musculoskeletal radiologists. Qualitative image noise and morphological characteristics of bony structures (cortex, trabeculae) were assessed on a Likert scale. Quantitative image noise was measured and effective dose (ED) was recorded. Parameters were compared using Mann-Whitney-U-test (p < 0.05).

RESULTS

At C2/3, DO-CT vs. SD-CT yielded comparable qualitative noise (mean, 1.3 vs. 1.0; p = 0.18) and morphological characteristics, but higher quantitative noise (27.2 ± 8.8HU vs. 19.6 ± 4.5HU; p < 0.001). At C6/7, DO-CT yielded lower subjective noise (1.9; SD-CT 2.2; p = 0.017) and better morphological characteristics with higher visibility scores for cortex (p = 0.001) and trabeculae (p = 0.03). Quantitative noise did not differ (p = 0.24). Radiation dose was 51% lower using DO-CT (ED_DO-CT 0.80 ± 0.1 mSv; ED_SD-CT 1.63 ± 0.2 mSv; p < 0.001).

CONCLUSION

C-spine CT with dose reduction of 51% showed no image quality impairment. Additional pull-down of both shoulders allowed better image quality at lower C-spine segments as compared to a standard protocol.

Comparative Study of Two Surgical Techniques for Proximal Adjacent Segment Pathology after Posterior Lumbar Interbody Fusion with Pedicle Screws: Fusion Extension using Conventional Pedicle Screw vs Cortical Bone Trajectory-Pedicle Screw (Cortical Screw)

OBJECTIVE

To present a minimally invasive surgical technique using cortical bone trajectory pedicle screws (cortical screws [CS]) for adjacent segment pathology (ASP) after lumbar fusion surgery, and to thoroughly compare postoperative outcomes of surgical techniques with either a CS or conventional pedicle screws (PS) for ASP at a 1-year follow-up.

METHODS

Among 59 patients who underwent surgical treatment for proximal ASP after lumbar fusion surgery, 53 patients who met the study criteria (group A, 31 patients with conventional technique using PS; group B, 22 patients with minimally invasive technique using CS) were enrolled in the study. The primary outcome measure was the fusion rate at 1 year after surgery, and secondary outcome measures included patient satisfaction, clinical outcomes, radiologic outcomes, and surgical outcomes and complications.

RESULTS

Fusion at 1 year postsurgery was achieved by 90% of the patients in group A with PS and 91% of those in group B with CS (P > 0.99). Patient satisfaction at 1 month postsurgery (P = 0.03) and pain intensity within 1 month postsurgery (P = 0.04) were significantly better in group B compared with group A. Regarding surgical outcomes, blood loss was significantly less, operation time and length of hospital stay were significantly shorter, and the incision was significantly shorter n group B than in group A. Other clinical parameters and outcomes were similar in the 2 groups.

CONCLUSIONS

We suggest that a minimally invasive surgical technique using CS for ASP can be a viable alternative to a conventional surgical technique using PS.

Determination of a suitable low-dose abdominopelvic CT protocol using model-based iterative reconstruction through cadaveric study

INTRODUCTION

Cadaveric studies provide a means of safely assessing new technologies and optimizing scanning prior to clinical validation. Reducing radiation exposure in a clinical setting can entail incremental dose reductions to avoid missing important clinical findings. The use of cadavers allows assessment of the impact of more substantial dose reductions on image quality. Our aim was to identify a suitable low-dose abdominopelvic CT protocol for subsequent clinical validation.

METHODS

Five human cadavers were scanned at one conventional dose and three low-dose settings. All scans were reconstructed using three different reconstruction algorithms: filtered back projection (FBP), hybrid iterative reconstruction (60% FBP and 40% adaptive statistical iterative reconstruction (ASIR40)), and model-based iterative reconstruction (MBIR). Two readers rated the image quality both quantitatively and qualitatively.

RESULTS

Model-based iterative reconstruction images had significantly better objective image noise and higher qualitative scores compared with both FBP and ASIR40 images at all dose levels. The greatest absolute noise reduction, between MBIR and FBP, of 34.3 HU (equating to a 68% reduction) was at the lowest dose level. MBIR reduced image noise and improved image quality even in CT images acquired with a mean radiation dose reduction of 62% compared with conventional dose studies reconstructed with ASIR40, with lower levels of objective image noise, superior diagnostic acceptability and contrast resolution, and comparable subjective image noise and streak artefact scores.

CONCLUSION

This cadaveric study demonstrates that MBIR reduces image noise and improves image quality in abdominopelvic CT images acquired with dose reductions of up to 62%.