Metal artefact reduction algorithm for correction of bone biopsy needle artefact in paediatric C-arm CT images: a qualitative and quantitative assessment

Evaluation of a prototype metal artifact reduction algorithm for cone beam CT in patients undergoing radioembolization

Metal artifacts notoriously pose significant challenge in computed tomography (CT), leading to inaccuracies in image formation and interpretation. Artifact reduction tools have been designed to improve cone beam computed tomography (CBCT) image quality by reducing artifacts caused by certain high-density materials. Metal artifact reduction (MAR) tools are specific algorithms that are applied during image reconstruction to minimize or eliminate artifacts degrading CBCT images. The purpose of the study is to evaluate the effect of a MAR algorithm on image quality in CBCT performed for evaluating patients before transarterial radioembolization (TARE). We retrospectively included 40 consecutive patients (aged 65 ± 13 years; 23 males) who underwent 45 CBCT examinations (Allura FD 20, XperCT Roll protocol, Philips Healthcare, Best, The Netherlands) in the setting of evaluation for TARE between January 2017 and December 2018. Artifacts caused by coils, catheters, and surgical clips were scored subjectively by four readers on a 5-point scale (1 = artifacts affecting diagnostic information to 5 = no artifacts) using a side-by-side display of uncorrected and MAR-corrected images. In addition, readers scored tumor visibility and vessel discrimination. MAR-corrected images were assigned higher scores, indicating better image quality. The differences between the measurements with and without MAR were most impressive for coils with a mean improvement of 1.6 points (95%CI [1.5 1.8]) on the 5-point likert scale, followed by catheters 1.4 points (95%CI [1.3 1.5]) and clips 0.7 points (95%CI [0.3 1.1]). Improvements for other artifact sources were consistent but relatively small (below 0.25 points on average). Interrater agreement was good to perfect (Kendall's W coefficient = 0.68-0.95) and was higher for MAR-corrected images, indicating that MAR improves diagnostic accuracy. A metal artifact reduction algorithm can improve diagnostic and interventional accuracy of cone beam CT in patients undergoing radioembolization by reducing artifacts caused by diagnostic catheters and coils, lowering interference of metal artifacts with adjacent major structures, and improving tumor visibility.

Application of a Metal Artifact Reduction Algorithm for C-Arm Cone-Beam CT: Impact on Image Quality and Diagnostic Confidence for Bronchial Artery Embolization

OBJECTIVE

The objective of this study was to evaluate the potential benefit of a dedicated cone-beam-CT streak metal artifact removal technique (SMART) in terms of both image quality and diagnostic confidence in patients undergoing bronchial artery embolization.

METHODS

A total of 17 patients were included in this retrospective study. The SMART algorithm was applied to images containing streak artifacts generated by a radiopaque intra-arterial catheter tip. Quantitative evaluation of artifact severity was performed via measurement of the Hounsfield units along a closed loop surrounding the catheter tip and was conducted in the frequency domain following the application of the discrete Fourier transform to the measured data. A high proportion of power in the low frequencies of the resulting spectrum indicated a high level of streak artifacts. Qualitative evaluation of diagnostic confidence was performed using a 4-point Likert scale.

RESULTS

Both quantitative and qualitative evaluation demonstrated a significant reduction in artifact severity using the SMART algorithm. Quantitative evaluation demonstrated a mean artifact reduction of 22.5% using SMART compared to non-SMART images (p < 0.001). Qualitative evaluation demonstrated the greatest artifact reduction at the inner and outer aortic curvature, as well as immediately surrounding the tip of the catheter. In 6 of 17 cases, the use of the SMART algorithm yielded additional clinical information, increasing mean diagnostic confidence from 3.17 to 3.78 (p < 0.001).

CONCLUSION

The SMART algorithm allows for efficient reduction of metal artifacts introduced by radiopaque catheter tips during cone-beam CT. Using this algorithm, diagnostic images of the aortic arch were significantly improved both quantitatively and qualitatively, yielding clinically relevant levels of enhanced diagnostic confidence. These results demonstrate that the SMART algorithm improves diagnostic and clinical characterization of the course of bronchial arteries on CBCT images, potentially improving the accuracy and clinical efficacy of bronchial artery embolization.

LEVEL OF EVIDENCE

3.

Real-time fluoroscopic needle guidance in the interventional radiology suite using navigational software for percutaneous bone biopsies in children

BACKGROUND

Navigational software provides real-time fluoroscopic needle guidance for percutaneous procedures in the Interventional Radiology (IR) suite.

OBJECTIVE

We describe our experience with navigational software for pediatric percutaneous bone biopsies in the IR suite and compare technical success, diagnostic accuracy, radiation dose and procedure time with that of CT-guided biopsies.

MATERIALS AND METHODS

Pediatric bone biopsies performed using navigational software (Syngo iGuide, Siemens Healthcare) from 2011 to 2016 were prospectively included and anatomically matched CT-guided bone biopsies from 2008 to 2016 were retrospectively reviewed with institutional review board approval. C-arm CT protocols used for navigational software-assisted cases included institution-developed low-dose (0.1/0.17 μGy/projection), regular-dose (0.36 μGy/projection), or a combination of low-dose/regular-dose protocols. Estimated effective radiation dose and procedure times were compared between software-assisted and CT-guided biopsies.

RESULTS

Twenty-six patients (15 male; mean age: 10 years) underwent software-assisted biopsies (15 pelvic, 7 lumbar and 4 lower extremity) and 33 patients (13 male; mean age: 9 years) underwent CT-guided biopsies (22 pelvic, 7 lumbar and 4 lower extremity). Both modality biopsies resulted in a 100% technical success rate. Twenty-five of 26 (96%) software-assisted and 29/33 (88%) CT-guided biopsies were diagnostic. Overall, the effective radiation dose was significantly lower in software-assisted than CT-guided cases (3.0±3.4 vs. 6.6±7.7 mSv, P=0.02). The effective dose difference was most dramatic in software-assisted cases using low-dose C-arm CT (1.2±1.8 vs. 6.6±7.7 mSv, P=0.001) or combined low-dose/regular-dose C-arm CT (1.9±2.4 vs. 6.6±7.7 mSv, P=0.04), whereas effective dose was comparable in software-assisted cases using regular-dose C-arm CT (6.0±3.5 vs. 6.6±7.7 mSv, P=0.7). Mean procedure time was significantly lower for software-assisted cases (91±54 vs. 141±68 min, P=0.005).

CONCLUSION

In our experience, navigational software technology in the IR suite is a promising alternative to CT guidance for pediatric bone biopsies providing comparable technical success and diagnostic accuracy with lower radiation dose and procedure time, in addition to providing real-time fluoroscopic needle guidance.

CAT & MAUS: A novel system for true dynamic motion measurement of underlying bony structures with compensation for soft tissue movement

Optoelectronic motion capture systems are widely employed to measure the movement of human joints. However, there can be a significant discrepancy between the data obtained by a motion capture system (MCS) and the actual movement of underlying bony structures, which is attributed to soft tissue artefact. In this paper, a computer-aided tracking and motion analysis with ultrasound (CAT & MAUS) system with an augmented globally optimal registration algorithm is presented to dynamically track the underlying bony structure during movement. The augmented registration part of CAT & MAUS was validated with a high system accuracy of 80%. The Euclidean distance between the marker-based bony landmark and the bony landmark tracked by CAT & MAUS was calculated to quantify the measurement error of an MCS caused by soft tissue artefact during movement. The average Euclidean distance between the target bony landmark measured by each of the CAT & MAUS system and the MCS alone varied from 8.32mm to 16.87mm in gait. This indicates the discrepancy between the MCS measured bony landmark and the actual underlying bony landmark. Moreover, Procrustes analysis was applied to demonstrate that CAT & MAUS reduces the deformation of the body segment shape modeled by markers during motion. The augmented CAT & MAUS system shows its potential to dynamically detect and locate actual underlying bony landmarks, which reduces the MCS measurement error caused by soft tissue artefact during movement.