Low-dose CT with tin filter combined with iterative metal artefact reduction for guiding lung biopsy

A systematic review and meta-analysis of randomized controlled trials comparing low-dose versus standard-dose computed tomography-guided lung biopsy

BACKGROUND

Despite the existence of several Randomized Controlled Trials (RCTs) investigating Low-Dose Computed Tomography (LDCT) as a guide in lung biopsies, conclusive findings remain elusive. To address this contention, we conducted a systematic review and meta-analysis to evaluate the efficacy and safety of LDCT-guided lung biopsies.

METHODS

A comprehensive search across major databases identified RCTs comparing the effectiveness of LDCT-guided with Standard-Dose Computed Tomography (SDCT)-guided lung biopsies. Subsequently, we utilized a random-effects model meta-analysis to assess diagnostic accuracy, radiation dose, operation duration, and clinical complications associated with these procedures.

RESULTS

Out of 292 scrutinized studies, six RCTs representing 922 patients were included in the final analysis. Results indicated the differences between the LDCT and SDCT groups were not different with statistical significance in terms of diagnostic accuracy rates (Intent-to-Treat (ITT) populations: Relative Risk (RR) 1.01, 95% Confidence interval [CI] 0.97-1.06, p = 0.61; Per-Protocol (PP) populations: RR 1.01, 95% CI 0.98-1.04, p = 0.46), incidence of pneumothorax (RR 1.00, 95% CI 0.75-1.35, p = 0.98), incidence of hemoptysis (RR 0.95, 95% CI 0.63-1.43, p = 0.80), and operation duration (minutes) (Mean Differences [MD] -0.34, 95% CI -1.67-0.99, p = 0.61). Notably, LDCT group demonstrated a lower radiation dose (mGy·cm) with statistical significance (MD -188.62, 95% CI -273.90 to -103.34, p < 0.0001).

CONCLUSIONS

The use of LDCT in lung biopsy procedures demonstrated equivalent efficacy and safety to standard methods while notably reducing patient radiation exposure.

Fusing Diverse Decision Rules in 3D-Radiomics for Assisting Diagnosis of Lung Adenocarcinoma

This study aimed to develop an interpretable diagnostic model for subtyping of pulmonary adenocarcinoma, including minimally invasive adenocarcinoma (MIA), adenocarcinoma in situ (AIS), and invasive adenocarcinoma (IAC), by integrating 3D-radiomic features and clinical data. Data from multiple hospitals were collected, and 10 key features were selected from 1600 3D radiomic signatures and 11 radiological features. Diverse decision rules were extracted using ensemble learning methods (gradient boosting, random forest, and AdaBoost), fused, ranked, and selected via RuleFit and SHAP to construct a rule-based diagnostic model. The model's performance was evaluated using AUC, precision, accuracy, recall, and F1-score and compared with other models. The rule-based diagnostic model exhibited excellent performance in the training, testing, and validation cohorts, with AUC values of 0.9621, 0.9529, and 0.8953, respectively. This model outperformed counterparts relying solely on selected features and previous research models. Specifically, the AUC values for the previous research models in the three cohorts were 0.851, 0.893, and 0.836. It is noteworthy that individual models employing GBDT, random forest, and AdaBoost demonstrated AUC values of 0.9391, 0.8681, and 0.9449 in the training cohort, 0.9093, 0.8722, and 0.9363 in the testing cohort, and 0.8440, 0.8640, and 0.8750 in the validation cohort, respectively. These results highlight the superiority of the rule-based diagnostic model in the assessment of lung adenocarcinoma subtypes, while also providing insights into the performance of individual models. Integrating diverse decision rules enhanced the accuracy and interpretability of the diagnostic model for lung adenocarcinoma subtypes. This approach bridges the gap between complex predictive models and clinical utility, offering valuable support to healthcare professionals and patients.

Establishment of local diagnostic reference levels for CT colonography at a tertiary hospital

Background

Diagnostic reference levels (DRLs) are an important metric in identifying abnormally high radiation doses in diagnostic examinations. National DRLs for CT colonography do not currently exist in South Africa, but there are efforts to collect data for a national DRL project.

Objectives

This study investigated radiation doses for CT colonography in adult patients at a large tertiary hospital in South Africa with the aim of setting local DRLs.

Method

Patient data from two CT scanners (Philips Ingenuity and Siemens Somatom go.Top) in the period March 2020 - March 2023 were obtained from the hospital's picture archiving and communication system (PACS) (n = 115). Analysis involved determining the median computed tomography dose index-volume (CTDIvol) and dose-length product (DLP) values. The findings were compared with DRLs established internationally.

Results

Ingenuity median CTDIvol was 20 mGy and DLP was 2169 mGy*cm; Somatom median CTDIvol was 6 mGy and DLP was 557 mGy*cm. Ingenuity exceeded the United Kingdom's (UK) recommended DRLs by 82% and 214%, respectively. Somatom median CTDIvol and DLP were 45% and 19% lower than UK NDRLs.

Conclusion

Somatom's tin filter and other dose reduction features provided significant dose reduction. These data were used to set DRLs for CT colonography at the hospital; CTDIvol: 6 mGy and DLP: 557 mGy*cm.

Contribution

In addition to informing radiation protection practices at the level of the institution, the established local DRLs contribute towards implementing regional and national DRLs.

Ultra-low dose CT scanning for PET/CT

BACKGROUND

The use of computed tomography (CT) for attenuation correction (AC) in whole-body PET/CT can result in a significant contribution to radiation exposure. This can become a limiting factor for reducing considerably the overall radiation exposure of the patient when using the new long axial field of view (LAFOV) PET scanners. However, recent CT technology have introduced features such as the tin (Sn) filter, which can substantially reduce the CT radiation dose.

PURPOSE

The purpose of this study was to investigate the ultra-low dose CT for attenuation correction using the Sn filter together with other dose reduction options such as tube current (mAs) reduction. We explore the impact of dose reduction in the context of AC-CT and how it affects PET image quality.

METHODS

The study evaluated a range of ultra-low dose CT protocols using five physical phantoms that represented a broad collection of tissue electron densities. A long axial field of view (LAFOV) PET/CT scanner was used to scan all phantoms, applying various CT dose reduction parameters such as reducing tube current (mAs), increasing the pitch value, and applying the Sn filter. The effective dose resulting from the CT scans was determined using the CTDIVol reported by the scanner. Several voxel-based and volumes of interest (VOI)-based comparisons were performed to compare the ultra-low dose CT images, the generated attenuation maps, and corresponding PET images against those images acquired with the standard low dose CT protocol. Finally, two patient datasets were acquired using one of the suggested ultra-low dose CT settings.

RESULTS

By incorporating the Sn filter and adjusting mAs to the lowest available value, the radiation dose in CT images of PBU-60 phantom was significantly reduced; resulting in an effective dose of nearly 2% compared to the routine low dose CT protocols currently in clinical use. The assessment of PET images using VOI and voxel-based comparisons indicated relative differences (RD%) of under 6% for mean activity concentration (AC) in the torso phantom and patient dataset and under 8% for a source point in the CIRS phantom. The maximum RD% value of AC was 14% for the point source in the CIRS phantom. Increasing the tube current from 6 mAs to 30 mAs in patients with high BMI, or with arms down, can suppress the photon starvation artifact, whilst still preserving a dose reduction of 90%.

CONCLUSIONS

Introducing a Sn filter in CT imaging lowers radiation dose by more than 90%. This reduction has minimal effect on PET image quantification at least for patients without Body Mass Index (BMI) higher than 30. Notably, this study results need validation using a larger clinical PET/CT dataset in the future, including patients with higher BMI.

Systematic review and meta-analysis of low-dose CT-driven biopsy for pulmonary nodules

Introduction

The diagnosis of pulmonary nodules (PNs) has traditionally relied on computed tomography (CT)-guided biopsy. To reduce radiation exposure, low-dose CT-guided PN biopsy has been employed.

Aim

This meta-analysis aimed at evaluating the efficacy and safety of low-dose CT-guided biopsy in the diagnosis of PNs.

Material and methods

PubMed, Web of Science, and Wanfang were searched for relevant articles until June 2023. Comparing low-dose CT to normal-dose CT, we considered factors such as diagnostic yield, diagnostic accuracy, biopsy process time, dose-length product (DLP) value, the frequency of pneumothorax and pulmonary bleeding, and the frequency with which complications necessitated the placement of a chest tube.

Results

This meta-analysis included data from a total of 6 investigations. There was a total of 459 patients who had a CT-guided PN biopsy performed at a low dosage, and 384 patients who had a normal-dose CT-guided PN biopsy. There were no statistically significant differences between the low-dose CT and normal-dose CT groups in terms of diagnostic accuracy (p = 0.08), diagnostic yield (p = 0.55), biopsy procedure duration (p = 0.30), pneumothorax (p = 0.61), pulmonary hemorrhage (p = 0.29), or complications requiring a chest tube (p = 0.48). Low-dose CT patients obtained a DLP that was 91% lower than those in the standard-dose CT group (p = 0.01). According to Egger's test, there is a significant possibility of publication bias in DLP (p = 0.034).

Conclusions

The diagnostic and safety results of low-dose CT-driven PN biopsy are equivalent to those of the standard one, although patients are much less exposed to radiation.

An ultra-low-dose protocol for computed tomography-guided lung radiofrequency ablations

To evaluate the safety and efficacy of ultra-low-dose (ULD) protocol for computed tomography (CT)-guided lung radiofrequency ablation (RFA). Patients who had undergone lung RFA between November 2017 and January 2021 were consecutively and retrospectively included. Thirty patients were treated using a conventional standard protocol (SP), including helical acquisitions with mA automatic adjustment and sequential CT at 80 kVp; and 31, with a ULD protocol defined with helical acquisitions with fixed mA and sequential series at 100 kVp. These parameters were selected from those used for a diagnostic lung low-dose CT scanner. Patient characteristics, dose indicators, technical efficacy (minimal margin [MM], recurrence during follow-up), and complications (pneumothorax, alveolar haemorrhage, and haemoptysis) were recorded. We included 61 patients (median age, 65 [54-73] and 33 women), with no significant differences according to the type of protocol, except for the type of anaesthesia. Even if the number of helical acquisitions did not significantly change, all dose indicators significantly decreased by 1.5-fold-3-fold. The median dose-length-product and effective dose, with their ranges, respectively, were 465 mGy cm (315-554) and 6.5 mSv (4.4-7.8) in the SP group versus 178 mGy cm (154-267) and 2.5 mSv (2.2-3.7) in the ULD group, (p< 001). The ULD group exhibited lower intraoperator variability and better interoperator alignment than those of the SP group. The MM was not significantly different between the two groups (4.6 mm versus 5 mm,p= 16). One local recurrence was observed in each group at 8 months in the SP and at one year in the ULD group (p= 1). The complication rates did not differ significantly. Implementing an ULD protocol during lung RFA may provide similar efficacy, a reduction of dose indicators, and intra- and interoperator variability, without increasing complication rates, compared to those associated with an SP.