Complications during CT-Guided Lung Nodule Localization: Impact of Needle Insertion Depth and Patient Characteristics

Chiang, Han-Sun; Chen, Liang-Kuang; Hsieh, Wen-Shyong; Tang, Yun-Xuan; Lo, Chun‐Yu

doi:10.3390/diagnostics13111881

Cited by 2 publications

(1 citation statement)

References 31 publications

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“…It is very versatile, and can be applicable across various organs, ranging from superficial soft tissue lesions to deep-seated lesions within the thoracic or abdominal cavities [9]. However, this method is associated with significant risk of complications; the most common are pneumothorax and pulmonary hemorrhaging, along with exposure to radiation [4,10]. There are plenty of risk factors for the development of complications as well, including increased number of punctures, wider insertion angle of the needle, small lesion size, greater lesion depth, and long biopsy path [11].…”

Section: Introductionmentioning

confidence: 99%

Mixed Reality Biopsy Navigation System Utilizing Markerless Needle Tracking and Imaging Data Superimposition

Trojak,

Stanuch,

Kurzyna

et al. 2024

Cancers

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Exact biopsy planning and careful execution of needle injection is crucial to ensure successful procedure completion as initially intended while minimizing the risk of complications. This study introduces a solution aimed at helping the operator navigate to precisely position the needle in a previously planned trajectory utilizing a mixed reality headset. A markerless needle tracking method was developed by integrating deep learning and deterministic computer vision techniques. The system is based on superimposing imaging data onto the patient’s body in order to directly perceive the anatomy and determine a path from the selected injection site to the target location. Four types of tests were conducted to assess the system’s performance: measuring the accuracy of needle pose estimation, determining the distance between injection sites and designated targets, evaluating the efficiency of material collection, and comparing procedure time and number of punctures required with and without the system. These tests, involving both phantoms and physician participation in the latter two, demonstrated the accuracy and usability of the proposed solution. The results showcased a significant improvement, with a reduction in number of punctures needed to reach the target location. The test was successfully completed on the first attempt in 70% of cases, as opposed to only 20% without the system. Additionally, there was a 53% reduction in procedure time, validating the effectiveness of the system.

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Section: Introductionmentioning

confidence: 99%

Mixed Reality Biopsy Navigation System Utilizing Markerless Needle Tracking and Imaging Data Superimposition

Trojak,

Stanuch,

Kurzyna

et al. 2024

Cancers

View full text Add to dashboard Cite

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Analysis of risk factors for pneumothorax after particle implantation in the treatment of advanced lung cancer after surgery and establishment of a nomogram prediction model

Ding,

Hao,

Wang

et al. 2024

Front. Med.

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ObjectiveTo analyze the risk factors for pneumothorax after particle implantation in the treatment of advanced lung cancer and to construct and validate a nomogram prediction model.MethodsA retrospective analysis was conducted on 148 patients who underwent 125I particle implantation for advanced lung cancer at the *** from December 2022 to December 2023. Potential risk factors were identified using univariate logistic regression analysis, followed by a multivariate logistic regression analysis to evaluate the predictive factors for pneumothorax. Interaction effects between variables were studied and incorporated into the model construction. ROC curves and nomograms were generated for visualization. Calibration analysis was performed, and the corresponding net benefit was calculated to adjust the predictive model.ResultsAmong the 148 patients, 58 (39.19%) experienced pneumothorax, with a mean age of 62.5 (55.25, 70) years. Multivariate analysis showed that the angle between the puncture needle and the pleura < 50° (P = 0.002, OR: 3.908, CI: 1.621–9.422), preoperative CT suggesting emphysema (P = 0.002, OR: 3.798, CI: 1.600–9.016), atelectasis (P = 0.009, OR: 3.156, CI: 1.331–7.481), and lesion located in the left lung fissure (P = 0.008, OR: 4.675, CI: 14.683) were independent risk factors for pneumothorax after particle implantation in the treatment of advanced lung cancer. Preoperative CT suggesting lesions in the left lung fissure or suggesting emphysema had a significant impact in the nomogram, with probabilities of pneumothorax occurrence at 40% and 38%, respectively. The predictive AUC for the above four risk factors for pneumothorax after particle implantation in the treatment of lung adenocarcinoma was 0.837 (95% CI: 0.767–0.908). When the Youden index was 0.59, the sensitivity was 85.56%, specificity was 74.13%, accuracy was 81.01%, positive predictive value was 83.69%, and negative predictive value was 76.78%.ConclusionThe angle between the puncture needle and the pleura < 50°, preoperative CT suggesting emphysema, atelectasis, and lesion located in the left lung fissure are independent risk factors for pneumothorax after particle implantation in the treatment of advanced lung cancer. Preoperative planning of the puncture path should avoid lung bullae, interlobar fissures, areas of severe emphysema, and atelectasis.

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Complications during CT-Guided Lung Nodule Localization: Impact of Needle Insertion Depth and Patient Characteristics

Cited by 2 publications

References 31 publications

Mixed Reality Biopsy Navigation System Utilizing Markerless Needle Tracking and Imaging Data Superimposition

Mixed Reality Biopsy Navigation System Utilizing Markerless Needle Tracking and Imaging Data Superimposition

Analysis of risk factors for pneumothorax after particle implantation in the treatment of advanced lung cancer after surgery and establishment of a nomogram prediction model

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