ArticleCureus2024
Comprehensive Evaluation of Pulmonary Masses Using Multi-detector CT: Correlating Morphological Features With CT-Guided Histopathological Findings for Enhanced Diagnostic Accuracy.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLung masses pose a significant diagnostic challenge due to their diverse causes, from benign hamartomas to malignant bronchogenic carcinoma. Multi-detector CT (MDCT) is essential in evaluating these masses, offering detailed morphological insights to help differentiate between benign and malignant lesions. However, a definitive diagnosis often requires histopathological confirmation. CT-guided biopsy is crucial, providing a minimally invasive method to obtain tissue samples and thus guiding clinical management and treatment decisions.
objectiveThe primary objective of this study was to assess the diagnostic accuracy of MDCT in differentiating between benign and malignant lung mass lesions. The study focused on evaluating the characteristic features of lung masses on MDCT that aid in this differentiation, correlating imaging findings with histopathological results from CT-guided biopsies, and determining the overall diagnostic utility of MDCT in thoracic lesions. METHODOLOGY: This hospital-based observational study was conducted over a period of 17 months. The study included 52 patients with thoracic lesions, identified through imaging techniques such as chest radiographs and CT scans. These patients underwent CT-guided biopsy, with tissue samples sent for histopathological examination. Inclusion criteria involved patients with clinically and radiographically diagnosed lung masses, while exclusion criteria included those who did not consent, had contraindications to contrast media, or had conditions such as severe respiratory distress or coagulopathy. The data were analyzed using descriptive statistics, with efficacy measures such as yield and failure rates of CT-guided biopsies and validation measures like sensitivity, specificity, positive predictive value, and negative predictive value for MDCT.
resultsThe study included 52 patients (50% male, 50% female), aged 16-80, with the most common age group being 51-60 years. Lesions were mainly in the lung parenchyma (65.38%), followed by the mediastinum (15.38%), hilar region (11.54%), and pleura (7.69%). MDCT evaluation classified 84.44% of the lesions as malignant, characterized by irregular contours, inhomogeneous texture, and contrast enhancement, while 15.55% were benign. Histopathology confirmed 42 malignant lesions, with squamous cell carcinoma being the most prevalent. Benign lesions included abscesses, tuberculosis, and pneumonitis. The study achieved a 100% success rate for CT-guided biopsy, with one minor complication (pneumothorax). The diagnostic accuracy of MDCT was notable, with a sensitivity of 100% for detecting malignancies, a specificity of 77.78%, a positive predictive value of 87.50%, and a negative predictive value of 100%, emphasizing its effectiveness in thoracic lesion evaluation.
conclusionMDCT is a highly effective tool in the evaluation of lung masses, providing critical information that aids in distinguishing between benign and malignant lesions. When combined with CT-guided biopsy, it offers a reliable method for obtaining diagnostic tissue samples, with a high degree of accuracy and a low complication rate. The study underscores the importance of integrating imaging and histopathological findings in the management of thoracic lesions, ultimately enhancing diagnostic precision and informing appropriate clinical interventions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.