Lung cancer is the leading cause of cancer-related mortality worldwide, accounting for approximately 1.8 million deaths each year, with a rising incidence in low- and middle-income countries [1,2]. The detection of pulmonary lesions such as nodules and masses has increased substantially with the widespread availability and use of multidetector computed tomography. These lesions include a wide spectrum of pathologies ranging from inflammatory and infectious granulomas to primary and metastatic malignancies. Accurate differentiation between benign and malignant pulmonary lesions is critical because it directly influences the choice between conservative follow-up, medical management, and invasive surgical or oncological treatment. Misclassification can lead to either unnecessary thoracotomy for benign disease or delayed diagnosis of potentially curable lung cancer [3,4]. Computed tomography of the thorax is the principal non-invasive imaging modality for evaluating pulmonary lesions. It provides detailed information about lesion size, margins, internal attenuation, calcification, cavitation, contrast enhancement, and associated findings such as lymphadenopathy and pleural involvement [5,6]. Malignant lesions typically demonstrate spiculated or lobulated margins, irregular wall thickening, heterogeneous enhancement, and regional lymphadenopathy. In contrast, benign lesions often show smooth margins, central or diffuse calcification, fat attenuation, and stable size over time [7,8]. However, substantial overlap exists in the CT appearances of benign and malignant lesions, particularly in regions where granulomatous diseases such as tuberculosis are endemic. In India, pulmonary tuberculosis and other inflammatory conditions frequently produce CT features that mimic malignancy, including irregular margins, cavitation, and mediastinal lymphadenopathy [9,10]. Histopathological examination of tissue obtained by CT-guided transthoracic needle biopsy, bronchoscopic biopsy, or surgical resection remains the definitive reference standard for diagnosing pulmonary lesions [11,12]. Although histopathology is accurate, it is invasive, carries a risk of complications, and may be technically difficult for small or centrally located lesions. Therefore, a reliable non-invasive method such as CT thorax that can accurately predict malignancy would help in triaging patients, reducing unnecessary biopsies, and expediting treatment for malignant lesions. The diagnostic performance of CT is, however, influenced by the prevalence of benign disease, reader experience, lesion characteristics, and CT protocols [13,14]. In the Indian healthcare setting, pulmonary tuberculosis and other infections are common, and the burden of lung cancer is increasing. Data on the diagnostic accuracy of CT thorax in this context are limited but necessary to guide clinical decision-making. The present study was therefore conducted to evaluate the diagnostic accuracy of CT thorax in differentiating benign and malignant pulmonary lesions using histopathology as the reference standard in a tertiary care hospital in Tamil Nadu, India [15,16]. OBJECTIVE The primary objective of this study was to determine the diagnostic accuracy of contrast-enhanced CT thorax in differentiating benign from malignant pulmonary lesions using histopathology as the reference standard. The diagnostic performance was assessed in terms of sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy. The secondary objective was to identify the individual CT morphological features that are most strongly associated with malignancy, including lesion size, margin characteristics, presence of calcification, cavitation, lymphadenopathy, pleural involvement, and contrast enhancement pattern. These findings were intended to assist radiologists and clinicians in the non-invasive assessment of pulmonary lesions and to guide the appropriate use of invasive diagnostic procedures.

This was a prospective cross-sectional study conducted in the Department of Radio-diagnosis in collaboration with the Department of Pathology at a tertiary care hospital in Tamil Nadu, India. The study period extended from November 2021 to August 2022. A total of 40 consecutive patients with suspected pulmonary lesions on chest radiography or ultrasonography were enrolled after obtaining written informed consent. Ethical approval was obtained from the Institutional Ethics Committee prior to commencement of the study. All procedures were performed in accordance with the ethical standards of the institutional research committee and the Declaration of Helsinki. All patients underwent contrast-enhanced computed tomography of the thorax using a 64-slice multidetector CT scanner. Scanning parameters were as follows: tube voltage 120 kVp, automatic tube current modulation, slice thickness 1.25 mm, reconstruction interval 0.625 mm, and pitch 0.9. Non-ionic iodinated contrast material (iohexol 300 mg I/mL) was administered intravenously at a dose of 1.5 mL/kg body weight at a rate of 3 mL/s, followed by a saline flush. Images were acquired in the portal venous phase at approximately 60–70 seconds after contrast injection. The CT images were reviewed by a radiologist with more than five years of experience who was blinded to the clinical history and histopathological results. Lesions were categorized as benign or malignant based on predefined morphological criteria including margin characteristics, internal attenuation, presence of calcification, cavitation, contrast enhancement, and associated lymphadenopathy or pleural involvement. Histopathological confirmation was obtained by CT-guided transthoracic needle biopsy, bronchoscopic biopsy, or surgical resection depending on lesion location and clinical condition. The histopathological diagnosis was considered the reference standard. Lesions were classified as malignant if the histopathology revealed primary lung carcinoma, small cell carcinoma, or metastatic malignancy. Lesions were classified as benign if histopathology revealed granulomatous inflammation, tuberculosis, hamartoma, organizing pneumonia, inflammatory pseudotumor, abscess, or other non-neoplastic conditions. Inclusion Criteria • Patients aged 18 years and above. • Patients with pulmonary nodules or masses detected on chest radiography or CT. • Patients who provided informed consent and underwent both CT thorax and histopathological evaluation. Exclusion Criteria • Patients with a known history of previous biopsy or surgical resection of the pulmonary lesion. • Patients who had received chemotherapy or radiotherapy for the pulmonary lesion before CT. • Pregnant or lactating women. • Patients with contraindications to iodinated contrast media such as severe renal impairment or previous anaphylactic reaction. • Patients in whom an adequate histopathological sample could not be obtained. Data Collection Procedure Demographic data, clinical history including smoking status, and CT findings were recorded on a structured proforma. The CT features evaluated included lesion size, location, margins, presence of calcification, cavitation, ground-glass opacity, spiculation, lobulation, lymphadenopathy, pleural effusion or thickening, and contrast enhancement pattern. Histopathology reports were retrieved after the CT interpretation was completed to ensure blinding. The final diagnosis was correlated with CT findings. Statistical Data Analysis Data were entered into Microsoft Excel and analyzed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA). Categorical variables were expressed as frequencies and percentages, and continuous variables as mean ± standard deviation. The chi-square test or Fisher’s exact test was used to compare categorical variables between benign and malignant groups, and the independent t-test was used for continuous variables. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated with 95% confidence intervals. A p-value <0.05 was considered statistically significant.

A total of 40 patients were included in the final analysis. The mean age of the study population was 55.4 ± 12.3 years, and 27 patients (67.5%) were male. Histopathology confirmed 26 malignant lesions (65.0%) and 14 benign lesions (35.0%). Among malignant lesions, adenocarcinoma was the most common histological type (12 cases), followed by squamous cell carcinoma (7 cases), small cell carcinoma (3 cases), metastatic carcinoma (3 cases), and large cell carcinoma (1 case). Among benign lesions, tuberculosis was the most common diagnosis (5 cases), followed by hamartoma (3 cases), organizing pneumonia (2 cases), inflammatory pseudotumor (2 cases), lung abscess (1 case), and sarcoidosis (1 case). Malignant lesions were significantly larger than benign lesions, with mean sizes of 3.4 ± 1.5 cm versus 2.1 ± 1.0 cm (p=0.006). Smoking was more frequent in patients with malignant lesions but did not reach statistical significance (p=0.10). Baseline characteristics are summarized in Table 1. The CT morphological features according to histopathological diagnosis are presented in Table 2. Spiculated margins were observed in 76.9% of malignant lesions compared with 21.4% of benign lesions (p<0.001). Lobulated margins were seen in 69.2% of malignant and 28.6% of benign lesions (p=0.014). Calcification was significantly more common in benign lesions (42.9%) than in malignant lesions (7.7%) (p=0.008). Lymphadenopathy was present in 42.3% of malignant lesions versus only 7.1% of benign lesions (p=0.021). Cavitation, ground-glass opacity, and pleural effusion or thickening did not show statistically significant differences between benign and malignant lesions. Heterogeneous contrast enhancement was more frequently associated with malignancy (84.6%) than with benign lesions (21.4%) (p<0.001). The cross-tabulation of CT diagnosis against histopathology is shown in Table 3. CT correctly identified 24 of 26 malignant lesions and 10 of 14 benign lesions. There were 4 false-positive results and 2 false-negative results. The sensitivity, specificity, positive predictive value, negative predictive value, and overall diagnostic accuracy of CT thorax were 92.3% (95% CI 74.9–99.1), 71.4% (95% CI 41.9–91.6), 85.7% (95% CI 67.3–96.0), 83.3% (95% CI 51.6–97.9), and 85.0% (95% CI 70.2–94.3), respectively. The positive likelihood ratio was 3.23 and the negative likelihood ratio was 0.11. Table 1: Baseline demographic, clinical, and lesion characteristics of the study population (N=40) Characteristic Total (n=40) Benign (n=14) Malignant (n=26) p-value Age (years), mean ± SD 55.4 ± 12.3 48.2 ± 13.1 59.6 ± 10.4 0.008 Sex, n (%) 0.31 Male 27 (67.5) 8 (57.1) 19 (73.1) Female 13 (32.5) 6 (42.9) 7 (26.9) Smoking, n (%) 24 (60.0) 6 (42.9) 18 (69.2) 0.10 Lesion size (cm), mean ± SD 2.9 ± 1.4 2.1 ± 1.0 3.4 ± 1.5 0.006 Lesion location, n (%) 0.18 Upper lobe 20 (50.0) 5 (35.7) 15 (57.7) Middle/lower lobe 20 (50.0) 9 (64.3) 11 (42.3) Table 2: CT morphological features in benign and malignant pulmonary lesions CT feature Benign (n=14), n (%) Malignant (n=26), n (%) p-value Spiculated margins 3 (21.4) 20 (76.9) <0.001 Lobulated margins 4 (28.6) 18 (69.2) 0.014 Calcification 6 (42.9) 2 (7.7) 0.008 Cavitation 2 (14.3) 6 (23.1) 0.51 Ground-glass opacity 5 (35.7) 8 (30.8) 0.75 Lymphadenopathy 1 (7.1) 11 (42.3) 0.021 Pleural effusion/thickening 2 (14.3) 9 (34.6) 0.16 Heterogeneous enhancement 3 (21.4) 22 (84.6) <0.001 Table 3: Diagnostic performance of CT thorax compared with histopathology CT diagnosis Malignant on histopathology Benign on histopathology Total Malignant 24 4 28 Benign 2 10 12 Total 26 14 40

The present study evaluated the diagnostic accuracy of contrast-enhanced CT thorax in distinguishing benign from malignant pulmonary lesions in a tertiary care hospital in Tamil Nadu. The observed sensitivity of 92.3% and specificity of 71.4% indicate that CT is highly sensitive for detecting malignancy but only moderately specific. The overall accuracy of 85.0% is consistent with previously reported values. A meta-analysis by Cronin et al. reported a pooled sensitivity of approximately 82–93% and specificity of 68–80% for CT in characterizing solitary pulmonary nodules [9]. Similarly, Kim et al. found that CT morphological features had good diagnostic performance, though specificity was limited by overlap with granulomatous disease [13]. The high sensitivity in our study suggests that a negative CT result can substantially reduce the probability of malignancy, but the moderate specificity indicates that a positive CT result should be interpreted with caution, particularly in areas with a high prevalence of benign inflammatory lesions. Several CT features were significantly associated with malignancy. Spiculated margins, lobulation, lymphadenopathy, and heterogeneous enhancement were more frequent in malignant lesions, while calcification was more frequent in benign lesions. These findings are in agreement with earlier studies [6,7,10]. Spiculation reflects desmoplastic reaction and irregular tumor infiltration, and it is one of the most reliable predictors of malignancy. Calcification, especially central, laminated, or popcorn-type, is a well-known benign feature, although eccentric calcification can occasionally be seen in malignant lesions [7,8]. In our study, cavitation and ground-glass opacity did not significantly differentiate benign from malignant lesions, likely because cavitation is common in both tuberculous cavities and cavitating squamous cell carcinoma, while ground-glass opacity may represent either inflammatory or early neoplastic processes. The high prevalence of tuberculosis in this region may have contributed to the reduced specificity of CT, as granulomatous inflammation often produces irregular margins, cavitation, and lymphadenopathy that mimic malignancy [9,10]. The diagnostic performance observed in this study has important clinical implications. The high negative predictive value of 83.3% suggests that CT can be useful for selecting patients who may be safely observed with serial imaging rather than undergoing immediate invasive biopsy. However, the false-positive rate of 28.6% highlights the need for histological confirmation before initiating definitive treatment such as surgery, chemotherapy, or radiotherapy. Guidelines from the Fleischner Society and the British Thoracic Society recommend risk stratification based on CT features, patient age, and smoking history, but they also emphasize that CT alone cannot definitively differentiate all benign and malignant lesions [3,5]. In our setting, CT-guided transthoracic needle biopsy remains an important tool for obtaining tissue confirmation [14,15]. The combination of clinical risk factors, CT morphology, and, when available, metabolic imaging such as PET-CT may improve diagnostic confidence and reduce unnecessary procedures [9]. The results of this study support the continued use of CT thorax as a first-line imaging investigation, but histopathology remains the gold standard for definitive diagnosis. Limitations of the Study This study had several limitations. First, the sample size of 40 patients was relatively small, which may limit the generalizability of the findings and the precision of the estimates, particularly for subgroup analyses of individual CT features. Second, the study was conducted in a single tertiary care hospital, and the results may not be applicable to other settings with different patient populations, disease prevalence, or imaging protocols. Third, there may have been selection bias because only patients who underwent both CT and histopathological evaluation were included, potentially excluding lesions that were clearly benign on imaging and not biopsied. Fourth, the CT interpretation was performed by a single radiologist, and interobserver variability was not assessed. Fifth, the study used contrast-enhanced CT, which may not be feasible in all patients, particularly those with renal impairment or contrast allergy. Finally, although histopathology was considered the reference standard, the method of tissue sampling varied among patients, and in some cases, sampling error may have influenced the final diagnosis. Acknowledgement We thank the patients who participated in this study and the departments of Radio-diagnosis and Pathology for their support. We are grateful to the technical staff of the CT unit and the pathology laboratory for their assistance with image acquisition and tissue processing. We also acknowledge the institutional ethics committee for approving this study and providing valuable guidance.

The present study demonstrated that CT thorax has high sensitivity, moderate specificity, and good overall diagnostic accuracy in differentiating benign from malignant pulmonary lesions using histopathology as the reference standard. The high sensitivity and negative predictive value indicate that CT can be reliably used to identify patients with a low probability of malignancy who may be managed with conservative follow-up. However, the moderate specificity and positive predictive value reflect the considerable overlap in CT features between benign and malignant lesions, particularly in a tuberculosis-endemic setting. Spiculated margins, lobulated margins, lymphadenopathy, heterogeneous enhancement, and absence of calcification were significantly associated with malignancy and may help radiologists to improve diagnostic confidence. Despite the valuable role of CT thorax in the initial evaluation of pulmonary lesions, histopathological confirmation remains essential for definitive diagnosis. The findings of this study support the integration of CT findings with clinical risk factors and histopathological evaluation to guide appropriate management. Further multicentric studies with larger sample sizes, multiple readers, and standardized CT protocols are recommended to validate these results and to evaluate the incremental value of advanced techniques such as CT texture analysis, dual-energy CT, and radiomics in differentiating benign from malignant pulmonary lesions.

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