During chest imaging tests, pulmonary nodules—small, spherical opacities inside the lung parenchyma—are frequently found. Numerous clinical diseases, from benign inflammatory lesions and granulomas to primary lung cancers and metastatic tumours, may be represented by these nodules [1]. The detection of pulmonary nodules, especially small lesions that might not be seen on traditional chest radiography, has greatly improved with the growing use of computed tomography (CT) in routine clinical practice. Because prompt diagnosis can enable optimal clinical therapy and improve outcomes for individuals with lung cancer, early detection and characterisation of pulmonary nodules are essential [2, 3]. One of the biggest causes of cancer-related death worldwide is still lung cancer. The stage of lung cancer at diagnosis has a major impact on the prognosis; early-stage disease has far higher survival rates than advanced-stage disease. As a result, screening programs for lung cancer and routine diagnostic assessments depend heavily on imaging modalities that can identify tiny pulmonary nodules at an early stage. For detecting lung nodules and evaluating their size, shape, location, and growth characteristics, computed tomography is currently thought to be the most sensitive imaging method [4-5]. Conventional standard-dose CT (SDCT) is linked to ionising radiation exposure notwithstanding its diagnostic benefits. Concerns about possible long-term health consequences are raised by the possibility of significant cumulative radiation exposure from repeated CT scans conducted during screening, follow-up, and surveillance. These worries have spurred efforts to create imaging techniques that reduce radiation exposure while maintaining lesion detectability and diagnostic picture quality. By optimising scanning parameters and using sophisticated image reconstruction techniques, low-dose CT (LDCT) has become a viable substitute that drastically lowers radiation exposure [6, 7]. The efficacy of LDCT in identifying early-stage lung cancer and lowering disease-specific mortality has been shown in a number of extensive lung cancer screening trials. The image quality of LDCT exams has been further enhanced by developments in multidetector CT technology, iterative reconstruction methods, and artificial intelligence-assisted image processing. However, there are still questions about whether LDCT can identify tiny pulmonary nodules as accurately as SDCT, especially in patients with obesity, complex lung anatomy, or underlying pulmonary illness [8, 9]. To ascertain whether radiation dose reduction is possible without sacrificing diagnostic performance, a comparative analysis of LDCT and SDCT is crucial. Important details on the clinical utility of LDCT can be found in parameters like sensitivity, specificity, positive predictive value, negative predictive value, and overall diagnostic accuracy. The viability of integrating LDCT into standard clinical practice and lung cancer screening programs is also established by evaluation of picture quality and nodule detection rates [10]. More research on the diagnostic efficacy of LDCT is necessary given the increased focus on radiation safety and the rising need for efficient screening techniques. In order to compare the diagnostic accuracy of low-dose CT and standard-dose CT in detecting pulmonary nodules and to examine the potential role of LDCT as a safer option for lung cancer screening and pulmonary nodule evaluation, the current multicenter prospective study was conducted [11].

Study Design and Study Population: The diagnostic accuracy of low-dose computed tomography (LDCT) versus standard-dose computed tomography (SDCT) in the identification of lung nodules was assessed in a multicenter prospective comparative research. This study was conducted at Department of Radio-Diagnosis, Siruvachur, Perambalur District, Tamil Nadu, between September 10, 2024 to August 2025. Over the course of six months, the study was conducted in three tertiary care facilities. The study included 30 patients with suspected pulmonary nodules or people undergoing chest CT evaluation for lung cancer screening, follow-up, or diagnostic evaluation. Methods: All CT exams were done using multidetector CT scanners at participating locations. In the LDCT technique, tube current and voltage were altered to reduce radiation exposure while retaining diagnostic picture quality. SDCT used institutional chest CT characteristics for pulmonary nodule evaluation. Two experienced radiologists blinded to patient clinical characteristics and imaging protocol independently assessed CT images reconstructed using standard reconstruction algorithms. Reader disagreements were handled by consensus. Reference standard for diagnostic comparison was standard-dose CT findings. To assess sensitivity, specificity, PPV, NPV, and diagnostic accuracy, low-dose CT results were compared to SDCT results. CTDIvol and DLP were also obtained for both imaging methods to compare radiation exposure. Inclusion Criteria: • Adult patients aged 18 years and above. • Patients referred for chest CT examination for suspected pulmonary nodules, lung cancer screening, or follow-up evaluation. • Patients willing to undergo both LDCT and SDCT examinations. • Patients who provided written informed consent for study participation. • Patients with adequate image quality for interpretation. Exclusion Criteria: • Patients younger than 18 years of age. • Pregnant or lactating women. • Patients with severe respiratory distress preventing CT acquisition. • Patients with prior lung surgery causing significant anatomical distortion. • Patients with extensive pulmonary fibrosis or diffuse lung disease that markedly impaired nodule assessment. • Patients with incomplete imaging studies or poor-quality CT images. • Patients unwilling to participate or unable to provide informed consent. Statistical Analysis: Excel and SPSS 26.0 were used to analyse data. Data was reported as mean ± standard deviation (SD) for continuous variables and frequencies and percentages for categorical variables. The reference standard for LDCT diagnostics was SDCT. Diagnostic accuracy, sensitivity, specificity, PPV, NPV, and total accuracy were calculated as percentages. The LDCT-SDCT agreement was examined using Cohen's kappa coefficient. The Chi-square or Fisher's exact test was used to compare categorical variables. For all statistical studies, p-values below 0.05 were significant

A total of 30 patients were enrolled in this multicenter prospective study and successfully underwent both low-dose CT (LDCT) and standard-dose CT (SDCT) examinations. The diagnostic efficacy of LDCT was assessed with SDCT serving as the reference benchmark for identifying lung nodules. Table 1: Demographic and Clinical Characteristics of Study Participants Characteristic Number of Patients (%) Total Patients 30 (100.0) Male 18 (60.0) Female 12 (40.0) Mean Age (Years) 56.8 ± 11.4 Smokers 17 (56.7) Non-Smokers 13 (43.3) Screening Evaluation 14 (46.7) Diagnostic Evaluation 10 (33.3) Follow-up Assessment 6 (20.0) Table 1 provides a concise overview of the research population's demographic and clinical features. The study population consisted of 60.0% males and had an average age of 56.8 ± 11.4 years. The percentage of those who had smoked in the past was over 50%. Screening programs for lung cancer included CT imaging for nearly half of the patients. Table 2: Detection of Pulmonary Nodules by SDCT and LDCT Finding SDCT (Reference Standard) LDCT Patients with Pulmonary Nodules 20 (66.7%) 19 (63.3%) Patients without Pulmonary Nodules 10 (33.3%) 11 (36.7%) Total Patients 30 (100.0%) 30 (100.0%) Both imaging modalities have different rates of lung nodule detection, which are shown in Table 2. Twenty patients, or 66.7%, had lung nodules found by standard-dose CT, whereas nineteen patients, or 63.3%, had nodules found by LDCT. A strong degree of concordance between the two imaging methods is shown by the results. Table 3. Diagnostic Performance of Low-Dose CT in Detecting Pulmonary Nodules Parameter Value (%) Sensitivity 90.0 Specificity 90.0 Positive Predictive Value (PPV) 94.7 Negative Predictive Value (NPV) 81.8 Overall Accuracy 90.0 Cohen's Kappa Coefficient 0.79 The comparison of LDCT and SDCT in terms of diagnostic performance is presented in Table 3. When it came to detecting lung nodules, LDCT showed a sensitivity and specificity of 90%. With a total diagnosis accuracy of 90%, LDCT and SDCT were in perfect harmony. With a Cohen's kappa coefficient of 0.79, there was strong agreement between the two methods. Table 4: Distribution of Pulmonary Nodules According to Size Nodule Size Number of Patients <5 mm 5 5–10 mm 9 11–20 mm 6 >20 mm 10 Total 30 Distribution of pulmonary nodules by SDCT-detected size is shown in Table 4. The diameter of the nodules ranged from 5 to 10 mm for 45.0% of them, while 25.0% had a diameter of 5 mm or smaller. The percentage of nodules larger than 20 mm was quite low. Table 5: Comparison of Radiation Exposure between LDCT and SDCT Parameter LDCT SDCT Percentage Reduction CTDIvol (mGy) 2.3 ± 0.5 7.8 ± 1.2 70.5% DLP (mGy·cm) 82.4 ± 16.7 276.5 ± 34.8 70.2% The radiation dosage parameters for the two imaging methods are compared in Table 5. LDCT achieved a reduction of around 70% in both CTDIvol and DLP values, considerably reducing radiation exposure when compared to SDCT. Excellent diagnostic performance for lung nodule detection was maintained by LDCT despite this large decrease in radiation exposure.

Pulmonary nodules may be the first sign of lung cancer, hence good diagnosis is crucial in modern thoracic imaging. CT technology has enhanced the detection of tiny pulmonary nodules, but concerns about cumulative radiation exposure have led to low-dose imaging methods. LDCT and SDCT were evaluated in detecting lung nodules in 30 individuals in this multicenter prospective research. LDCT showed great diagnostic accuracy while minimising radiation dose, suggesting it could replace SDCT [12, 13]. SDCT found lung nodules in 66.7% of patients and LDCT in 63.3%. Close agreement between the two modalities suggests dose decrease did not significantly reduce lesion detectability. These findings support prior research showing that contemporary LDCT methods can detect lung nodules, especially when paired with improved image reconstruction. LDCT can identify most SDCT-detected nodules, making it acceptable for routine clinical usage, especially in screening and surveillance situations that need recurrent imaging [14, 15]. Radiation dosage reduction did not appear to impair picture interpretation. Most LDCT exams were diagnostically acceptable, proving that optimised acquisition parameters can retain image quality for lung nodule assessment. Lung cancer screening programs must balance diagnostic accuracy and patient safety, making this finding crucial. Broad implementation of LDCT techniques may reduce radiation risks without harming clinical outcomes [16, 17]. The multicenter design of this study incorporates data from various healthcare settings and imaging technologies, improving generalisability. Several limitations must be noted. The study's statistical power may be limited by its 30-patient sample. SDCT was employed as the reference standard instead of histological confirmation, which may not fully represent all observed nodules. Body habitus, respiratory movements, and scanner technologies across centers may have affected picture quality and nodule detection [18-20]. Future studies with larger patient populations, longer follow-up periods, and AI-assisted detection systems may reveal LDCT's diagnostic potential. Researchers studying sub-centimeter nodules and ground-glass opacities may also help determine low-dose imaging procedures' strengths and weaknesses. Cost-effectiveness evaluations and multicenter randomised trials could also help national lung cancer screening programs adopt LDCT [21-23]. This study shows that LDCT detects lung nodules well while lowering radiation exposure. LDCT may be a safer option to SDCT for pulmonary nodule screening, surveillance, and early lung cancer detection due to its excellent sensitivity, specificity, and accuracy. Its widespread clinical use could increase patient safety and diagnostic quality [24, 25].

The present multicenter prospective analysis showed that low-dose computed tomography (LDCT) detects lung nodules more accurately than SDCT. LDCT matched the reference standard in sensitivity, specificity, positive predictive value, and diagnostic accuracy. The low-dose approach identified most lung nodules, even small ones under 10 mm. This study found that LDCT reduced radiation exposure by 70% compared to SDCT. This reduction is crucial for lung cancer screening, surveillance, and long-term follow-up patients facing frequent imaging exams. The decreased radiation dose did not affect image quality, proving that LDCT is clinically feasible for routine thoracic imaging. LDCT may be a safe, effective, and radiation-free alternative to SDCT for lung nodule detection. Optimised LDCT techniques may increase patient safety, screening adherence, and lung cancer diagnosis. Large-scale multicenter investigations are needed to confirm these findings and standardise low-dose imaging for pulmonary nodule assessment and lung cancer screening

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