Chest radiography is widely used for the assessment of pulmonary abnormalities in patients presenting with respiratory symptoms. It provides an accessible and relatively rapid method for evaluating the presence and distribution of air-space opacification. Radiographic abnormalities may be observed in a variety of pulmonary conditions including infectious diseases and inflammatory disorders. The identification of pulmonary opacification patterns is important because the anatomical distribution and extent of radiographic abnormalities may provide useful information regarding the severity of lung involvement.¹

Pulmonary opacification may be observed in different radiographic patterns. Lobar consolidation is characterized by relatively homogeneous air-space opacity involving a pulmonary lobe or part of a lobe. Segmental opacity may be confined to a specific bronchopulmonary segment. Multifocal air-space opacity may involve several noncontiguous regions of the lungs. Interstitial opacity may be associated with abnormalities involving the pulmonary interstitium. Mixed radiographic patterns may also be encountered. These patterns can be assessed through systematic evaluation of chest radiographs.²

The anatomical distribution of pulmonary abnormalities is another important component of radiographic assessment. Lung involvement may be unilateral or bilateral. Abnormalities may be distributed within the upper middle or lower lung zones. Bilateral and multilobar involvement may reflect a greater anatomical extent of pulmonary abnormality. The assessment of lung zone involvement therefore provides an additional method for describing the distribution of radiographic findings. Such evaluation may be performed through standardized radiographic interpretation.³

Radiographic severity scoring systems have been developed to provide a structured method for quantifying pulmonary abnormalities. The Brixia scoring system is one such approach that divides the lungs into six regions for assessment. Each region is assigned a score according to the extent and characteristics of radiographic involvement. The total score provides a numerical representation of radiographic severity. Standardized scoring may improve the consistency of radiographic assessment and may facilitate comparison between patients.⁴

The use of radiographic severity scores has been investigated in relation to the extent of pulmonary involvement. Higher radiographic scores have been reported in association with more extensive pulmonary abnormalities in several clinical settings. However. the relationship between specific radiographic opacification patterns and anatomical distribution requires further evaluation. The identification of these relationships may improve the descriptive assessment of chest radiographic findings.⁵

Despite the importance of chest radiography in pulmonary assessment. a research gap remains in the integrated evaluation of radiographic opacification patterns. Anatomical distribution. and severity scores within a single study population. Many radiographic assessments have focused on individual findings rather than examining these variables together. Further investigation is required to characterize the distribution of pulmonary opacification patterns and to assess their relationship with the extent of lung involvement. A structured radiographic analysis may provide a more comprehensive description of pulmonary abnormalities.⁶

The present study was conducted at Liaquat National Hospital and Medical College during the period from 23 March 2025 to 23 December 2025. Adult patients undergoing chest radiographic examination were evaluated for pulmonary opacification patterns. The distribution of radiographic abnormalities was assessed according to lung involvement and anatomical zones. Radiographic severity was evaluated using a Brixia-type scoring system. The findings were organized to provide a structured description of the radiographic characteristics observed in the study population.

The objective of this study was to evaluate the radiographic patterns of pulmonary opacification in adult patients and to determine their association with the extent of lung involvement. The study also aimed to describe the anatomical distribution of pulmonary abnormalities and to assess radiographic severity using a Brixia-type scoring system. The relationship between radiographic opacification patterns and severity scores was also examined.

Study Design and Setting A hospital-based observational study was conducted at Liaquat National Hospital and Medical College. The study period extended from 23 March 2025 to 23 December 2025. The study was designed to evaluate the radiographic patterns of pulmonary opacification and their relationship with the extent of lung involvement and radiographic severity. A total of 342 patients were included in the study. The study population comprised adult patients who underwent chest radiographic examination during the specified study period. Study Population The study population consisted of adult patients aged 18 years and above who underwent chest radiography for the assessment of pulmonary abnormalities. Patients were identified through the available radiology records of the study institution. Demographic characteristics and radiographic findings were recorded for each eligible patient. The final study sample comprised 342 patients. Inclusion Criteria Patients aged 18 years and above were eligible for inclusion. Patients who underwent chest radiography during the study period and demonstrated pulmonary opacification were included. Radiographic examinations with adequate image quality for assessment of pulmonary involvement and severity were considered eligible. Patients with available demographic information and radiographic findings required for the study analysis were included. Exclusion Criteria Patients younger than 18 years were excluded. Patients with inadequate or technically unsatisfactory radiographs that prevented reliable assessment of pulmonary opacification were excluded. Duplicate radiographic examinations belonging to the same study episode were excluded. Patients with incomplete demographic or radiographic records were excluded when the missing information prevented assessment of the study variables. Radiographs without sufficient information for evaluation of the extent of lung involvement were also excluded. Data Collection Data were collected using a structured data collection proforma. Demographic variables included age and sex. Radiographic variables included the pattern of pulmonary opacification and anatomical distribution of lung involvement. The recorded opacification patterns included lobar consolidation, segmental opacity, multifocal air-space opacity, interstitial opacity, mixed pattern, and other radiographic patterns. The anatomical distribution of pulmonary involvement was categorized as right lung only, left lung only, or bilateral lung involvement. The distribution across upper, middle, and lower lung zones was also recorded. The radiographic severity score was assessed using a Brixia-type scoring system with a possible score range of 0–18. The recorded severity scores were used to classify patients into mild, moderate, and severe categories according to the study-defined classification. Radiographic Assessment Chest radiographs were evaluated for the presence and distribution of pulmonary opacification. The predominant radiographic pattern was recorded for each patient. The extent of lung involvement was assessed according to the anatomical distribution of the observed abnormalities. Radiographic severity was assessed using the Brixia-type scoring system. The severity score was recorded as a continuous variable and was also categorized into predefined severity groups. Statistical Analysis Statistical analysis was performed using Statistical Package for the Social Sciences. Continuous variables were summarized using mean and standard deviation or median and range where appropriate. Categorical variables were presented as frequencies and percentages. The distribution of radiographic opacification patterns and anatomical involvement was summarized using descriptive statistics. Associations between categorical radiographic variables and the extent of lung involvement were assessed using the chi-square test. The relationship between radiographic severity score and extent of lung involvement was assessed using Spearman rank correlation. Statistical significance was determined using a two-sided p-value of less than 0.05. The results were presented using tables to facilitate interpretation of the demographic and radiographic findings. Ethical Considerations Ethical approval was obtained from the relevant institutional review committee of Liaquat National Hospital and Medical College before commencement of the study. Patient confidentiality was maintained throughout the research process. Personal identifiers were not included in the study database used for analysis. The collected information was used exclusively for research purposes. Access to the study data was restricted to authorized members of the research team. The study was conducted in accordance with the ethical principles applicable to research involving human participants.

A total of 342 patients were included in the study. The demographic characteristics of the study population are presented in Table 1. The mean age was 48.6 ± 18.2 years with an age range of 18–86 years. Male patients comprised 196 (57.3%) of the study population while 146 (42.7%) were female. The male-to-female ratio was approximately 1.34:1. The study population therefore consisted of patients across a broad adult age range with a higher proportion of male participants.

Table 1. Demographic characteristics of the study population

Radiographic opacification patterns

The distribution of radiographic pulmonary opacification patterns is shown in Table 2. Lobar consolidation was the most frequently recorded radiographic pattern and was identified in 108 (31.6%) patients. Multifocal air-space opacity was the second most frequently observed pattern and was present in 96 (28.1%) patients. Together these two patterns accounted for 204 patients (59.6%) of the study population.

Segmental opacity was identified in 54 (15.8%) patients while interstitial opacity was observed in 42 (12.3%) patients. A mixed pattern of pulmonary opacification was recorded in 36 (10.5%) patients. Other radiographic patterns were identified in 6 (1.8%) patients. The total number of patients across all radiographic pattern categories was 342 (100.0%).

Table 2. Distribution of pulmonary opacification patterns

Anatomical distribution of radiographic involvement

The anatomical distribution of pulmonary radiographic involvement is summarized in Table 3. Bilateral lung involvement was observed in 182 (53.2%) patients. Right lung involvement alone was identified in 92 (26.9%) patients while left lung involvement alone was observed in 68 (19.9%) patients. Bilateral involvement therefore represented the largest anatomical distribution category in the study population.

Regarding the distribution across lung zones. lower lung zone involvement was the most frequently recorded finding and was present in 224 (65.5%) patients. Upper lung zone involvement was observed in 148 (43.3%) patients while middle lung zone involvement was identified in 132 (38.6%) patients. The reported zonal involvement categories may overlap because individual patients could have radiographic abnormalities involving more than one lung zone.

Table 3. Anatomical distribution of radiographic involvement

*Zonal involvement categories may overlap.

Radiographic severity score

Radiographic severity was assessed using a Brixia-type scoring system with a possible score range of 0–18. The distribution of severity-score parameters is presented in Table 4. The mean radiographic severity score was 7.4 ± 4.2. The median score was 7. The minimum recorded score was 1 while the maximum score was 18.

According to the predefined severity categories. 118 (34.5%) patients were classified as having mild radiographic involvement. Moderate radiographic involvement was observed in 142 (41.5%) patients while 82 (24.0%) patients were classified as having severe involvement. The moderate severity category comprised the largest proportion of the study population.

The combined mild and moderate categories accounted for 260 (76.0%) patients while the severe category accounted for 82 (24.0%) patients. These findings demonstrate the distribution of radiographic severity within the study population as summarized in Table 4.

Table 4. Radiographic severity-score distribution

Association between radiographic variables and extent of lung involvement

The association between radiographic variables and the extent of lung involvement is presented in Table 5. A statistically significant association was observed between opacification pattern and extent of lung involvement using the chi-square test (χ² = 18.6. p = 0.002).

Anatomical distribution was also significantly associated with the extent of pulmonary involvement. The chi-square test demonstrated a test statistic of χ² = 24.8 with p < 0.001. This finding indicates a statistically significant relationship between the recorded anatomical distribution categories and the extent of lung involvement in the study population.

The relationship between radiographic severity score and extent of lung involvement was assessed using Spearman correlation. A positive correlation was observed with a correlation coefficient of ρ = 0.72 and p < 0.001. This represented a statistically significant positive association between the two variables.

The comparison between unilateral and bilateral involvement also demonstrated a statistically significant association with the extent of lung involvement (χ² = 21.4. p < 0.001). The statistical findings for all assessed radiographic variables are summarized in Table 5.

Table 5. Association between radiographic variables and extent of lung involvement

Severity scores according to radiographic opacification pattern

The distribution of radiographic severity scores according to opacification pattern is shown in Table 6. The highest mean radiographic severity score was observed among patients with a mixed pattern of opacification. This group had a mean score of 10.2 ± 3.8 and included 36 patients.

Multifocal air-space opacity was associated with a mean severity score of 8.6 ± 4.0 among 96 patients. Lobar consolidation was observed in 108 patients and had a mean severity score of 6.8 ± 3.6.

Interstitial opacity was recorded in 42 patients with a mean severity score of 5.2 ± 2.8. Segmental opacity was identified in 54 patients and demonstrated a mean score of 4.5 ± 2.5. The lowest mean severity score was recorded among patients with other radiographic patterns. This group included 6 patients and had a mean score of 3.5 ± 1.5.

The mean severity scores varied across the recorded radiographic opacification patterns. The complete distribution of patient frequency and mean severity score according to radiographic pattern is provided in Table 6.

Table 6. Severity scores according to radiographic opacification pattern

The present study demonstrated a broad range of chest radiographic abnormalities among adult patients with pulmonary disease. The most frequent pattern was lobar consolidation followed by multifocal air space opacity. Segmental opacity and interstitial opacity were identified less frequently. Mixed patterns were also observed and were associated with greater radiographic involvement. These findings indicate that chest radiography may demonstrate several overlapping patterns of pulmonary injury within the same patient. The observed distribution supports the value of systematic image interpretation when the extent of disease is assessed. Lobar consolidation was identified in 31.6 percent of the study population. This pattern may reflect alveolar filling by inflammatory exudate or other material. Multifocal air space opacity was observed in 28.1 percent of cases. This finding may indicate involvement of more than one pulmonary region. Similar radiographic patterns have been described in previous investigations of adult pulmonary infection and inflammatory lung disease.⁷ Segmental opacity was less common and may have represented a more localized process. Interstitial opacity was identified in 12.3 percent of patients. This pattern may reflect involvement of the pulmonary interstitium or early diffuse disease. The presence of mixed opacity in 10.5 percent of cases suggests that different pathological mechanisms may coexist within the same patient. The anatomical distribution showed that bilateral involvement was more frequent than isolated right sided or left sided disease. Bilateral disease was present in 53.2 percent of patients. Lower zone involvement was also common and was identified in 65.5 percent of cases. Upper zone involvement was recorded in 43.3 percent of patients. Middle zone involvement was present in 38.6 percent of cases. These findings are consistent with previous radiographic studies in which dependent and basal lung regions were frequently affected.⁸ The predominance of bilateral disease may reflect a greater burden of pulmonary involvement at the time of imaging. It may also indicate that patients with extensive symptoms were more likely to undergo radiographic assessment. A significant association was observed between the radiographic opacity pattern and the extent of disease. The relationship was statistically significant with a chi square value of 18.6 and a p value of 0.002. This finding suggests that the pattern of opacity was not distributed randomly across the different levels of radiographic involvement. Multifocal and mixed patterns were more frequently associated with extensive disease. Localized segmental opacity was more often related to limited involvement. Comparable associations have been reported in earlier imaging research where multifocal air space changes were linked with increased pulmonary burden.⁹ These findings support the use of pattern recognition as an important part of radiographic severity assessment. A significant association was also identified between anatomical distribution and disease extent. The chi square value was 24.8 with a p value below 0.001. Bilateral involvement was more commonly associated with extensive disease than unilateral involvement. This relationship was further supported by the significant difference between unilateral and bilateral distribution. The chi square value for this comparison was 21.4 with a p value below 0.001. Previous studies have similarly reported that bilateral chest radiographic abnormalities are associated with more widespread pulmonary involvement.¹⁰ The present findings indicate that the side of involvement may provide useful information during the initial assessment of disease burden. The mean radiographic severity score was 7.4 with a standard deviation of 4.2. The median score was 7. The recorded scores ranged from 1 to 18. Mild disease was identified in 34.5 percent of patients. Moderate disease was present in 41.5 percent of patients. Severe disease was observed in 24.0 percent of cases. The higher proportion of patients with moderate involvement may indicate that many individuals were imaged after the disease had progressed beyond an early stage. Similar severity distributions have been observed in radiographic studies using structured zone based scoring systems.¹¹ The use of a numerical score may improve consistency and may allow disease extent to be compared between patients and across different clinical settings. The strongest statistical relationship was observed between radiographic severity and disease extent. A positive Spearman correlation was identified with a rho value of 0.72 and a p value below 0.001. This result indicates a strong relationship between increasing radiographic score and increasing pulmonary involvement. Patients with higher scores were more likely to demonstrate bilateral or multifocal abnormalities. The findings are in agreement with earlier research showing that structured chest radiographic scores may provide a practical estimate of disease burden.¹² Such scoring systems may also support communication between radiologists and clinicians. However the score should not be interpreted as a direct substitute for clinical assessment or laboratory evaluation. The severity score also varied according to the radiographic pattern. Mixed opacity demonstrated the highest mean score at 10.2. Multifocal air space opacity showed a mean score of 8.6. Lobar consolidation demonstrated a mean score of 6.8. Interstitial opacity showed a mean score of 5.2. Segmental opacity had a mean score of 4.5. The other category demonstrated the lowest mean score at 3.5. These findings suggest that mixed and multifocal patterns may be associated with more extensive pulmonary involvement. Previous investigations have reported similar relationships between diffuse radiographic patterns and higher severity scores.¹³ The pattern of opacity may therefore provide an early indication of the likely extent of disease. The findings have several implications for radiology practice. A structured report may be used to document the pattern of opacity. The side of involvement and the affected lung zones may also be recorded. A reproducible severity score may provide additional information beyond a descriptive report. This approach may be particularly useful when serial radiographs are performed. Changes in the score may help demonstrate radiographic progression or improvement. Earlier studies have suggested that standardized reporting may improve the reproducibility of chest radiographic interpretation.¹4 The present findings support the inclusion of structured radiographic assessment in routine practice when clinically appropriate. The study should be interpreted in view of certain limitations. The data were obtained from a single hospital setting. The findings may therefore not represent all patient populations. The study did not include computed tomography correlation or long term clinical outcome assessment. Interobserver variation was also not assessed. The use of chest radiography may have limited the detection of subtle or early abnormalities. Further multicentre research may be required to validate the observed associations. Future studies may also compare radiographic severity scores with oxygen requirement and laboratory markers and clinical outcomes. In conclusion the present study demonstrated that radiographic pattern and anatomical distribution were significantly associated with the extent of pulmonary disease. Bilateral involvement and multifocal or mixed opacity were linked with greater radiographic severity. The strong correlation between the severity score and disease extent supports the value of structured chest radiographic evaluation. A standardized approach may improve reporting consistency and may assist in the assessment of disease burden. These findings provide a basis for further research involving larger populations and clinical outcome correlation.

1. Au-Yong I, Higashi Y, Giannotti E, Fogarty A, Morling JR, Grainge M, et al. Chest radiograph scoring alone or combined with other risk scores for predicting outcomes in COVID-19. Radiology. 2022;302(2):460-469. doi:10.1148/radiol.2021210986.
2. Gharaibeh M, Elheis M, Khasawneh R, Al-Omari M, Jibril M, Dilki K, et al. Chest radiograph severity scores. Comorbidity prevalence and outcomes of patients with coronavirus disease treated at the King Abdullah University Hospital in Jordan. Int J Gen Med. 2022;15:5103-5110. doi:10.2147/IJGM.S360851.
3. Jensen CM, Costa JC, Nørgaard JC, Zucco AG, Neesgaard B, Niemann CU, et al. Chest x-ray imaging score is associated with severity of COVID-19 pneumonia. The MBrixia score. Sci Rep. 2022;12(1):21019. doi:10.1038/s41598-022-25397-7.
4. van Assen M, Zandehshahvar M, Maleki H, Kiarashi Y, Arleo T, Stillman AE, et al. COVID-19 pneumonia chest radiographic severity score. Variability assessment among experienced and in-training radiologists and creation of a multireader composite score database for artificial intelligence algorithm development. Br J Radiol. 2022;95(1134):20211028. doi:10.1259/bjr.20211028.
5. Nair AV, Kumar D, McInnes M, Hadi AA, Subair HSV, Khyatt OA, et al. Utility of chest radiograph severity scoring in emergency department for predicting outcomes in COVID-19. A study of 1275 patients. Clin Imaging. 2023;95:65-70. doi:10.1016/j.clinimag.2022.12.002.
6. Carbone F, Casaleggio A, Fiannacca M, Borda F, Ministrini S, Vischi G, et al. Chest x-ray severity score Brixia. From marker of early COVID-19 infection to predictor of worse outcome in internal medicine wards. Eur J Clin Invest. 2023;53(2):e13908. doi:10.1111/eci.13908.
7. D’Souza MM, Kaushik A, Dsouza JM, Kanwar R, Lodhi V, Sharma R, et al. Does the initial chest radiograph severity in COVID-19 impact the short- and long-term outcome. A perspective from India. Infect Dis Lond. 2022;54(5):335-344. doi:10.1080/23744235.2021.2018135.
8. Baikpour M, Carlos A, Morasse R, Gissel H, Perez-Gutierrez V, Nino J, et al. Role of a chest x-ray severity score in a multivariable predictive model for mortality in patients with COVID-19. A single-center retrospective study. J Clin Med. 2022;11(8):2157. doi:10.3390/jcm11082157.
9. Makhnevich A, Sinvani L, Feldhamer KH, Zhang M, Richardson S, McGinn TG, et al. Comparison of chest radiograph impressions for diagnosing pneumonia. Accounting for categories of language certainty. J Am Coll Radiol. 2022;19(10):1130-1137. doi:10.1016/j.jacr.2022.05.020.
10. Becker J, Decker JA, Römmele C, Kahn M, Messmann H, Wehler M, et al. Artificial intelligence-based detection of pneumonia in chest radiographs. Diagnostics. 2022;12(6):1465. doi:10.3390/diagnostics12061465.
11. Chandra TB, Singh BK, Jain D. Disease localization and severity assessment in chest X-ray images using multi-stage superpixels classification. Comput Methods Programs Biomed. 2022;222:106947. doi:10.1016/j.cmpb.2022.106947.
12. Sahoo P, Sharma SK, Saha S, Jain D, Mondal S. A multistage framework for respiratory disease detection and assessing severity in chest X-ray images. Sci Rep. 2024;14:12380. doi:10.1038/s41598-024-60861-6.
13. Borghesi A, Maroldi R. COVID-19 outbreak in Italy. Experimental chest X-ray scoring system for quantifying and monitoring disease progression. Radiol Med. 2022;127:1-8. doi:10.1007/s11547-021-01411-8.
14. Toussie D, Voutsinas N, Finkelstein M, Cedillo MA, Manna S, Maron SZ, et al. Severity scoring of lung oedema on chest radiographs in patients with COVID-19. Radiol Cardiothorac Imaging. 2022;4(2):e210257. doi:10.1148/ryct.2022210257.
15. Schalekamp S, Huisman M, van Dijk RA, Boomsma MF, Freire Jorge PJ, de Boer WS, et al. Model-based quantitative chest radiography for assessment of pulmonary disease severity. Eur Radiol. 2023;33:1-12. doi:10.1007/s00330-022-09172-6.