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Background:
Systematic Review

Diagnostic Accuracy of Imaging Findings in Pleural Empyema: Systematic Review and Meta-Analysis

by
Desiree Zettinig
1,2,
Tugba Akinci D’Antonoli
1,3,
Adrian Wilder-Smith
1,
Jens Bremerich
4,
Jan A. Roth
1,5 and
Raphael Sexauer
1,4,*
1
Division of Research and Analytical Services, Department of Informatics, University Hospital Basel, 4031 Basel, Switzerland
2
Institute of Radiology, Kantonsspital Aarau, 5001 Aarau, Switzerland
3
Department of Radiology, University Children’s Hospital Basel, 4056 Basel, Switzerland
4
Department of Radiology and Nuclear Medicine, University Hospital Basel, 4031 Basel, Switzerland
5
Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, 4056 Basel, Switzerland
*
Author to whom correspondence should be addressed.
J. Imaging 2022, 8(1), 3; https://doi.org/10.3390/jimaging8010003
Submission received: 29 November 2021 / Revised: 17 December 2021 / Accepted: 23 December 2021 / Published: 28 December 2021
(This article belongs to the Topic Medical Image Analysis)
Browse Figures
Versions Notes

Abstract

:
Computed tomography (CT) diagnosis of empyema is challenging because current literature features multiple overlapping pleural findings. We aimed to identify informative findings for structured reporting. The screening according to inclusion criteria (P: Pleural empyema, I: CT C: culture/gram-stain/pathology/pus, O: Diagnostic accuracy measures), data extraction, and risk of bias assessment of studies published between 01-1980 and 10-2021 on Pubmed, Embase, and Web of Science (WOS) were performed independently by two reviewers. CT findings with pooled diagnostic odds ratios (DOR) with 95% confidence intervals, not including 1, were considered as informative. Summary estimates of diagnostic accuracy for CT findings were calculated by using a bivariate random-effects model and heterogeneity sources were evaluated. Ten studies with a total of 252 patients with and 846 without empyema were included. From 119 overlapping descriptors, five informative CT findings were identified: Pleural enhancement, thickening, loculation, fat thickening, and fat stranding with an AUC of 0.80 (hierarchical summary receiver operating characteristic, HSROC). Potential sources of heterogeneity were different thresholds, empyema prevalence, and study year.

1. Introduction

Pleural effusion is common with an incidence of 0.32% per year in the general population [1] amounting to approximately 1.5 million people in the United States each year alone [2]. Frequently pleural effusion is related to pneumonia, malignancy, or trauma, which may become secondarily infected. Empyema is defined by pus in the pleural space and the most common cause is pneumonia [3]. Empyema-related hospitalizations are increasing [4]. Although empyema accounts for only 5–10% of parapneumonic effusions [5,6], it is associated with worse outcomes: Longer hospital stays and more complications, especially in culture-positive empyemas [7]. Whilst uncomplicated parapneumonic effusions can be treated with antimicrobial therapy, empyema often requires invasive procedures in addition to broad-spectrum antimicrobial therapy [8]. Computed tomography (CT) is a valuable imaging modality for diagnosing pleural effusions and identifying their etiology [9]. Therefore, it is an integral part of diagnostic procedures for a timely diagnosis of empyema.
So far, no systematic review (Cochrane Library, PROSPERO, and PubMed) has evaluated the accuracy of CT for detection of empyema. Therefore, this systematic review and meta-analysis aims to identify relevant CT findings for the diagnosis of empyema and to investigate their diagnostic accuracy including the sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC).

2. Materials and Methods

This study is registered on PROSPERO (protocol number: CRD42021251903, approved on 29 April 2021). No protocol deviations occurred.

2.1. Eligibility Criteria

Based on the PICOT framework, we defined the following inclusion criteria.
  • Population: Human patients with empyema as a positive condition and other pleural effusions as a negative condition.
  • Index test: Computed tomography.
  • Comparison: Diagnosis based on positive culture or gram-stain, pathological, or macroscopic confirmation [10,11,12].
  • Outcome: Diagnostic accuracy measures (e.g., sensitivity, specificity, area under the curve (AUC), diagnostic odds ratio (DOR)). The data is retrievable to calculate a 2 × 2 contingency.
  • Time-period: Studies between 01-1980 and 10-2021.
Case reports, case series, and animal experiments were excluded.

2.2. Information Sources

Information sources were Pubmed, Embase, and Web of Science (WOS).

2.3. Search Strategy

A sensitive search strategy was established with Mesh-term and Title/Abstract search in Pubmed which included the terms “empyema”, “computed tomography”, and “diagnostic accuracy”. This search strategy was translated with the “polyglot search translator” [13] to “Embase” and “Web of Science”. The detailed search terms can be found in Appendix A. The literature search was updated monthly, with the last update performed on 31 October 2021. Additionally, “Cochrane library”, PROSPERO, and online clinical trial registries such as ClinicalTrials.gov (https://clinicaltrials.gov, last update: 31 October 2021) and ISRCTN (https://www.isrctn.com, last update: 31 October 2021) were searched for additional relevant studies.

2.4. Selection Process

Eligibility screening was conducted in two steps: Title and abstract screening for matching the inclusion criteria (1) and full-text screening (2)
Title, author, and abstract were exported from Pubmed, Embase, and WOS to Microsoft Excel 2019 (Redmond, WA, USA). Duplicates were removed prior to the initiation of the screening process. Both reviewers independently reviewed the title and abstract of all identified studies blinded to each other.
If disagreement existed or a paper could not be excluded by title and abstract alone, the paper was included for full-text reading. Full-text versions of relevant studies were retrieved for further evaluation. Reference lists of included studies were checked manually to identify other relevant papers.

2.5. Data Collection Process

A structured data extraction sheet [14] was designed, which included QUADAS-2 [15] and all STARD 2015 [16] criteria to review the identified studies summarized in Appendix B. Assessment of risk of bias and methodological quality is summarized in Appendix C. A study was judged to be at risk of bias if one or more QUADAS criteria were unclear or high.

2.6. Data Items and Data Extraction

Both reviewers assessed both the individual data items and risk of bias in the uniform data extraction sheet in a blinded design. Any disagreement was resolved by rechecking the original data and consensus.

2.7. Statistical Analysis and Data Synthesis

All statistical analyses including synthesis methods were performed with R 4.0.5 (R Core Team, Vienna, Austria) and the following packages: “mada”, “ellipse”, “meta”, “metafor”, “rmeta”, “tidyverse”, and “mvtnorm”.
For each study included in the meta-analysis, data were extracted to generate 2 × 2 contingency tables displaying true positives, true negatives, false positives, and false negatives. Patients without infected pleural effusion were regarded as disease negatives and patients with a positive culture, gram stain, or macroscopic pus as disease positive. False positives were defined as patients having the disease based on a positive pleural finding but categorized as not having the disease by the reference standard.
Pooled sensitivity, specificity, DOR, and AUC (univariate and hierarchical analysis), as well as 95% CI intervals, were calculated for each pleural finding of the published studies. Forest plots were constructed for all included studies displaying sensitivity and specificity.
Since a common implicit cut-off value for test positivity is to be expected and large differences between disease prevalence in different studies exist, estimates of pooled sensitivity and specificity were calculated by fitting a bivariate random effect model to account for both within- and between-study heterogeneity [17,18]. We quantified heterogeneity between the studies using the I2-Index and level of heterogeneity (low < 25, moderate 25–75, and high > 75) as defined by Higgins et al. [19]. We are aware there is a threshold value effect for diagnostic accuracy studies of modalities so that these can only be interpreted to a limited extent [20].
Informative CT findings were defined as a DOR 95% confidence interval, not including 1 [21]. The publication bias could only be assessed to a limited extent, as there is no generally accepted method for diagnostic accuracy studies and the number of studies included was low [22]. Subgroup analyses for sensitivity and specificity with random effect models were performed regarding informative pleural findings, the negative collectives (parapneumonic effusions, benign effusions, or effusions in general), concerns regarding applicability (QUADAS-2), the reference standard, slice thickness, whether a study was performed after the year 2000, multiple reviewers, and the dichotomized prevalence of empyema (cutoff 30%). Additionally, a meta-analysis with a mixed-effects model based on DOR estimates was used for disease prevalence and study year. We evaluated suspected significance based on meta-regression with permutation tests (1000 iterations). Alpha level was set to 0.05.

3. Results

3.1. Study Selection

The initial search identified 545 studies, which were screened by title and abstract after deduplication. Figure 1 shows the study flow detailing search results and study inclusion. No comparable study was found on Cochrane library, Clinical Trials, or Prospero. A total of 32 articles were eligible for full-text screening and were examined in detail according to the pre-specified PICOT criteria. A manual search of references from these studies and reviews did not yield any additional records. A total of 22 were excluded (see Table A1) after full-text assessment for the following reasons: No diagnostic accuracy design [23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40] (n = 18), no empyema in the study collective [41] (n = 1), case-report [42] (n = 1), no reference test [43] (n = 1), and empyema as negative collective [44].

3.2. Data Extraction/Characteristics of the Included Studies Population

Finally, 10 studies were included in the quantitative synthesis (meta-analysis) with a total of 1098 patients and 252 empyemas. The summary of the baseline characteristics is shown in Table 1. The mean patient age ranged from 56 to 72. All studies were a retrospective cohort study design.

3.3. Risk of Bias

The quality of included studies assessed by QUADAS-2 is summarized in Table 2. As illustrated, there is a substantial amount of underreporting in the included studies, resulting in many “unclear” judgments which consequently diminish the quality of the data. None of the studies reported whether the reference standard was blinded for the index test.

3.4. Categorization of Pleural Findings

There were 119 overlapping descriptions of which 99 describe the pleura, pleural effusion, or the adjoining adipose tissue, and 20 other findings such as lymphadenopathy, liver metastases, lung metastases, and pneumonia. Of these, duplicates were removed and 35 CT findings were assessed as descriptors of empyema. Of these findings, 11 findings were not included in the meta-analysis because they were described in less than 2 studies with the same negative collective (parapneumonic effusion, benign effusion, or pleural effusion in general). Table A2 summarizes the descriptors that were not used for the meta-analysis. Finally, similar descriptors (n = 24) referring to the same imaging finding were subsumed under the following five informative CT findings (visually summarized in Figure 2) after consensus discussion: Pleural enhancement (including the split pleura sign), “pleural thickening” (visible—4 mm), “loculation”, “fat thickening” (visible—4 mm), and “fat stranding”. Sensitivity, specificity, and DOR are summarized in Table A3. “Hemisplit pleura sign”, “circumferential pleural thickening”, “pleural thickening ≥ 4 mm”, and “fat thickening > 5 mm” were identified as non-informative (2.5% DOR ≤ 1) and later excluded from the following analyses.

3.5. Results of Syntheses

Sensitivities for informative pleural findings independent of negative collective were 84% (95% CI 62–94) for pleural enhancement, 68% (95% CI 56–77) for pleural thickening, 52% (95% CI 44–59%) for loculation, 53% (95% CI 47–60) for fat thickening, and 39% (95% CI 32–48) for fat stranding, with corresponding specificities of 83% (95% CI 75–89), 87% (95% CI 80–92), 89% (95% CI 82–94), 91% (95% CI 72–96), and 97% (95% CI 94–98), respectively. The “split pleura sign” as a specific threshold for pleural enhancement was explicitly addressed in 2 studies [45,46] with a pooled sensitivity of 68% (95% CI 51–81) and a specificity of 83% (95% CI 71–91).
Table 3 summarizes the syntheses of the pleural findings. In addition, we analyzed the diagnostic accuracies of the negative collective for parapneumonic (Figure A1, Figure A2, Figure A3 and Figure A4), benign, and effusions in general (Table A5). For the distinction between empyema and parapneumonic effusion, pleural enhancement and thickening have the highest specificities (89% and 90%) with the highest AUCs (bivariate: 0.83 and 0.80). Figure A6 shows a scatter plot of the studies’ observed sensitivities against their standard error without significant asymmetry (only informative CT findings, Eggers Test: intercept = 0.70, t = 0.28, p = 0.786).

3.6. Empyema and Subgroup Analysis

If the CT findings are interpreted as different threshold values for the same diagnosis of empyema, the result is a pooled specificity of 90% (95% CI 86–93) and a sensitivity of 62% (95% CI 55–68) with an AUC of 0.80. Figure A5 shows the corresponding HSROC curve.
The individual pleural finding (p ≤ 0.001 for sensitivity and specificity), the prevalence of empyema (p = 0.04 for specificity), slice thickness (p < 0.001 for sensitivity), and whether a study published after 2000 (p = 0.01 for specificity) was identified as a source of heterogeneity with significant differences in pooled diagnostic accuracy measures of the subgroups.
Based on the random-effects model, there is a significant difference between the sensitivity (p ≤ 0.001) of the individual pleural findings, ranging from 84% for pleural enhancement to 39% for fat stranding. There is also a significant difference between the specificity (p ≤ 0.001), ranging from 83% for pleural enhancement to 97% for fat stranding. Sensitivities (84%, 68%, p = 0.14) and specificities (83%, 87%, p = 0.40) of pleural enhancement and pleural thickening do not differ significantly.
The empyema prevalence between the studies ranged from 11% [47] to 87% [48] with a significant effect on specificity (p = 0.04), and with a pooled specificity of 94% (95%CI: 88–97%) for studies with a prevalence > 30% versus 87% (95%CI 81–91%) < 30%. Mean prevalence was 34% compared to an expected prevalence of ~10% in parapneumonic effusions [5]. The mixed-effect model was significant for prevalence (0.01, tau2: 0.14, sampling variability H2: 1.28, residual heterogeneity I2: 21.87%), which accounts for 23.75% (R2) of heterogeneity.
The following slice thicknesses were used in the studies: 10 mm [49,50,53], 6.5–10 mm [48], 6–10 mm [54], 1.5–10 mm [51], 5 mm [52], and 3 mm [46], with a pooled specificity of 94% (95%CI 87–98%), 92% (95%CI 87–95%), 85% (95%CI 78–90%), 58% (95%CI 50–65%), and 88% (95%CI 81–93%). Sensitivities did not defer significantly (p: 0.634) with 66% (95%CI 52–77%) for 10 mm, 62% (95%CI 50–72%) for 5 mm, and 52% (95%CI 32–71%) for 3 mm.
Studies after 2000 showed higher pooled specificity with 92% (95%-CI 87–95%) compared to 84% (95%CI 78–88%), with an inverse tendency in sensitivity of 59% (>2000; 95%CI 50–67%) compared to 63% (<2000, 95%CI 54–71). The mixed-effect model (p = 0.02) estimated the amount of heterogeneity to be 4.92% (R2) for the year of publication (residual heterogeneity I2: 25.8%, sampling variability H2: 1.35). Figure 3 shows the metaregression for the covariate’s year and prevalence.
There was no significant difference between the negative collectives (sens: p = 0.96/spec: p = 0.84), the reference standard (sens: p = 0.26/spec: p = 0.99), and between the number of reviewers (sens: p = 0.75/spec: p = 0.24). A tabular representation of subgroup analysis can be found in Table A6.

4. Discussion

Informative CT findings had visible pleural enhancement (including split pleura sign), pleural thickening (<4 mm), loculation, subcostal fat thickening (<4 mm), and fat stranding. With those findings, detection of empyema using CT has a pooled specificity of 90% (95% CI 86–93), a sensitivity of 62% (95% CI 56–68), and an AUC of 0.80. Of those informative findings, pleural enhancement and pleural thickening had the highest sensitivities with 84% (95% CI 62–94) and 68% (95% CI 56–77), respectively, whereas fat stranding and fat thickening showed the highest specificities of 91% (95% CI 72–96) and 97% (95% CI 94–98), respectively.
Of the subsumed pleural findings, pleural enhancement and fat stranding had the highest DOR with 20.1 and 26.5. Smooth margin, microbubbles, or pleural gas showed relative high DORs in the narrative summary (range: 5.6 [46,48]–62.4 [49,50]). Despite comparable feature-definitions, there were frequently major differences in the DOR. For example, the DOR of visible fat stranding varied between 28.8 [48] and 19.2 [53] and the DOR of the “Split pleura sign” varied between 7.9 [46] and 44.8 [49]. The diagnostic value of the amount of effusion [47,50] and the presence of septations [47,49] remains unclear, as the available studies show controversial results with regard to the DOR.
While different studies used different CT findings to indicate thoracocentesis [46,56,57], the identified informative findings can be used to differentiate empyema from other pleural diseases in a more complete and standardized manner. This distinction is important because both clinical management and patient outcomes differ [10,58]. Because pleural effusions are managed conservatively, false-negative empyema diagnoses should be avoided, suggesting that more value should be given to sensitivity over specificity. Most of the included studies lacked detailed definition and description of CT findings [46,47,48,49,50,51,52], thereby limiting the analysis of different thresholds. However, since CT findings have relatively high specificity with lower sensitivity, no other lower threshold value can be recommended besides the visibility of the findings. However, a threshold greater than 4 mm for pleural thickening [53,54] and subcostal fat thickening [53] was not shown to be informative, mainly as this decreases the differentiability from a pleural tumor manifestation. Whereas pleural carcinomatosis is more likely to show nodular, rind-like, pleural thickening (>10 mm) [50,51] or a pleural-based soft tissue mass [50,51], empyema tends to show smooth pleural thickening [48,54].
In an attempt to maximize pleural enhancement, a dedicated CT protocol is warranted [59,60] to further increase the sensitivity of pleural enhancement and pleural thickening at the expense of a potential higher false-positive rate. In addition, more specific features including fat thickening and fat stranding should be utilized to achieve a higher overall diagnostic accuracy. With newer CT scanners and modern diagnostic monitors offering higher resolution, an ever-increasing higher sensitivity can be expected. Surprisingly, our study showed an inverse correlation when comparing sensitivity with the study date as well as no significant difference with decreasing slice-thickness. This could be partly explained by the fact that older studies only partially fulfilled the STARD criteria, and the patient flow in the included studies remained mostly unclear.
There are several limitations to this study. First, the number of included studies was limited, resulting in a paucity of data available for meta-analysis. Second, different CT parameters, especially concerning the administration of contrast medium, could only be compared to a limited extend, as these were not recorded in a standardized manner in the studies presented. This also applies to the slice thickness, as several studies used different CT scanners or CT settings and therefore only overlapping subgroups could be formed. Finally, we found high heterogeneity among the studies used, which can only be partially explained by the subgroup analyses. This might be mostly related to poor methodology and serious underreporting of the patient selection process. This is an important cause of concern and should be taken into consideration when interpreting the results

5. Conclusions

Our study concludes that an early diagnosis depends on a high index of suspicion. Combined with the presence of one (or more) of the several aforementioned informative pleural findings, the diagnosis of pleural empyema can be made with high specificity.

6. Future Directions

Imaging advances and a lack of evidence for the optimization of CT protocols with regards to contrast agent administration indicate the need for further studies. In addition to confirming the high specificity already shown in our review, this could lead to improvements in sensitivity. The CT imaging, which is often performed routinely, could thus become increasingly reliable and useful for therapy decisions in the management of pleural empyema.

Author Contributions

D.Z.: Conceptualization, Data curation and investigation, Methodology, Formal analysis, Validation, Visualization, and Writing-original draft. T.A.D.: Methodology, Writing-review & editing. A.W.-S.: Writing-review & editing. J.B.: Writing-review & editing, Project administration. J.A.R.: Methodology, and Writing-review & editing. R.S.: Conceptualization, Data curation and investigation, Methodology, Formal analysis, Project administration, Supervision, Validation, Visualization, and Writing-original draft. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was approved by the local ethics committee (EKNZ, Project ID: 2021-00946, approval date: 20 May 2021).

Informed Consent Statement

The patient with the empyema (Figure 2) signed the institutional consent form on 23 July 2018.

Data Availability Statement

Most data generated or analyzed during the study are included in the published paper. Additional data generated or analyzed during the study are available from the corresponding author by request.

Acknowledgments

We thank Christian Appenzeller-Herzog (information specialist) who helped to develop the search strategy.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A. Search Strategy

Pubmed: (“Empyema, Pleural”[Mesh] OR (empyema* [tiab] OR pyothorax [tiab]) AND (pleura* [tiab] OR lung [tiab])) AND (“Tomography, X-Ray Computed”[Mesh] OR “computer assisted tomography”[tiab] OR “computed tomography”[tiab] OR “computed tomographic scan”[tiab] OR “computed tomography scan” [tiab] OR “computer tomography” [tiab] OR “computerized tomography” [tiab] OR “computerized tomography” [tiab]) AND (“Data Accuracy/statistics and numerical data”[Mesh] OR “Sensitivity and Specificity”[Mesh] OR “ROC Curve”[Mesh] OR “Area Under Curve”[Mesh] OR accuracy* [tiab] OR sens* [tiab] OR speci* [tiab] OR ROC [tiab] OR AUC [tiab]).
Embase: (‘Empyema, pleural’/exp OR (empyema*: ti, ab OR pyothorax: ti, ab) AND (pleura*: ti, ab OR lung: ti, ab)) AND (‘Tomography, X-Ray Computed’/exp OR “computer assisted tomography”: ti, ab OR “computed tomography”: ti, ab OR “computed tomographic scan”: ti, ab OR “computed tomography scan”: ti, ab OR “computer tomography”: ti, ab OR “computerized tomography”: ti, ab OR “computerized tomography”: ti, ab) AND (‘Data Accuracy/statistics and numerical data’/exp OR ‘Sensitivity and Specificity’/exp OR ‘ROC Curve’/exp OR ‘Area Under Curve’/exp OR accuracy*:ti,ab OR sens*:ti, ab OR speci*: ti, ab OR ROC: ti, ab OR AUC: ti,ab).
Web of Science: (“Empyema, pleural” OR (empyema* OR pyothorax) AND (pleura* OR lung)) AND (“Tomography, X-Ray Computed” OR “computer assisted tomography” OR “computed tomography” OR “computed tomographic scan” OR “computed tomography scan” OR “computer tomography” OR “computerized tomography” OR “computerized tomography”) AND (“Data Accuracy/statistics and numerical data” OR “Sensitivity and Specificity” OR “ROC Curve” OR “Area Under Curve” OR accuracy* OR sens* OR speci* OR ROC OR AUC).

Appendix B. Extracted Data Items

The extracted data items were: (1) Expected outcome data were absolute numbers (number of true positive (TP), true negative (TN), false positive (FP), false negative (FN)) to calculate diagnostic accuracy measures, sensitivity, specificity, negative predictive value, positive predictive value, and AUC/ROC. (2) The various pleural findings were understood as prespecified thresholds for the diagnosis of empyema and were initially collected separately in the data collection since a threshold value for the diagnosis “empyema” from the combination of these findings has not yet been established. (3) A clear definition of the negative collective, as this is needed for comparison and pooling of the different identified studies (mainly: Parapneumonic effusions, benign effusions, and effusions in general). (4) A detailed description of computed tomography was included (vendor collimation, slice thickness, contrast, etc.). (5) Additional data items were: First author, published paper, study design, unit of assessment (per patient/ per effusion), prior testing, method of patient selection, number of participants, number of patients excluded (study overlap, insufficient test, no reference standard), number of empyemas (and prevalence), mean age, distribution of sex, definition of test positivity, thresholds of test positivity, number of readers and readers characteristics (e.g., years of professional experience), definition of the reference standard, the time interval between the reference standard and index test, country, year, follow-up, shortly conclusion, funding sources, and studied subgroups.

Appendix C. Study Risk of Bias and Assessment of the Methodological Quality

A customized QUADAS-2 [15] was used, based on the four domains of “study selection”, “index test”, “reference standard”, and “flow and timing”. After the assessment, disagreements were resolved by consensus. During the pilot review, there was frequent disagreement on the reference standard because most studies had a clear definition of the reference standard, but the handling of indeterminate, or missing data, or blinding for index tests was unclear. In those studies, we rated the risk of bias as “unclear”, but concerns regarding applicability as “low” because of the accepted reference standard.
Table
Table A1. Excluded studies.
Table A1. Excluded studies.
First AuthorJournal/MeetingPublication YearReason for Exclusion
Schmitt [23]Rofo1981No Diagnostic accuracy
Williford [24]Radiol Clin North Am.1983No Diagnostic accuracy
Snow [25]Chest1990No Diagnostic accuracy
Kohda [26]Nihon Kyobu Shikkan Gakkai Zasshi1994No Diagnostic accuracy
Beigelman [27]Rev Mal Respir.1998No Diagnostic accuracy
Kearney [28]Clin Radiol.2000No Diagnostic accuracy
Ellis [29]ER2002No Diagnostic accuracy
Smolikov [30]Clin Radiol2006No Diagnostic accuracy
Lee [31]J Comput Assit Tomogr.2006No Diagnostic accuracy
Heffner [32]Chest2010No Diagnostic accuracy
Franklin [33]BMJ2011No Diagnostic accuracy
Franklin [34]AJRCCM2012No Diagnostic accuracy
Valdés [35]Lung2013No Diagnostic accuracy
Yasnogorodsky [36]Khirurgiia2017No Diagnostic accuracy
Carlucci [37]Panminerva Med.2019No Diagnostic accuracy
Agrawal [38]Indian Journal of Surgery2020No Diagnostic accuracy
Das [39]Indian J Thorac Cardiovasc Surg2021No Diagnostic accuracy
Franklin [40]Clinical Radiology2021No Diagnostic accuracy
Kendrick [41]Pediatr Radiol.2002No Empyema
Ahmed [42]Semin Interven Radiol2012Case report
Iudin [43]Vestn Rentgenol Radiol1997No reference test
Liu [44]Journal of Acute Medicine2016Empyemas as the negative collective
Table
Table A2. Narrative summary of CT findings.
Table A2. Narrative summary of CT findings.
CT FindingTPFNFPTNNegative CollectiveSensitivity [95%-CI] Specificity [95%-CI]DOR [95%-CI]
Stark [49]septated104739A17.5 [9.8; 29.4]75.0 [46.8; 91.1]0.0 [0.0; 2.8 ]
smooth luminal margin52516A91.2 [81.1; 96.2]85.7 [48.7; 97.4]62.4 [6.2; 627]
Porcel [46]microbubbles131024103A56.5 [36.8; 74.4]81.1 [73.4; 87.0]5.6 [2.2; 14.2]
Metintas [50]smooth margin20641107C76.9 [57.9; 89.0]72.3 [64.6; 78.9]8.7 [3.3; 23.2]
Moderate or large effusion131310147C50.0 [32.4; 67.6]31.9 [24.9; 39.7]0.0 [0.0; 1.1]
Leung [51]Lung base
involvement		905510C95.0 [65.5; 99.5]15.9 [9; 26.6]3.6 [0.0; 66.6]
Tsujimoto [47]amount > 30 mm26101433B72.2 [56.0; 84.2]70.2 [56.0; 81.3]6.1 [2.3; 16.0]
gas pleural fluid1125245B30.6 [18.0; 46.9]95.7 [85.8; 98.8]9.9 [2.0; 48.3]
HU > 103152423B86.1 [71.3; 93.9]48.9 [35.3; 62.8]5.9 [2.0; 17.9]
Septum828245B22.2 [11.7; 38.1]95.7 [85.8; 98.8]6.4 [1.3; 32.5]
Jimenez [48]pleural gas6188203C25.0 [12.0; 44.9]96.2 [92.7; 98.1]8.5 [2.6; 27.1]
Negative collective: A = parapneumonic, B = benign effusions, and C = effusions in general.
Table
Table A3. Categorization of pleural findings, sensitivities, and specificities.
Table A3. Categorization of pleural findings, sensitivities, and specificities.
AuthorNeg. CollectiveThresholdTPFNFPTNSensitivity [95%-CI]Specificity [95%-CI]DOR [95%-CI]
fat strandingJimenez [48]Cvisible1113817946 [28.3; 64.7]95.5 [91.5; 97.6]18 [6.3; 51.1]
Bvisible111328446 [28.3; 64.7]97.1 [91.2; 99.1]28.8 [6.5; 126.9]
Avisible111322246 [28.3; 64.7]90 [72.5; 96.8]7.7 [1.7; 35.2]
Waite [53]Bvisible112402031.9 [19.1; 48.3]97.6 [80.8; 99.8]19.2 [1.1; 346.8]
Cvisible122305034.7 [21.3; 51.1]99 [91.3; 99.9]53.7 [3.1; 946.3]
fat thickeningJimenez [48]Bvisible159305662 [42.6; 78.2]64.9 [54.5; 74.1]3 [1.2; 7.6]
B>2 mm1212108450 [31.8; 68.2]88.9 [81.1; 93.8]8 [2.9; 22.2]
C>2 mm12121916850 [31.8; 68.2]89.6 [84.4; 93.2]8.6 [3.5; 21.5]
A>2 mm121222250 [31.8; 68.2]90 [72.5; 96.8]9 [2; 41.3]
Waite [53]Bvisible211411959.7 [43.5; 74]92.9 [74.1; 98.3]19.3 [3.2; 115.4]
Cvisible211442659.7 [43.5; 74]85.5 [69.2; 93.9]8.7 [2.6; 29]
C3–4 mm122305034.7 [21.3; 51.1]99 [91.3; 99.9]53.7 [3.1; 946.3]
loculationÇullu [52]Cvisible94227167.9 [42; 86]76.1 [66.5; 83.6]6.7 [2; 22.7]
Avisible9493867.9 [42; 86]80.2 [66.9; 89]8.6 [2.3; 32.3]
Bvisible94136067.9 [42; 86]81.8 [71.5; 88.9]9.5 [2.7; 33.6]
Jimenez [48]Bvisible101439142 [25; 61.1]96.3 [90.4; 98.6]18.9 [5; 71.6]
Avisible101422242 [25; 61.1]90 [72.5; 96.8]6.5 [1.4; 30.1]
Cvisible10141417342 [25; 61.1]92.3 [87.6; 95.3]8.7 [3.3; 22.6]
Stark [49]Avisible403701251.9 [41; 62.7]96.2 [71.7; 99.6]27 [1.5; 472.1]
pleural enhancementPorcel [46]Asplit pleura12111511252.1 [33.2; 70.4]87.9 [81.1; 92.5]7.9 [3; 20.6]
Stark [49]Asplit pleura391801068.1 [55.3; 78.6]95.5 [67.9; 99.5]44.8 [2.5; 807]
Tsujimoto [47]Bsplit pleura297123579.7 [64.3; 89.6]74 [60.1; 84.3]11.2 [4; 31.2]
Waite [53]Cvisible34184295.8 [83.8; 99]83.3 [70.9; 91.1]115 [19.1; 690.8]
Bvisible24182094.2 [78.4; 98.7]70.7 [52.5; 84]39.4 [6.3; 246.1]
pleural thickeningAquino [54]C2–4 mm64115959.1 [31.6; 81.9]83.8 [73.5; 90.6]7.5 [1.9; 29.1]
B2–4 mm6485259.1 [31.6; 81.9]86.1 [75.2; 92.6]8.9 [2.2; 36.3]
Çullu [52]Avisible7644353.6 [29.6; 76]90.6 [79.1; 96.1]11.2 [2.7; 46.6]
Bvisible7656853.6 [29.6; 76]92.6 [84.3; 96.7]14.4 [3.7; 56.2]
Cvisible76128153.6 [29.6; 76]86.7 [78.4; 92.1]7.5 [2.2; 25.2]
Jimenez [48]Bcostal186147274 [54.5; 87.1]83.3 [74.1; 89.7]14.2 [4.9; 40.9]
Ccostal1865713074 [54.5; 87.1]69.4 [62.5; 75.6]6.5 [2.5; 16.6]
Acostal18671774 [54.5; 87.1]70 [50.4; 84.3]6.6 [1.9; 22.9]
Cvisceral915518238 [21.8; 57.4]97.1 [93.6; 98.7]20.3 [6.3; 65.6]
Bvisceral91518538 [21.8; 57.4]98.3 [92.9; 99.6]34.9 [5.7; 212.4]
Avisceral91512338 [21.8; 57.4]94 [77.7; 98.6]9.6 [1.5; 60.3]
Leung [51]Bsmooth8162085 [54.1; 96.5]75.9 [57.3; 88.1]17.9 [2.6; 125.3]
Cvisceral90111595 [65.5; 99.5]57.4 [39; 74]25.6 [1.3; 486.5]
Bunilateral81313485 [54.1; 96.5]52.3 [40.4; 63.9]6.2 [1; 37.6]
Cvisceral90293695 [65.5; 99.5]55.3 [43.3; 66]23.5 [1.3; 420.9]
Metintas [50]Cdiffuse15115910957.4 [39; 74]64.8 [57.3; 71.6]2.5 [1.1; 5.7]
Stark [49]Bfocal111552542.6 [26; 61]82.3 [65.5; 91.9]3.4 [1; 11.4]
Cfocal11151914942.6 [26; 61]88.5 [82.8; 92.4]5.7 [2.3; 13.9]
Auniform5140992 [81.9; 96.7]95 [65.5; 99.5]217.4 [10.8; 4378.8]
Waite [53]Bvisible30502084.7 [69.7; 93]97.6 [80.8; 99.8]227.4 [11.9; 4338.3]
Cvisible30584284.7 [69.7; 93]83.3 [70.9; 91.1]27.7 [8.6; 89.3]
B3–4 mm122302034.7 [21.3; 51.1]97.6 [80.8; 99.8]21.8 [1.2; 391.7]
Negative collective: A = parapneumonic, B = benign effusions, and C = effusions in general.
Table
Table A4. DOR independent of negative collective.
Table A4. DOR independent of negative collective.
DORProportion [95%-CI]Tau2QAUC (Univariate)
enhancement21.08 [7.91–56.20]0.624.020.91
pleural thickening10.11 [6.88–14.87]0.2920.380.82
loculation9.40 [5.73–15.44]0.002.150.79
fat thickening7.99 [4.97–12.86]0.056.910.80
fat stranding17.88 [8.88–36.01]0.002.150.81
Table
Table A5. Diagnostic accuracy measures of pleural findings in benign effusions and effusions in general.
Table A5. Diagnostic accuracy measures of pleural findings in benign effusions and effusions in general.
CT FeaturePooled Sensitivity [95%-CI]Pooled Specificity [95%-CI]AUC (Bivariate)DOR [95%-CI]Tau2Cochrane QHeterogenity Chi2AUC: Univariate
Benign Effusionenhancement0.89
[0.60–0.98]		0.73
[0.62–0.82]		0.7620.1
[4.6–87.2]		0.51.002.28 *0.93
pleural thickening0.64
[0.46–0.79]		0.86
[0.77–0,92]		0.8513.5
[7.2–25.2]		0.28.0010.100.84
loculation0.55
[0.26–0.82]		0.92
[0.64–0.99]		0.8014.6
[5.6–38.4]		0.00.560.10 *0.80
fat thickening0.59
[49.4–67.2]		0.87
[0.68–0.95]		0.618.7
[3.1–24.1]		0.53.037.06 *0.87
fat stranding0.38
[0.26–0.53]		0.97
[0.92–0.99]		0.9626.5
[7.1–99.0]		0.00.060.03 *0.80
Effusion generalenhancement 10.97
[0.82–1.00]		0.84
[0.71–0.92]		0.977.9
[4.5–13.8]		NANANA0.98
pleural thickening0.65
[0.51–0.78]		0.79
[0.66–0.88]		0.787.9
[4.6–13.8]		0.37.068.150.81
loculation0.56
[0.26–0.82]		0.86
[0.67–0.96]		0.788.2
[3.8–17.8]		0.00.060.34 *0.75
fat thickening0.48
[0.32–0.64]		0.92
[0.79–0.97]		0.749.6
[4.8–19.6]		0.01.450.410.80
fat stranding0.40
[0.28–0.52]		0.96
[0.92–0.98]		0.7720.4
[7.6–54.6]		0.00.490.06 *0.80
Pleural findings marked with a 1 were only described in one study in the respective negative collective, which is why sensitivity, specificity, DOR, and AUC were not pooled and tau2, Cochrane Q, and Chi2 are not calculable (“NA”).* p < 0.05.
Table
Table A6. Subgroup analysis.
Table A6. Subgroup analysis.
Sensitivity [95%-CI]Tau2I2Specificity [95%-CI]Tau2I2
Random effect model 0.62 [0.55; 0.68]0.737367.3%0.90 [0.86; 0.93]1.135982.5%
Sensitivity [95%-CI]pQSpecificity [95%-CI]pQ
Negative collectiveAll0.63 [0.50; 0.74]0.92340.160.88 [0.80; 0.93]0.74850.58
Benign0.63 [0.52; 0.73]0.91 [0.84; 0.95]
Parapneumonic0.60 [0.48; 0.71]0.90 [0.84; 0.94]
Concerns regarding appicabilityYes0.69 [0.58; 0.78]0.19021.720.87 [0.80; 0.91]0.30761.04
No0.60 [0.52; 0.680.90 [0.85; 0.93]
Referencestandard for all patientsYes0.61 [0.54; 0.67]0.28791.130.89 [0.85; 0.92]0.99960.00
No0.75 [0.48; 0.90]1.00 [0.00; 1.00]
More than 1 reviewerYes0.60 [0.52; 0.67]0.52570.400.88 [0.83; 0.92]0.26051.27
No0.65 [0.52; 0.76]0.92 [0.86; 0.96]
Slice thickness10 mm0.66 [0.52; 0.77]0.6341.710.94 [0.87; 0.98]<0.00184.39
5 mm0.62 [0.50; 0.72]0.86 [0.80; 0.90]
3 mm0.52 [0.32; 0.71]0.88 [0.81; 0.93]
Study after 2000Yes0.59 [0.50; 0.67]0.44890.570.92 [0.87; 0.95]0.01316.15
No0.63 [0.54; 0.71]0.84 [0.78; 0.88]
Pleural findingpleural thickening0.68 [0.56; 0.77]0.000123.350.87 [0.80; 0.92]<0.000124.68
enhancement0.84 [0.62; 0.94]0.83 [0.75; 0.89]
fat stranding0.39 [0.32; 0.48]0.97 [0.94; 0.98]
fat thickening0.53 [0.47; 0.60]0.91 [0.82; 0.96]
loculation0.52 [0.44; 0.59]0.89 [0.82; 0.94]
Empyema prevalence<30%0.59 [0.52; 0.65]0.44910.570.87 [0.81; 0.91]0.03874.27
>30%0.64 [0.52; 0.74] 0.94 [0.88; 0.97]
High biasYes0.60 [0.52; 0.66]0.42700.630.88 [0.83; 0.92]0.22911.45
No0.66 [0.51; 0.78] 0.93 [0.85; 0.97]
Jimaging 08 00003 g0a1 550
Figure A1. Sensitivity of informative pleural findings to detect pleural empyema in parapneumonic effusions.
Figure A1. Sensitivity of informative pleural findings to detect pleural empyema in parapneumonic effusions.
Jimaging 08 00003 g0a1
Jimaging 08 00003 g0a2 550
Figure A2. Specificity of informative pleural findings to detect pleural empyema in parapneumonic effusions.
Figure A2. Specificity of informative pleural findings to detect pleural empyema in parapneumonic effusions.
Jimaging 08 00003 g0a2
Jimaging 08 00003 g0a3 550
Figure A3. DOR of informative pleural findings to detect pleural empyema in parapneumonic effusions.
Figure A3. DOR of informative pleural findings to detect pleural empyema in parapneumonic effusions.
Jimaging 08 00003 g0a3
Jimaging 08 00003 g0a4 550
Figure A4. HSROC in parapneumonic effusions: HSROC curve in black with confidence region (dashed line) of the pleural findings (A): Pleural thickening, (B): Loculation, (C): Fat thickening and (D): Pleural enhancement (each shown as a point and 95% confidence region as a gray ellipse).
Figure A4. HSROC in parapneumonic effusions: HSROC curve in black with confidence region (dashed line) of the pleural findings (A): Pleural thickening, (B): Loculation, (C): Fat thickening and (D): Pleural enhancement (each shown as a point and 95% confidence region as a gray ellipse).
Jimaging 08 00003 g0a4
Jimaging 08 00003 g0a5 550
Figure A5. HSROC for all pleural findings and all negative collectives: HSROC curve in black with confidence region (dashed line) of all pleural findings (each shown as a point and 95% confidence region as a gray ellipse) with an AUC of 0.80.
Figure A5. HSROC for all pleural findings and all negative collectives: HSROC curve in black with confidence region (dashed line) of all pleural findings (each shown as a point and 95% confidence region as a gray ellipse) with an AUC of 0.80.
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Jimaging 08 00003 g0a6 550
Figure A6. Scatter plot of sensitivities of the studies (only informative CT findings) compared to their standard error. The summary estimate is based on a random effects model.
Figure A6. Scatter plot of sensitivities of the studies (only informative CT findings) compared to their standard error. The summary estimate is based on a random effects model.
Jimaging 08 00003 g0a6

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Jimaging 08 00003 g001 550
Figure 1. Study flow chart according to PRISMA [45].
Figure 1. Study flow chart according to PRISMA [45].
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Jimaging 08 00003 g002 550
Figure 2. Pathological confirmed pleural empyema of an 83-year-old female patient. (A): Original axial slice with empyema on the right side. (B–D) Magnifications views with (B): Pleural fat thickening and increased attenuation (fat stranding) compared to the contralateral side. (C): Pleural thickening with an increased enhancement of the pleura. (D): Loculation (biconvex, acute marginal angles).
Figure 2. Pathological confirmed pleural empyema of an 83-year-old female patient. (A): Original axial slice with empyema on the right side. (B–D) Magnifications views with (B): Pleural fat thickening and increased attenuation (fat stranding) compared to the contralateral side. (C): Pleural thickening with an increased enhancement of the pleura. (D): Loculation (biconvex, acute marginal angles).
Jimaging 08 00003 g002
Jimaging 08 00003 g003 550
Figure 3. Mixed effect model for the moderator’s (A): “year” and (B): “empyema prevalence”. The dotted red line shows regression.
Figure 3. Mixed effect model for the moderator’s (A): “year” and (B): “empyema prevalence”. The dotted red line shows regression.
Jimaging 08 00003 g003
Table
Table 1. Descriptive statistics of the included studies.
Table 1. Descriptive statistics of the included studies.
StudyIndex Test: CTReference Standard
JournalYearDurationOCEBMIncluded (n)Mean Age (y)Female (n)Empyema (n)Vendor *i.v. Contrast (n)Contrast Agent **Delay (s)i.v. (mL)Rate (mL/s)Slice Thickness (mm)Rater (n)Experience (y)Procedure ***
Porcel [46]APSR1708–15215056NA23IV150b/c~6090–10033220 & 202 B
Tsujimoto [47]PloS one1506–14283721336NA23NANANANANA4101/2 B
Jimenez [48]ER99NA2211636624II/III/VIII211cNA100–1202–36.5–102NA2/3 B
Stark [49]AJR83NA463NANA58INAaNA150NA103NA1 (53%), A
Metintas [50]EJR0289–982215NANA26V215NANANANA104NA2 B/C
Leung [51]AJR9085–8927460219I/II58NANANANA102NA2 B
Cullu [52]DIR1410–123106NA4613IX58fNA100–3002–3.512NA2 B
Waite [53]Radiology90NA28557NA35I/II75a~201200.910NANA2 B
Aquino [54]Radiology94NA280582510II/VI80dNA60–2001.76–102NA2 B
Takasugi [55]BJR91NA224NANA18VII14eNA170NA10/30NANA1/2 B/D
Missing data are marked NA. * I: GE 8800 with a 10-mm slice thickness (ST), II: GE 9800 with a 10-mm ST, III: GE Pace Plus with a 6.5–10-mm ST, IV: Philips Brilliance with a 3-mm ST, V: Toshiba TCT 600 with a 10-mm ST, VI: Imatron Cine Scanner with a 6–8-mm ST, VII: Pixer 1200 SX with a 10-mm ST, VIII: Elscint Helicat II with a 6.5–10-mm ST, IX: Siemens Somatom emotion with a 5-mm ST. Note: I-III, V-VIII: Single slice, IV: 16/64 slice, IX: 16 slice. **: a: Diatrizoate meglumine, b: Iobitridol (Xenetix, Guerbet), c: Iopromide (Clarograf, Bayer), d: Iohexol (international nonproprietary name), e: Iothalamate meglumine (Conray, Guerbet), f: Iopamidol (international nonproprietary name). *** 1: Thoracotomy, 2: Thoracocentesis, 3: Biopsy, A: Clinical diagnosis, B: Culture/gram stain, C: Macroscopic purulent pleural fluid, D: Laboratory findings (pleural LDH/WBC/protein). Abbreviations: OCEBM-Level (Oxford Centre for Evidence Based Medicine). Y: Years. I.v.: Intravenous.
Table
Table 2. Evaluation according to the QUADAS-2 criteria.
Table 2. Evaluation according to the QUADAS-2 criteria.
Risk of Bias Applicability Concerns
StudyPatient SelectionIndex TestReference StandardFlow and TimingPatient SelectionIndex TestReference Standard
Porcel [46]lowlowunclearunclearlowlowlow
Tsujimoto [47]unclearlowunclearlowunclearlowlow
Jimenez [48]lowlowunclearhighlowlowlow
Stark [49]highlowunclearhighunclearlowhigh
Metintas [50]lowlowunclearhighlowlowlow
Leung [51]lowlowunclearhighlowlowlow
Cullu [52]unclearhighunclearlowunclearunclearunclear
Waite [53]lowunclearunclearlowlowlowlow
Aquino [54]lowlowunclearlowlowlowlow
Takasugi [55]unclearlowunclearunclearunclearlowlow
Table
Table 3. Syntheses of the pleural findings with the pooled sensitivities and specificities.
Table 3. Syntheses of the pleural findings with the pooled sensitivities and specificities.
EnhancementPleural ThickeningLoculationFat ThickeningFat Stranding
Sensitivity0.84 [95%-CI: 0.62–0.94]0.68 [0.56–0.77] 0.52 [0.44–0.59]0.53 [0.47–0.60]0.39 [0.32–0.48]
Tau 2: 13.740.950.000.020.00
Q: 17.1274.907.447.832.54
I 2: 76.60%72.00%19.30%10.60%0.00%
Specificity0.83 [95%-CI: 0.75–0.89]0.87 [0.80–0.92]0.89 [0.82–0.94]0.91 [0.82–0.96]0.97 [0.94–0.98]
Tau 2: 0.1112.140.480.820.00
Q: 7.20142.7523.1531.681.7
I 2: 44.40%85.30%74.10%77.90%0.00%
AUC (bivariate)0.860.810.750.680.79
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Zettinig, D.; D’Antonoli, T.A.; Wilder-Smith, A.; Bremerich, J.; Roth, J.A.; Sexauer, R. Diagnostic Accuracy of Imaging Findings in Pleural Empyema: Systematic Review and Meta-Analysis. J. Imaging 2022, 8, 3. https://doi.org/10.3390/jimaging8010003

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Zettinig D, D’Antonoli TA, Wilder-Smith A, Bremerich J, Roth JA, Sexauer R. Diagnostic Accuracy of Imaging Findings in Pleural Empyema: Systematic Review and Meta-Analysis. Journal of Imaging. 2022; 8(1):3. https://doi.org/10.3390/jimaging8010003

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Zettinig, Desiree, Tugba Akinci D’Antonoli, Adrian Wilder-Smith, Jens Bremerich, Jan A. Roth, and Raphael Sexauer. 2022. "Diagnostic Accuracy of Imaging Findings in Pleural Empyema: Systematic Review and Meta-Analysis" Journal of Imaging 8, no. 1: 3. https://doi.org/10.3390/jimaging8010003

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