Impact of Standardized Scheme on the Detection of Chest X-Ray Abnormalities and Radiographic Diagnosis of Pulmonary Tuberculosis in Adult
Author(s)
Marie Laure Gharingam,
Boniface Moifo*,
Eric Walter Pefura Yone,
André Pascal Kengne,
Jean Roger Moulion Tapouh,
Annick Laure Edzimbi,
Georges Nguefack-Tsague,
Samuel Nko’o Amvene
Affiliation(s)
Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, Yaounde, Cameroon. Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, Yaounde, Cameroon; Department of Medical Imaging and Radiation Therapy, The University of Yaoundé I, Yaoundé, Cameroon. Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, Yaounde, Cameroon; Department of Internal Medicine and Specialties, The University of Yaoundé I, Yaoundé, Cameroon; Service of Pulmonology, Yaounde Jamot Hospital, Yaounde, Cameroon. South African Medical Research Council & University of Cape Town, Cape Town, South Africa. Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, Yaounde, Cameroon; Department of Public Health, The University of Yaoundé I, Yaoundé, Cameroon.
Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, Yaounde, Cameroon. Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, Yaounde, Cameroon; Department of Medical Imaging and Radiation Therapy, The University of Yaoundé I, Yaoundé, Cameroon. Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, Yaounde, Cameroon; Department of Internal Medicine and Specialties, The University of Yaoundé I, Yaoundé, Cameroon; Service of Pulmonology, Yaounde Jamot Hospital, Yaounde, Cameroon. South African Medical Research Council & University of Cape Town, Cape Town, South Africa. Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, Yaounde, Cameroon; Department of Public Health, The University of Yaoundé I, Yaoundé, Cameroon.
ABSTRACT
Purpose: The complexity of chest radiography (CXR) is a source of variability in its interpretation. We assessed the effect of an interpretation grid on the detection of CXR anomalies and radio- graphic diagnosis of tuberculosis in an endemic area for tuberculosis. Methods: The study was conducted in Yaounde (Cameroon). Six observers (2 pulmonologists, 2 radiologists and 2 senior residents in medical imaging) interpreted 47 frontal CXR twice two months apart without (R1) and with (R2) the aid of an interpretation grid. We focused on the detection of micro nodules (n = 16), cavitations (n = 12), pleural effusion (n = 6), adenomegaly (n = 6), and diagnosis of tuberculosis (n = 23) and cancer (n = 7). Results: The average score for accurate detection of elementary lesions was 40.4% [95%CI: 25% - 58.3%] in R1 and 52.1% [36.9% - 65.3%] in R2. The highest im- provement was observed for micro nodules (19.8%). Cavitations had the highest proportions of accurate detections (58.3% in R1 and 65.3% in R2). The average score of accurate diagnosis was 46.1% in R1 and 57.4% in R2. Accurate diagnosis improved by 3.6% for tuberculosis and 19% for cancer between R1 and R2. Intra-observer agreement was higher for the diagnosis of cancers (0.22 ≤ k ≤ 1) than for diagnosing tuberculosis (0.21 ≤ k ≤ 0.68). Inter-observer agreement was highly variable with a modest improvement for the diagnosis of tuberculosis in R2. Conclusion: Standardized interpretation scheme improved the detection of CXR anomalies and diagnosis of tuberculosis. It significantly improved inter-observer’s agreement in diagnosing tuberculosis but not in detecting most lesions.
Purpose: The complexity of chest radiography (CXR) is a source of variability in its interpretation. We assessed the effect of an interpretation grid on the detection of CXR anomalies and radio- graphic diagnosis of tuberculosis in an endemic area for tuberculosis. Methods: The study was conducted in Yaounde (Cameroon). Six observers (2 pulmonologists, 2 radiologists and 2 senior residents in medical imaging) interpreted 47 frontal CXR twice two months apart without (R1) and with (R2) the aid of an interpretation grid. We focused on the detection of micro nodules (n = 16), cavitations (n = 12), pleural effusion (n = 6), adenomegaly (n = 6), and diagnosis of tuberculosis (n = 23) and cancer (n = 7). Results: The average score for accurate detection of elementary lesions was 40.4% [95%CI: 25% - 58.3%] in R1 and 52.1% [36.9% - 65.3%] in R2. The highest im- provement was observed for micro nodules (19.8%). Cavitations had the highest proportions of accurate detections (58.3% in R1 and 65.3% in R2). The average score of accurate diagnosis was 46.1% in R1 and 57.4% in R2. Accurate diagnosis improved by 3.6% for tuberculosis and 19% for cancer between R1 and R2. Intra-observer agreement was higher for the diagnosis of cancers (0.22 ≤ k ≤ 1) than for diagnosing tuberculosis (0.21 ≤ k ≤ 0.68). Inter-observer agreement was highly variable with a modest improvement for the diagnosis of tuberculosis in R2. Conclusion: Standardized interpretation scheme improved the detection of CXR anomalies and diagnosis of tuberculosis. It significantly improved inter-observer’s agreement in diagnosing tuberculosis but not in detecting most lesions.
KEYWORDS
Chest Radiography; Interpretation Scheme; Tuberculosis; Micro Nodules; Cavitations; Agreement
Chest Radiography; Interpretation Scheme; Tuberculosis; Micro Nodules; Cavitations; Agreement
Cite this paper
Laure Gharingam, M. , Moifo, B. , Walter Pefura Yone, E. , Pascal Kengne, A. , Roger Moulion Tapouh, J. , Laure Edzimbi, A. , Nguefack-Tsague, G. and Nko’o Amvene, S. (2014) Impact of Standardized Scheme on the Detection of Chest X-Ray Abnormalities and Radiographic Diagnosis of Pulmonary Tuberculosis in Adult. Open Journal of Medical Imaging, 4, 23-30. doi: 10.4236/ojmi.2014.41004.
Laure Gharingam, M. , Moifo, B. , Walter Pefura Yone, E. , Pascal Kengne, A. , Roger Moulion Tapouh, J. , Laure Edzimbi, A. , Nguefack-Tsague, G. and Nko’o Amvene, S. (2014) Impact of Standardized Scheme on the Detection of Chest X-Ray Abnormalities and Radiographic Diagnosis of Pulmonary Tuberculosis in Adult. Open Journal of Medical Imaging, 4, 23-30. doi: 10.4236/ojmi.2014.41004.
References
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[1] McAdams, H.P., Samei, E., Dobbins III, J. and Tourassi, D.G. (2006) Recent Advances in Chest Radiography. Radiology, 241, 663-683. http://dx.doi.org/10.1148/radiol.2413051535 [2] Remy, J., Remy-Jardin, M., Bonnel, F. and Masson, P. (2001) L’interprétation d’une Radiographie Thoracique Revue et Corrigée par la Tomodensitométrie. Journal de Radiologie, 82, 1067-1079. [3] Moifo, B., Tambe, J., Pefura Yone, E.W. and Zeh, O.F. (2012) Assessing the Role of Routine Chest Radiography in Asymptomatic Students during Registration at a University in an Endemic Area of Tuberculosis. Annals of Tropical Medicine & Public Health, 5, 419-422. http://dx.doi.org/10.4103/1755-6783.105122 [4] Neossi Guena, M., Moifo, B., Pefura Yone, E.W. and Mankaa Wankie, M. (2011) Influence des Protocoles d’Examen sur la Qualité et les Performances Diagnostiques d’une TDM Thoracique: Expérience du Service d’Imagerie Thoracique du CHRU de Lille (France). Journal Africain d’Imagerie Médicale, 6, 277-289. [5] Balabanova, Y., Cocker, R., Fedorin, I. and Zakharova, S. (2005) Variability in Interpretation of Chest Radiographs among Russian Clinicians and Implications for Screening Programmes: Observational Study. BMJ, 331, 1-4.
http://dx.doi.org/10.1136/bmj.331.7513.379 [6] Sakurada, S., Nguyen Hang, T.L., Ishizuka, N. and Toyota, E. (2012) Inter-Rater Agreement in the Anormal Chest X-Ray Findings for Tuberculosis between Two Asian Countries. BMC Infectious Diseases, 12, 1-8.
http://dx.doi.org/10.1186/1471-2334-12-31 [7] Van Cleeff, M.R., Kivihya-Ndugga, L.E., Meme, H. and Odhiambo, J.A. (2005) The Role of Performance of Chest X-Ray for the Diagnosis of Tuberculosis: A Cost Effectiveness Analysis in Nairobi, Kenya. BMC Infectious Diseases, 12, 111. http://www.biomedcentral.com/1471-2334/5/111 [8] Kumar, N., Bhargava, S.K., Agrawal, C.S. and George, K. (2005) Chest Radiographs and Their Reliability in the Diagnosis of Tuberculosis. Journal of the Nepal Medical Association, 44, 138-142. [9] Boon, S.D., Bateman, E.D., Enarson, A.D. and Borgdorff, N.W. (2005) Development and Evaluation of a New Chest Radiograph Reading and Recording for Epidemiological Surveys of Tuberculosis and Lung Disease. The International Journal of Tuberculosis and Lung Disease, 9, 1088-1096. [10] Graham, S., Gupta, K.D., Hidvegi, R.J. and Hanson, R. (2002) Chest Radiograph Abnormalities Associated with Tuberculosis: Reproductility and Yield of Active Cases. The International Journal of Tuberculosis and Lung Disease, 6, 137-142. [11] OMS Global Tuberculosis Report 2012.
http://apps.who.int/iris/bitstream/10665/75938/1/9789241564502_eng.pdf [12] Boulhabal, F. and Chaulet, P. (2004) La Tuberculose en Afrique: Epidémiologie et Mesures de Lutte. Medecine Tropicale, 64, 224-228. [13] Lorentz Quekel, G.B.A., Alphons Kessels, G.H., Goei, R. and Engelshoven, M.J.V. (2001) Detection of Lung Cancer on the Chest Radiograph: A Study on Observer Performance. European Journal of Radiology, 39, 111-116.
http://dx.doi.org/10.1016/S0720-048X(01)00301-1 [14] Hopstaken, R.M., Witbraad, T., Van Engelshoven, J.M.A. and Dinant, G. (2004) Inter-Observer Variation in the Interpretation of Chest Radiographs for Pneumonia in Community-Acquired Lower Respiratory Tract Infections. Clinical Radiology, 58, 478-481. http://dx.doi.org/10.1016/j.crad.2004.01.011 [15] Viera, J.A. and Garrett, J.M. (2005) Understanding Interobserver Agreement: The Kappa Statistic. Family Medicine, 37, 360-363. [16] Pefura Yone, E.W., Kengne, A.P., Moifo, B. and Kuaban, C. (2013) Prevalence and Determinants of Extrapulmonary Involvement in Patients with Pulmonary Tuberculosis in a Sub-Saharan African Country: A Cross-Sectional Study. Scandinavian Journal of Infectious Diseases, 45, 104-111.
http://dx.doi.org/10.3109/00365548.2012.714905 [17] Blum, A., Feldmann, L., Brester, F. and Jouanny, P. (1995) Intérêt du Calcul du Coefficient Kappa dans l’Evaluation d'une Méthode d’Imagerie. Journal of Radiology, 76, 441-443. [18] Fermanian, J. (1984) Mésure de l’Accord Entre Deux Juges. Cas Qualitatif. Revue d’Epidemiologie et de Santé Publique, 32, 140-147. [19] Sim, J. and Wright, C.C. (2005) The Kappa Statistic in Reliability Studies: Interpretation, and Sample Size Requirements. Physical Therapy, 85, 257-268. [20] Whitley, E. and Ball, J. (2002) Sample size Calculations. Critical Care, 6, 335-341.
http://dx.doi.org/10.1186/cc1521 [21] Zellweger, J.P., Heinzer, R., Touray, M. and Vidondo, B. (2006) Intra-Observer and Overall Agreement in the Radiological Assessment of Tuberculosis. The International Journal of Tuberculosis and Lung Disease, 10, 1123-1126. [22] Potchen, E.J., Cooper, T.G., Sierra, A.E. and Aben, G.R. (2000) Measuring Performance in Chest Radiography. Radiology, 217, 456-459. http://dx.doi.org/10.1148/radiology.217.2.r00nv14456 [23] Eisen, A.L., Berger, S.J., Hedge, A. and Schneider, F.R. (2006) Competency in Chest Radiograph: Comparism of Medical Students, Résidents, and Fellows. Journal of General Internal Medicine, 21, 460-465.
http://dx.doi.org/10.1111/j.1525-1497.2006.00427.x [24] Leslie, A., Jones, A.J. and Goddard, P. (2000) The Influence of Clinical Information on the Reporting of CT by Radiologists. The British Journal of Radiology, 73, 1052-1055.