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Diagnostic importance of maximum intensity projection technique in the identification of small pulmonary nodules with computed tomography

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Tuberk Toraks 2020;68(2):196-197 Diagnostic importance of MIP technique in the identification of small pulmonary nodules

196

Diagnostic importance of maximum

intensity projection technique in the

identification of small pulmonary nodules

with computed tomography

doi • 10.5578/tt.69776

Tuberk Toraks 2020;68(2):196-197

Geliş Tarihi/Received: 19.06.2020 • Kabul Ediliş Tarihi/Accepted: 14.07.2020

Pınar GÜLERYÜZ KIZIL1(ID)

Koray HEKİMOĞLU2(ID) Mehmet COŞKUN2(ID) Şule AKÇAY3(ID)

1Department of Radiology, Faculty of Medicine, TOBB Economy and

Technology University, Ankara, Turkey

1TOBB Ekonomi ve Teknoloji Üniversitesi Tıp Fakültesi, Radyoloji Anabilim

Dalı, Ankara, Türkiye

2Department of Radiology, Baskent University Hospital, Ankara, Turkey 2Başkent Üniversitesi Ankara Hastanesi, Radyoloji Bölümü, Ankara, Türkiye 3Department of Chest Diseases, Baskent University Hospital, Ankara, Turkey 3Başkent Üniversitesi Ankara Hastanesi, Göğüs Hastalıkları Bölümü,

Ankara, Türkiye

EDİT

ÖRE MEKTUP

LETTER

T

O

THE

EDIT

OR

To the Editor,

Various studies in adults show that axial MIP images can increase the accuracy and speed of small nodule detection compared to conventional thin section axial CT (1,2). There is a significant grad-ual improvement in nodule detection using MIP in conjunction with axial images in adults and reduces inter-observer variability (3). For these reasons, we absolutely correlate MIP images with thin section axial images during nodule detection in our patients. However, in our experience, performing nodule detection by look-ing at MIP images alone may cause misdiagnosis especially when there are underlying lung diseases. In most of the studies performed so far, as in our study, the underlying parenchymal diseases are not included in the study, as they may prevent optimal nodule detec-tion. Gruden et al. (4) excluded patients with nodules larger than 1 cm in diameter or with complicating pleural or parenchymal dis-ease as this may interfere with optimal nodule identification. Kilburn et al. (3) excluded children with nodules larger than 10 mm as they would look comfortable in both imaging datasets and back-ground lung disease to avoid confusion. Valencia et al. (1) separated Dr. Pınar GÜLERYÜZ KIZIL

TOBB Ekonomi ve Teknoloji Üniversitesi Tıp Fakültesi, Radyoloji Anabilim Dalı, ANKARA - TÜRKİYE

e-mail: pnrglryz84@gmail.com

Yazışma Adresi (Address for Correspondence)

Cite this article as: Güleryüz Kızıl P, Hekimoğlu K,

Coşkun M, Akçay Ş. Diagnostic importance of maximum intensity projection technique in the identification of small pulmonary nodules with computed tomography. Tuberk Toraks 2020;68(2):196-197.

©Copyright 2020 by Tuberculosis and Thorax. Available on-line at www.tuberktoraks.org.com

(2)

Tuberk Toraks 2020;68(2):196-197

Güleryüz Kızıl P, Hekimoğlu K, Coşkun M, Akçay Ş.

197

nodules by giving confidence level (1, no nodule; 2, no confident nodule; 3, probable nodule; 4, more definite nodule; 5, definite nodule). İn their study with scar tissue determined pleural nodules or lesions together, misinterpretation of pulmonary vessels and ground glass density were classified with a confidence level of 1. Kawel et al. (5) excluded patients with lung disease (eg consolidations, interstitial lung disease). Peloschek et al. (6) did not include patients with con-comitant pulmonary abnormalities such as extensive scar, pneumonia, fibrosis or edema. In our current experience; when it has diseases such as fibrosis or emphysema in the lung parenchyma, it predicts that the nodule-disease separation is difficult and causes overdiagnose and reduces sensitivity and specfity so we did not include these patients in our study.

In most of the studies on MIP, solid nodules were included in the study. In our study, we did not include ground glass nodules as they can cause confusion, as in underlying lung diseases. Valencia et al. (1) per-formed the study by giving confidence level and deter-mined the confidence levels of ground glass nodules as 1. In addition, Scholten et al. (7) explained the some overlooked nodules in the study of non-solid nodules by the fact that the ground-glass appearance looks solid in MIP images. Our experience supports this. We did not include ground glass nodules in our study to remove confusion and avoid overdiagnose.

For this reasons, it is absolutely necessary to confirm MIP images with thin section images in nodule evalu-ations.

REFERENCES

1. Valencia R, Denecke T, Lehmkuhl L, et al. Value of axial and coronal maximum intensity projection (MIP) images in the detection of pulmonary nodules by multislice spiral CT: comparison with axial 1-mm and 5-mm slices. Eur Radiol 2006;16:325-32.

2. Jankowski A, Martinelli T, Timsit JF, et al. Pulmonary nodule detection on MDCT images: evaluation of diagnostic per-formance using thin axial images, maximum intensity pro-jections, and computer-assisted detection. Eur Radiol 2007;17:3148-56.

3. Kilburn F, Arthurs O, Tasker AD, Set P. Detection of pulmo-nary nodules at paediatric CT: maximum intensity projec-tions and axial source images are complementary. Pediatr Radiol 2013;43:820-6.

4. Gruden JF, Ouanounou S, Tigges S. Incremental benefit of maximum-intensity-projection images on observer detec-tion of small pulmonary nodules revealed by multidetector CT. AJR Am J Roentgenol 2002;179:149-57.

5. Kawel N, Seifert B, Luetolf M, Boehm T. Effect of slab thick-ness on the CT detection of pulmonary nodules: use of sliding thin slab maximum intensity projection and volume rendering. AJR Am J Roentgenol 2009;192:1324-9. 10.2214/AJR. 08.1689.

6. Peloschek P,  Sailer J,  Weber M, Herold CJ, Prokop M, Schaefer-Prokop C. Pulmonary nodules: sensitivity of max-imum intensity projection versus that of volume rendering of 3D multidetector CT data. Radiology 2007;243(2):561-9.

7. Scholten ET, Mali W, Prokop M, Ginnekan BV, Glandorf R, Klaveren RV, et al. Non-solid lung nodules on low-dose computed tomography: comparison of detection rate between 3 visualization techniques. Cancer Imaging 2013;13(2):150-4.

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