Abstract
Purpose
To evaluate the influence of slice thickness, reconstruction algorithm and tube current (mA) on the performance of a software package in determining the volume of solid pulmonary nodules on multidetector-row computed tomography (MDCT).
Materials and methods
A chest phantom containing artificial solid nodules with known volume was imaged with two MDCT scans at 100 and 40 mAs (200 mA and 80 mA, 0.5-s rotation time), respectively. Data were reconstructed with slice thicknesses of 1.25 and 2.5 mm and five different algorithms. The volumes of three nodules (juxtavascular, intraparenchymal, juxtapleural) were calculated using three-dimensional (3D) volumetric software. Differences between estimated and real volume were reported for each nodule and reconstruction set.
Results
The software segmented all nodules on 1.25-mmthick reconstructions, independently from the mAs. It did not segment the juxtapleural nodule on 2.5-mm-thick reconstructions at 40 mAs. Mean values of the differences, which better approximated the real volume of the nodules, were obtained with high-spatial-resolution algorithms on both 100 and 40 mAs images at 1.25-mm slice thickness.
Conclusions
Slice thickness, reconstruction algorithm and tube current can affect the 3D volume measurement of solid nodules. The best performance of the software, on both 100 and 40 mAs images, was observed with a slice thickness of 1.25 mm and high-spatial-resolution algorithms.
Riassunto
Obiettivo
Valutare l’influenza di spessore di strato, algoritmo di ricostruzione e corrente del tubo (mA) sulla performance di un software nella volumetria dei noduli polmonari solidi in TC multidetettore (TCMD).
Materiali e metodi
Il torace di un fantoccio, contenente noduli solidi artificiali di volume noto, è stato sottoposto a due scansioni TCMD, rispettivamente a 100 e 40 mAs (200 mA e 80 mA, tempo di rotazione di 0,5 s). I dati sono stati ricostruiti con spessori di strato di 1,25 e 2,5 mm e cinque differenti algoritmi. È stato calcolato il volume di tre noduli (iuxtavascolare, centroparenchimale, iuxtapleurico) con software tridimensionale (3D) e riportate le differenze tra volume stimato e reale, per ciascun nodulo e ricostruzione.
Risultati
Il software ha segmentato tutti i noduli nelle ricostruzioni a spessore di strato di 1,25 mm, indipendentemente dai mAs. Non ha segmentato il nodulo iuxtapleurico a 2,5 mm e a 40 mAs. I kernel ad alta risoluzione spaziale hanno fornito valori medi di differenze dei volumi più prossimi al volume reale dei noduli nelle ricostruzioni a 1,25 mm, sia a 100 che a 40 mAs.
Conclusioni
Spessore di strato, algoritmo di ricostruzione e corrente del tubo possono influenzare la volumetria 3D dei noduli solidi. Lo spessore di 1,25 mm e gli algoritmi ad alta risoluzione hanno consentito la migliore performance del software, sia a 100 che a 40 mAs.
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References/Bibliografia
Feragalli B, Guido F, Larici AR et al (2005) Il nodulo polmonare. Radiol Med 110:294–316
Ko JP, Rusinek H, Jacobs EL et al (2003) Small pulmonary nodules: volume measurement at chest CT-phantom study. Radiology 228:864–870
Zerhouni EA, Stitik FP, Siegelman SS et al (1986) CT of the pulmonary nodule: a cooperative study. Radiology 160:319–327
Henschke CI, McCauley DI, Yankelevitz DF et al (1999) Early Lung Cancer Action Project: overall design and findings from baseline screening. Lancet 354:99–105
Munden RF, Pugatch RD, Liptay MJ et al (1997) Small pulmonary lesions detected at CT: clinical importance. Radiology 202:105–110
Yankelevitz DF, Reeves AP, Kostis WJ et al (2000) Small pulmonary nodules: volumetrically determined growth rates based on CT evaluation. Radiology 217:251–256
Revel MP, Merlin A, Peyrard S et al (2006) Software volumetric evaluation of doubling times for differentiating benign versus malignant pulmonary nodules. AJR Am J Roentgenol 187:135–142
Revel MP, Bissery A, Bienvenu M et al (2004) Are two-dimensional CT measurements of small noncalcified pulmonary nodules reliable? Radiology 231:453–458
Yankelevitz DF, Henschke CI (2000) Small solitary pulmonary nodules. Radiol Clin North Am 38:471–478
Jennings SG, Winer-Muram HT, Tarver RD et al (2004) Lung Tumor Growth: assessment with CT-comparison of diameter and cross-sectional area with volume measurements. Radiology 231:866–871
Revel MP, Lefort C, Bissery A et al (2004) Pulmonary Nodules: preliminary experience with three-dimensional evaluation. Radiology 231:459–466
Marten K, Grillhosl A, Seyfarth T et al (2005) Computer-assisted detection of pulmonary nodules: evaluation of diagnostic performance using an expert knowledge-based detection system with variable reconstruction slice thickness settings. Eur Radiol 15:203–212
Kim SJ, Kim JH, Cho G et al (2005) Automated detection of pulmonary nodules on CT images: effect of slice thickness and reconstruction interval. Initial results. Radiology 236:295–299
Kuhnigk JM, Dicken V, Bornemann L et al (2006) Morphological segmentation and partial volume analysis for volumetry of solid pulmonary lesions in thoracic CT scans. IEEE Trans Med Imaging 25:417–434
Muramatsu Y, Tsuda Y, Nakamura Y (2003) The development and use of a chest phantom for optimizing scanning techniques on a variety of low-dose helical computed tomography devices. J Comput Assist Tomogr 27:364–374
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Larici, A.R., Storto, M.L., Torge, M. et al. Automated volumetry of pulmonary nodules on multidetector CT: influence of slice thickness, reconstruction algorithm and tube current. Preliminary results. Radiol med 113, 29–42 (2008). https://doi.org/10.1007/s11547-008-0231-3
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DOI: https://doi.org/10.1007/s11547-008-0231-3