Enhancing ¹⁸F-FDG-PET/CT analysis in lung cancer patients

Summary

Aim: To retrospectively evaluate the feasibility and value of CT-CT image fusion to assess the shift of peripheral lung cancers with/-out chest wall infiltration, comparing computed tomography acquisitions in shallow-breathing (SB-CT) and deep-inspiration breath-hold (DIBH-CT) in patients undergoing FDG-PET/ CT for lung cancer staging. Methods: Image fusion of SB-CT and DIBH-CT was performed with a multimodal workstation used for nuclear medicine fusion imaging. The distance of intrathoracic landmarks and the positional shift of tumours were measured using semitransparent overlay of both CT series. Statistical analyses were adjusted for confounders of tumour infiltration. Cutoff levels were calculated for prediction of no-/infiltration. Results: Lateral pleural recessus and diaphragm showed the largest respiratory excursions. Infiltrating lung cancers showed more limited respiratory shifts than non-infiltrating tumours. A large respiratory tumour-motility accurately predicted non-infiltration. However, the tumour shifts were limited and variable, limiting the accuracy of prediction. Conclusion: This pilot fusion study proved feasible and allowed a simple analysis of the respiratory shifts of peripheral lung tumours using CT-CT image fusion in a PET/CT setting. The calculated cutoffs were useful in predicting the exclusion of chest wall infiltration but did not accurately predict tumour infiltration. This method can provide additional qualitative information in patients with lung cancers with contact to the chest wall but unclear CT evidence of infiltration undergoing PET/CT without the need of additional investigations. Considering the small sample size investigated, further studies are necessary to verify the obtained results.

Zusammenfassung

Ziel ist die retrospektive Beurteilung des Nutzens der Bildfusion von zwei CT-Serien – CTScan in flacher Atmung (SB-CT) bzw. tiefer Inspiration (DIBH-CT) – die im Rahmen eines PET/CT-Protokolls akquiriert werden, um Unterschiede in der atemabhängigen Bewegung von peripheren Lungentumoren mit oder ohne Infiltration der Thoraxwand zu erfassen. Methoden: Die Bildfusion der SB-CTund DIBH-CT-Serien erfolgte mit Hilfe einer in der Nuklearmedizin etablierten multimodalen Workstation. Anhand der semitransparent Überlagerten CT-CT-Fusionsbilder wurden die Distanzen definierter intrathorakaler Landmarken und die Bewegung von peripheren Lungentumoren zwischen diesen Serien gemessen. Um die eigentliche Tumorbewegung von der Thoraxbewegung differenzieren zu können, erfolgten statistische Analysen zu Einflussfaktoren. Es wurden Schwellenwerte für die Vorhersage einer Infiltration bzw. Nicht-Infiltration in die Thoraxwand berechnet. Ergebnisse: Die größte atemabhängige Bewegung zeigten der laterale pleurale Recessus und die Zwerchfellkuppel. Infiltrierende Lungentumore wiesen im Vergleich zu nicht-infiltrierenden Tumoren eine verminderte Beweglichkeit auf, wobei eine große Beweglichkeit mit einem hohen positiven Vorhersagewert für die Nicht-Infiltration verbunden war. Insgesamt war die Tumorbeweglichkeit jedoch gering, was die Genauigkeit der Vorhersage limitierte. Schlussfolgerung: Die vorliegende Pilotstudie stellt eine einfache Möglichkeit vor, mit Hilfe der CT-CT-Bildfusion im Rahmen einer PET/CT-Studie die Bewegung intrathorakaler Landmarken und peripherer Lungentumore zu bestimmen. Mit Hilfe der berechneten Schwellenwerte konnte eine Infiltration der Thoraxwand sicher ausgeschlossen werden, während eine genaue Vorhersage einer Infiltration nicht möglich war. Die Methode kann bei unklaren CT-Befunden hinsichtlich einer Thoraxwandinfiltration eine hilfreiche Ergänzung im Rahmen der PET/CT-Diagnostik von Lungenkarzinomen sein. Um die Ergebnisse zu verifizieren, sind weitere Studien mit größeren Patientenzahlen notwendig.

Keywords

Respiratory tumour shift - software-assisted image fusion - bronchial carcinoma - tumour movement - pleural infiltration - CT-CT image fusion

Schlüsselwörter

Atemabhängige Tumorverschieblichkeit - Software- assistierte Bildfusion - Bronchialkarzinom - Tumorbewegung - pleurale Infiltration - CT-CT-Bild-Fusion

• References

• 1 Akata S, Kajiwara N, Park J. et al. Evaluation of chest wall invasion by lung cancer using respiratory dynamic MRI. J Med Imaging Radiat Oncol 2008; 52: 36-39.
• 2 Bandi V, Lunn W, Ernst A. et al. Ultrasound vs. CT in detecting chest wall invasion by tumor: a prospective study. Chest 2008; 133: 881-886.
• 3 Boussuges A, Gole Y, Blanc P. Diaphragmatic motion studied by m-mode ultrasonography: methods, reproducibility, and normal values. Chest 2009; 135: 391-400.
• 4 Bruzzi JF, Munden RF. PET/CT imaging of lung cancer. J Thorac Imaging 2006; 21: 123-136.
• 5 Chira R, Chira A, Mircea PA. Intrathoracic tumors in contact with the chest wall - ultrasonographic and computed tomography comparative evaluation. Med Ultrason 2012; 14: 115-119.
• 6 Delbeke D, Coleman RE, Guiberteau MJ. et al. Procedure guideline for tumor imaging with ¹⁸F-FDG PET/CT 1.0. J Nucl Med 2006; 47: 885-895.
• 7 Giraud P, De Rycke Y, Dubray B. et al. Conformal radiotherapy (CRT) planning for lung cancer: analysis of intrathoracic organ motion during extreme phases of breathing. Int J Radiat Oncol Biol Phys 2001; 51: 1081-1092.
• 8 Glazer HS, Duncan-Meyer J, Aronberg DJ. et al. Pleural and chest wall invasion in bronchogenic carcinoma: CT evaluation. Radiology 1985; 157: 191-194.
• 9 Hanley J, Debois MM, Mah D. et al. Deep inspiration breath-hold technique for lung tumors: the potential value of target immobilization and reduced lung density in dose escalation. Int J Radiat Oncol Biol Phys 1999; 45: 603-611.
• 10 Jacobs I, Vanregemorter J, Scalliet P. Influence of respiration on calculation and delivery of the prescribed dose in external radiotherapy. Radiother Oncol 1996; 39: 123-128.
• 11 Jin X, Han C, Zhou Y. et al. A modified VMAT adaptive radiotherapy for nasopharyngeal cancer patients based on CT-CT image fusion. Radiat Oncol 2013; 8: 277.
• 12 Kodalli N, Erzen C, Yuksel M. Evaluation of parietal pleural invasion of lung cancers with breath-hold inspiration and expiration MRI. Clin Imaging 1999; 23: 227-235.
• 13 Kolar P, Neuwirth J, Sanda J. et al. Analysis of diaphragm movement during tidal breathing and during its activation while breath holding using MRI synchronized with spirometry. Physiol Res 2009; 58: 383-392.
• 14 Lindner O, Burchert W, Schäfers M, Schaefer W. Myocardial perfusion scintigraphy 2012 in Germany. Results of the 6th Query. Nuklearmedizin 2014; 53: 13-18.
• 15 Liu HH, Balter P, Tutt T. et al. Assessing respiration-induced tumor motion and internal target volume using four-dimensional computed tomography for radiotherapy of lung cancer. Int J Radiat Oncol Biol Phys 2007; 68: 531-540.
• 16 Pearlberg JL, Sandler MA, Beute GH. et al. Limitations of CT in evaluation of neoplasms involving chest wall. J Comput Assist Tomogr 1987; 11: 290-293.
• 17 Pennes DR, Glazer GM, Wimbish KJ. et al. Chest wall invasion by lung cancer: limitations of CT evaluation. AJR Am J Roentgenol 1985; 144: 507-511.
• 18 Ratto GB, Piacenza G, Frola C. et al. Chest wall involvement by lung cancer: computed tomographic detection and results of operation. Ann Thorac Surg 1991; 51: 182-188.
• 19 Roach PJ, Schembri GP, Bailey DL. V/Q scanning using SPECT and SPECT/CT. J Nucl Med 2013; 54: 1588-1596.
• 20 Sakai S, Murayama S, Murakami J. et al. Bronchogenic carcinoma invasion of the chest wall: evaluation with dynamic cine MRI during breathing. J Comput Assist Tomogr 1997; 21: 595-600.
• 21 Shirakawa T, Fukuda K, Miyamoto Y. et al. Parietal pleural invasion of lung masses: evaluation with CT performed during deep inspiration and expiration. Radiology 1994; 192: 809-811.
• 22 Vansteenkiste J, De Ruysscher D, Eberhardt WE. et al. Early and locally advanced non-small-cell lung cancer (NSCLC): ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol 2013; 24 (Suppl 6) vi89-vi98.
• 23 Wade OL. Movements of the thoracic cage and diaphragm in respiration. The J Physiol 1954; 124: 193-212.
• 24 Webb WR, Higgins CB. Thoracic Imaging: Pulmonary and Cardiovascular Radiology. Lippincott Williams & Wilkins; 2010
• 25 Wittekind C. TNM atlas: illustrated guide to the TNM classification of malignant tumours. Hoboken NJ: Wiley-Liss: John Wiley; 2005: xiv-428.