PURPOSE: A prospective feasibility study was conducted to investigate the utility of dual-energy (DE) imaging compared to conventional x-ray imaging for patients undergoing kV-based image guided radiation therapy (IGRT) for lung cancer. METHODS AND MATERIALS: An institutional review board-approved feasibility study enrolled patients with lung cancer undergoing IGRT and was initiated in September 2011. During daily setup, 2 sequential respiration-gated x-ray images were obtained using an on-board imager. Imaging was composed of 1 standard x-ray image at 120 kVp (1 mAs) and a second image obtained at 60 kVp (4 mAs). Weighted logarithmic subtraction of the 2 images was performed offline to create a soft tissue-selective DE image. Conventional and DE images were evaluated by measuring relative contrast and contrast-to-noise ratios (CNR) and also by comparing spatial localization, using both approaches. Imaging dose was assessed using a calibrated ion chamber. RESULTS: To date, 10 patients with stage IA to IIIA lung cancer were enrolled and 57 DE images were analyzed. DE subtraction resulted in complete suppression of overlying bone in all 57 DE images, with an average improvement in relative contrast of 4.7 ± 3.3 over that of 120 kVp x-ray images (P<.0002). The improvement in relative contrast with DE imaging was seen for both smaller (gross tumor volume [GTV] ≤5 cc) and larger tumors (GTV >5 cc), with average relative contrast improvement ratios of 3.4 ± 4.1 and 5.4 ± 3.6, respectively. Moreover, the GTV was reliably localized in 95% of the DE images versus 74% of the single energy (SE images, (P=.004). Mean skin dose per DE image set was 0.44 ± 0.03 mGy versus 0.43 ± 0.03 mGy, using conventional kV imaging parameters. CONCLUSIONS: Initial results of this feasibility study suggest that DE thoracic imaging may enhance tumor localization in lung cancer patients receiving kV-based IGRT without increasing imaging dose.
PURPOSE: A prospective feasibility study was conducted to investigate the utility of dual-energy (DE) imaging compared to conventional x-ray imaging for patients undergoing kV-based image guided radiation therapy (IGRT) for lung cancer. METHODS AND MATERIALS: An institutional review board-approved feasibility study enrolled patients with lung cancer undergoing IGRT and was initiated in September 2011. During daily setup, 2 sequential respiration-gated x-ray images were obtained using an on-board imager. Imaging was composed of 1 standard x-ray image at 120 kVp (1 mAs) and a second image obtained at 60 kVp (4 mAs). Weighted logarithmic subtraction of the 2 images was performed offline to create a soft tissue-selective DE image. Conventional and DE images were evaluated by measuring relative contrast and contrast-to-noise ratios (CNR) and also by comparing spatial localization, using both approaches. Imaging dose was assessed using a calibrated ion chamber. RESULTS: To date, 10 patients with stage IA to IIIA lung cancer were enrolled and 57 DE images were analyzed. DE subtraction resulted in complete suppression of overlying bone in all 57 DE images, with an average improvement in relative contrast of 4.7 ± 3.3 over that of 120 kVp x-ray images (P<.0002). The improvement in relative contrast with DE imaging was seen for both smaller (gross tumor volume [GTV] ≤5 cc) and larger tumors (GTV >5 cc), with average relative contrast improvement ratios of 3.4 ± 4.1 and 5.4 ± 3.6, respectively. Moreover, the GTV was reliably localized in 95% of the DE images versus 74% of the single energy (SE images, (P=.004). Mean skin dose per DE image set was 0.44 ± 0.03 mGy versus 0.43 ± 0.03 mGy, using conventional kV imaging parameters. CONCLUSIONS: Initial results of this feasibility study suggest that DE thoracic imaging may enhance tumor localization in lung cancerpatients receiving kV-based IGRT without increasing imaging dose.
Authors: Linxi Shi; Minghui Lu; N Robert Bennett; Edward Shapiro; Jin Zhang; Richard Colbeth; Josh Star-Lack; Adam S Wang Journal: Med Phys Date: 2020-05-18 Impact factor: 4.071
Authors: John C Roeske; Hassan Mostafavi; Maksat Haytmyradov; Adam Wang; Daniel Morf; Luca Cortesi; Murat Surucu; Rakesh Patel; Roberto Cassetta; Liangjia Zhu; Mathias Lehmann; Matthew M Harkenrider Journal: Adv Radiat Oncol Date: 2020-03-02
Authors: Maksat Haytmyradov; Hassan Mostafavi; Adam Wang; Liangjia Zhu; Murat Surucu; Rakesh Patel; Arun Ganguly; Michelle Richmond; Roberto Cassetta; Matthew M Harkenrider; John C Roeske Journal: Med Phys Date: 2019-06-01 Impact factor: 4.071
Authors: Maksat Haytmyradov; Hassan Mostafavi; Roberto Cassetta; Rakesh Patel; Murat Surucu; Liangjia Zhu; John C Roeske Journal: Med Phys Date: 2020-01-10 Impact factor: 4.071
Authors: Shailaja Sajja; Young Lee; Markus Eriksson; Håkan Nordström; Arjun Sahgal; Masoud Hashemi; James G Mainprize; Mark Ruschin Journal: Adv Radiat Oncol Date: 2019-07-30
Authors: Kevin Nguyen; Maksat Haytmyradov; Hassan Mostafavi; Rakesh Patel; Murat Surucu; Alec Block; Matthew M Harkenrider; John C Roeske Journal: Front Oncol Date: 2018-07-31 Impact factor: 6.244