Reconstruction of a time-averaged midposition CT scan for radiotherapy planning of lung cancer patients using deformable registrationa)

2008 ◽  
Vol 35 (9) ◽  
pp. 3998-4011 ◽  
Author(s):  
J. W. H. Wolthaus ◽  
J.-J. Sonke ◽  
M. van Herk ◽  
E. M. F. Damen
2006 ◽  
Vol 65 (5) ◽  
pp. 1560-1571 ◽  
Author(s):  
Jochem W.H. Wolthaus ◽  
Christoph Schneider ◽  
Jan-Jakob Sonke ◽  
Marcel van Herk ◽  
José S.A. Belderbos ◽  
...  

2009 ◽  
Vol 92 ◽  
pp. S41
Author(s):  
N. Marmouk ◽  
E. Van Mierlo ◽  
B. Verhoeven ◽  
A. Arens ◽  
M. van de Pol

2021 ◽  
Vol 41 (2) ◽  
pp. 94-101
Author(s):  
Luths Maharina ◽  
Yusup Subagio Sutanto ◽  
Widiastuti Widiastuti ◽  
Sulistyani Kusumaningrum ◽  
Adam Prabata ◽  
...  

2019 ◽  
Vol 21 (Supplement_3) ◽  
pp. iii92-iii93
Author(s):  
E Kobyakova ◽  
E Nechipay ◽  
D Sashin ◽  
N Kobiakov ◽  
G L Kobyakov

Abstract BACKGROUND Brain metastases (BM) affect 8%-10% of all cancer patients and 40% of patients with metastatic cancer. The majority of BM originate from lung cancer (40%-50%), breast cancer (15%-25%), and melanoma (5%-20%). Total incidence proportions percentage (IP %) of brain metastases was reported as 9.6% for all primary sites combined, and was highest for lung cancer (19.9%). The incidence of BM is believed to be increasing, likely resulting from longer patient survival due to more effective systemic therapies for the primary cancer and the increased use of neuroimaging in neurologically asymptomatic patients. MATERIAL AND METHODS Our aim was to determine incidence of brain metastases in lung cancer patients at the time of primary diagnosis on cohort of our regular clinical practice. Since September 2014 till December 2017 189 primarily diagnosed patients with suspected lung cancer were evaluated with brain MRI as obligatory part of diagnostic protocol at N.N. Blokhin Russian Cancer Research Center. MR imaging protocol included T1, T2-weighted images, FLAIR, DWI, VIBE (with contrast enhancement, slice thickness <1.2 mm). According to diagnostic guidelines for lung cancer in Russia, all patients underwent chest CT scan with contrast enhancement, bronchoscopy, abdominal ultrasonography, ultrasonography of cervical lymph nodes (+ CT to evaluate detected abnormalities), bone scintigraphy with X-ray control of detected abnormalities, surgical removal (in case of T1-T2 tumor) or tumor biopsy to determine morphology. Additionally, all patients underwent Whole Body MR DWI, some patients received FDG-PET/CT scan. RESULTS Brain metastases were detected in 89 (48%) of 189 patients, while only 9 patients (10.1% of patients with brain metastases) had neurological deficits. Lesion sizes were as follows: 0.1–0.5 cm in 46 (51.7%) patients, 0.5–1.0 cm in 21 (23.6%) patients, 1.0–2.0 cm in 7 (7.9%) patients, 2.0–3.0 cm in 8 (9.0%) patients and >3.0 in 7 (7.9% patients). The majority of patients (45 - 50.56%) had solitary metastases, 10 patients (11.24%) had two lesions and 34 (38.20 %) patients had three and more lesions. Metastatic disease most commonly affected frontal lobes - 45 (50.56%) patients, temporal lobes - 36 (40.45%) patients, parietal lobes - 22 (24.72%) patients, occipital lobes - 22 (24.72%), basal ganglia and brainstem - 18 (20.22%), - 3 (3.37%), cerebellum - 30 (33.71%) patients. Concerning morphology, in 80 of 89 brain metastases NSCLC was identified and in 9 patients SCLC was observed. CONCLUSION Very high incidence of brain metastases in lung cancer patients at the time of primary diagnosis in our study cohort may be explained by the use of precision brain MRI as an obligatory part of diagnostic protocol at the time of primary admission. We suggest including precision brain MRI in guidelines for primary diagnosis of lung cancer patients as an obligatory examination


Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4823 ◽  
Author(s):  
Da-Chuan Cheng ◽  
Jen-Hong Chi ◽  
Shih-Neng Yang ◽  
Shing-Hong Liu

In this study, we proposed a semi-automated and interactive scheme for organ contouring in radiotherapy planning for patients with non-small cell lung cancers. Several organs were contoured, including the lungs, airway, heart, spinal cord, body, and gross tumor volume (GTV). We proposed some schemes to automatically generate and vanish the seeds of the random walks (RW) algorithm. We considered 25 lung cancer patients, whose computed tomography (CT) images were obtained from the China Medical University Hospital (CMUH) in Taichung, Taiwan. The manual contours made by clinical oncologists were taken as the gold standard for comparison to evaluate the performance of our proposed method. The Dice coefficient between two contours of the same organ was computed to evaluate the similarity. The average Dice coefficients for the lungs, airway, heart, spinal cord, and body and GTV segmentation were 0.92, 0.84, 0.83, 0.73, 0.85 and 0.66, respectively. The computation time was between 2 to 4 min for a whole CT sequence segmentation. The results showed that our method has the potential to assist oncologists in the process of radiotherapy treatment in the CMUH, and hopefully in other hospitals as well, by saving a tremendous amount of time in contouring.


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