Utility of PET/CT in the diagnosis and staging of lung cancer after ecobronchoscopy in mining population

SummaryAim: 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.

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STEREOTACTIC HYPO-FRACTIONAL RADIOTHERAPY OF PATIENTS WITH LUNG CANCER I-IIA CLINICAL STAGE: THE ROLE OF SUVMAX ASSESSMENT IN 18F-FDG PET/CT FOR MONITORING TREATMENT OUTCOMES

Problems in oncology ◽

10.37469/0507-3758-2017-63-4-632-638 ◽

2017 ◽

Vol 63 (4) ◽

pp. 632-638

Author(s):

Tatyana Borisova ◽

Arif Allakhverdiev ◽

Yuriy Gerasimov ◽

Nadezhda Meshcheryakova ◽

Mikhail Dolgushin ◽

...

Keyword(s):

Lung Cancer ◽

Treatment Effectiveness ◽

Clinical Stage ◽

First Year ◽

Pet Ct ◽

History Of ◽

Single Factor Analysis ◽

Fdg Pet Ct ◽

Second Tumor ◽

Monitoring Treatment

Material and methods: Since 2014, 33 patients with lung cancer of clinical stage I-IIa (cT1N0M0 - 12 patients, with T2N0M0 - 21 patients) have undergone SRT. Verification of tumor process was obtained in 30 patients. A third of patients (n = 10) had a history of metachronic primary-multiple tumors and 31 patients had peripheral lung cancer. The used variants of SRT fractionation were as followed: 10Gr x 5 fractions (n = 22) and 7Gr x 8 fractions (n = 11) - BED 100Gy. Results: With a median follow-up of 21 months (range 3-37 months), 4 patients (12 %) within the first year had a loco-regional and distant progression, of which two died. During the year one patient died from complications of treatment, one - from the progression of the second tumor. One- and two-year local control was 94 %. Overall and disease-free 2-year survival was 84 % (95 % CI, 70 - 99) and 83.2 % (95 % CI, 70.5 - 99), respectively. Single-factor analysis revealed a significant effect on the overall survival of the fractionation regimen (p = 0.04). The effect of the baseline SUVmax tended to be reliable (p = 0.07). Conclusions: In order to implement the principles of risk-adaptive radiation therapy it is necessary to consider the initial SUVmax of tumor as one of potential predictive and predicative markers of treatment effectiveness.

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A Novel Adaptive PET/CT Image Fusion Algorithm

Current Bioinformatics ◽

10.2174/1574893613666180704153946 ◽

2019 ◽

Vol 14 (7) ◽

pp. 658-666

Author(s):

Kai-jian Xia ◽

Jian-qiang Wang ◽

Jian Cai

Keyword(s):

Lung Cancer ◽

Image Fusion ◽

High Frequency ◽

Malignant Tumors ◽

Low Frequency ◽

Combination Method ◽

Ct Image ◽

Fusion Algorithm ◽

Pet Ct ◽

Frequency Components

Background: Lung cancer is one of the common malignant tumors. The successful diagnosis of lung cancer depends on the accuracy of the image obtained from medical imaging modalities. Objective: The fusion of CT and PET is combining the complimentary and redundant information both images and can increase the ease of perception. Since the existing fusion method sare not perfect enough, and the fusion effect remains to be improved, the paper proposes a novel method called adaptive PET/CT fusion for lung cancer in Piella framework. Methods: This algorithm firstly adopted the DTCWT to decompose the PET and CT images into different components, respectively. In accordance with the characteristics of low-frequency and high-frequency components and the features of PET and CT image, 5 membership functions are used as a combination method so as to determine the fusion weight for low-frequency components. In order to fuse different high-frequency components, we select the energy difference of decomposition coefficients as the match measure, and the local energy as the activity measure; in addition, the decision factor is also determined for the high-frequency components. Results: The proposed method is compared with some of the pixel-level spatial domain image fusion algorithms. The experimental results show that our proposed algorithm is feasible and effective. Conclusion: Our proposed algorithm can better retain and protrude the lesions edge information and the texture information of lesions in the image fusion.

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Comparison between silicon photomultiplier-based and conventional PET/CT in patients with suspected lung cancer—a pilot study

EJNMMI Research ◽

10.1186/s13550-019-0504-y ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 1

Author(s):

Johan Economou Lundeberg ◽

Jenny Oddstig ◽

Ulrika Bitzén ◽

Elin Trägårdh

Keyword(s):

Lung Cancer ◽

Expectation Maximization ◽

Image Interpretation ◽

Imaging Study ◽

Reconstruction Algorithm ◽

Tnm Staging ◽

Reconstruction Algorithms ◽

Silicon Photomultiplier ◽

Standardized Uptake Values ◽

Pet Ct

Abstract Background Lung cancer is one of the most common cancers in the world. Early detection and correct staging are fundamental for treatment and prognosis. Positron emission tomography with computed tomography (PET/CT) is recommended clinically. Silicon (Si) photomultiplier (PM)-based PET technology and new reconstruction algorithms are hoped to increase the detection of small lesions and enable earlier detection of pathologies including metastatic spread. The aim of this study was to compare the diagnostic performance of a SiPM-based PET/CT (including a new block-sequential regularization expectation maximization (BSREM) reconstruction algorithm) with a conventional PM-based PET/CT including a conventional ordered subset expectation maximization (OSEM) reconstruction algorithm. The focus was patients admitted for 18F-fluorodeoxyglucose (FDG) PET/CT for initial diagnosis and staging of suspected lung cancer. Patients were scanned on both a SiPM-based PET/CT (Discovery MI; GE Healthcare, Milwaukee, MI, USA) and a PM-based PET/CT (Discovery 690; GE Healthcare, Milwaukee, MI, USA). Standardized uptake values (SUV) and image interpretation were compared between the two systems. Image interpretations were further compared with histopathology when available. Results Seventeen patients referred for suspected lung cancer were included in our single injection, dual imaging study. No statically significant differences in SUVmax of suspected malignant primary tumours were found between the two PET/CT systems. SUVmax in suspected malignant intrathoracic lymph nodes was 10% higher on the SiPM-based system (p = 0.026). Good consistency (14/17 cases) between the PET/CT systems were found when comparing simplified TNM staging. The available histology results did not find any obvious differences between the systems. Conclusion In a clinical setting, the new SiPM-based PET/CT system with a new BSREM reconstruction algorithm provided a higher SUVmax for suspected lymph node metastases compared to the PM-based system. However, no improvement in lung cancer detection was seen.

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