Dosimetry Comparison of Palliative Radiation Plans Generated From Available Diagnostic CT Images Versus Dedicated CT Simulation for Inpatients

Abstract Background Bronchoscopy serves as direct visualisation of the airway. Virtual bronchoscopy provides similar visual information using a non-invasive imaging procedure(s). Early and accurate image-guided diagnosis requires the possible highest performance, which might be approximated by combining anatomical and functional imaging. This communication describes an advanced functional virtual bronchoscopic (fVB) method based on the registration of PET images to high-resolution diagnostic CT images instead of low-dose CT images of lower resolution obtained from PET/CT scans. PET/CT and diagnostic CT data were collected from 22 oncological patients to develop a computer-aided high-precision fVB. Registration of segmented images was performed using elastix. Results For virtual bronchoscopy, we used an in-house developed segmentation method. The quality of low- and high-dose CT image registrations was characterised by expert’s scoring the spatial distance of manually paired corresponding points and by eight voxel intensity-based (dis)similarity parameters. The distribution of (dis)similarity parameter correlating best with anatomic scoring was bootstrapped, and 95% confidence intervals were calculated separately for acceptable and insufficient registrations. We showed that mutual information (MI) of the eight investigated (dis)similarity parameters displayed the closest correlation with the anatomy-based distance metrics used to characterise the quality of image registrations. The 95% confidence intervals of the bootstrapped MI distribution were [0.15, 0.22] and [0.28, 0.37] for insufficient and acceptable registrations, respectively. In case of any new patient, a calculated MI value of registered low- and high-dose CT image pair within the [0.28, 0.37] or the [0.15, 0.22] interval would suggest acceptance or rejection, respectively, serving as an aid for the radiologist. Conclusion A computer-aided solution was proposed in order to reduce reliance on radiologist’s contribution for the approval of acceptable image registrations.

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Comparison of radiomic features in diagnostic CT images with and without contrast enhancement in the delayed phase for NSCLC patients

Physica Medica ◽

10.1016/j.ejmp.2019.12.019 ◽

2020 ◽

Vol 69 ◽

pp. 176-182 ◽

Cited By ~ 4

Author(s):

Ryo Kakino ◽

Mitsuhiro Nakamura ◽

Takamasa Mitsuyoshi ◽

Takashi Shintani ◽

Hideaki Hirashima ◽

...

Keyword(s):

Contrast Enhancement ◽

Ct Images ◽

Nsclc Patients ◽

Delayed Phase ◽

Diagnostic Ct

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Estimation of bone mineral density in children from diagnostic CT images: A comparison of methods with and without an internal calibration standard

Bone ◽

10.1016/j.bone.2010.12.012 ◽

2011 ◽

Vol 48 (5) ◽

pp. 1087-1094 ◽

Cited By ~ 18

Author(s):

Alexander H. Habashy ◽

Xiaowei Yan ◽

J. Keenan Brown ◽

Xiaoping Xiong ◽

Sue C. Kaste

Keyword(s):

Bone Mineral Density ◽

Bone Mineral ◽

Ct Images ◽

Comparison Of Methods ◽

Calibration Standard ◽

Mineral Density ◽

Internal Calibration ◽

Diagnostic Ct

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Deep learning-based artifact detection for diagnostic CT images

Medical Imaging 2019: Physics of Medical Imaging ◽

10.1117/12.2511766 ◽

2019 ◽

Cited By ~ 1

Author(s):

Prakhar Prakash ◽

Sandeep Dutta

Keyword(s):

Deep Learning ◽

Ct Images ◽

Artifact Detection ◽

Diagnostic Ct

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The impact of different simulation modalities on target volume delineation in breast-conserving radiotherapy

10.21203/rs.3.rs-27116/v1 ◽

2020 ◽

Author(s):

Meng Jin ◽

Xia Liu ◽

Jiabin Ma ◽

Xiansong Sun ◽

Hongnan Zhen ◽

...

Keyword(s):

Ct Images ◽

Conformity Index ◽

Mr Images ◽

Mean Values ◽

Surgical Clips ◽

Tumor Bed ◽

Volume Delineation ◽

Ct Simulation ◽

The Mean ◽

The Impact

Abstract Background In the management of breast-conserving radiotherapy, computed tomography (CT) simulation is now commonly used to identify tumor bed while has difficult ies defining precisely. We aimed to evaluate the impact of magnetic resonance (MR) and CT simulation on defining the postoperative tumor bed for breast-conserving radiotherapy in patients without the aid of surgical clips. Methods From August 2018 to March 2019, twenty patients with T 1 - 2 N 0 M 0 breast cancer at our situation were enrolled. All the patients underwent breast-conserving surgery without implantation of surgical clips and were prepared to receive radiotherapy. CT and MR images were acquired on the same day for each patient. Three radiation oncologists independently assigned cavity visualization score (CVS) and delineated the tumor bed based on first the CT then the MR images with a 14-day interval for each patient. Interobserver variability was assessed by volumes, generalized conformity index (CI gen ) and the distance between the centers of mass (dCOM). Differences in mean values for parameters were tested by paired t -test or one-way analysis of variance, as appropriate. Results The median age of the enrolled patients was 48 years old. First, the mean volumes of tumor bed derived from MR were 22%, 27% and 21% smaller than those based on CT images for each observer. Second, the mean CI gen was significantly superior, and dCOM was smaller for MR than for CT images (CI gen : 0.59 vs 0.52, P = 0.008; dCOM: 1.30 cm vs 1.39 cm, P = 0.095). Third, the mean CVS was 3.23±1.34 and 2.43±0.92 for MR and CT images, respectively ( P = 0.035). In the subgroup with a CT-based CVS≥3, the mean dCOM obtained from CT was larger than that from the MR images (1.35 cm vs 1.19 cm, P = 0.048). Last, there was a positive association between the CVS and CI gen for both modalities (CT: r = 0.699, P = 0.001; MR: r = 0.895, P ＜ 0.001). Conclusion Compared to CT, MR can improve the visualization of changes in the postoperative tumor bed. In addition, MR can yield a more precise definition of the tumor bed and improve the consistency of tumor bed contouring in patients without surgical clips.

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