Presence Of Solitary Pulmonary Nodule Research Articles

PET Counting Response Variability Depending on Tumor Location, Activity, and Patient Obesity: A Feasibility Study of Solitary Pulmonary Nodule Using Monte Carlo.

We aim to investigate the counting response variations of positron emission tomography (PET) scanners with different detector configurations in the presence of solitary pulmonary nodule (SPN). Using experimentally validated Monte Carlo simulations, the counting performance of four different scanner models with varying tumor activity, location, and patient obesity is represented using a noise equivalent count rate (NECR). NECR is a well-established quantitative metric which has positive correlation with clinically perceived image quality. The combined effect of tumor displacement and increased activity shows a linear ascending trend for NECR with slope ranges of (12.5-18.2)*10-3 (kBq/cm3)-1 for three-ring (3R) scanners and (15.3-21.5)*10-3 (kBq/cm3)-1 for four-ring (4R). The trend for the combined effect of tumor displacement and patient obesity is exponential decay with 3R configurations weakly dependent on the patient obesity if the tumor is located at the center of the field of view with exponent's range of (6.6-33.8)*10-2cm-1. The dependence is stronger for 4R scanners (9.6-38.5)*10-2cm-1. The analysis indicates that quantitative PET data from the same SPN patient possibly examined in different time points (e.g., during staging or for the evaluation of treatment response) are affected by the different detector configurations and need to be normalized with patient weight, activity, and tumor location to reduce unwanted bias of the diagnosis. This paper provides also with a proof of concept for the ability of properly tuned simulations to provide additional insights into the counting response variability especially in tumor types where often borderline decisions have to be made regarding their characterization.

1-Dimensional quantitative micro-architecture mapping of multiple scattering media using backscattering of ultrasound in the near-field: Application to nodule imaging in the lungs

In this letter, we present a near-field method for mapping the micro-architecture of complex media based on the measurement of the diffusion constant D using multiple backscattering of ultrasound waves. Simulation results are reported and validated with experiments. For both simulations and experiments, a linear array of ultrasound transducers is used. The coherent and incoherent intensities are separated using a matrix manipulation of the inter-element response matrix. We demonstrate that no beamforming is necessary to extract the diffusion constant. Acquiring sub-inter-element response matrices by using subsets of elements and calculating the growth of the diffusive halo for each sub-matrix provides an estimate of a semi-local diffusion constant, enabling a 1-D mapping of the scatterer density or volume fraction in a strongly heterogeneous medium. This methodology is then applied to quantitatively characterize the lung parenchyma and detect the presence of solitary pulmonary nodules. The semi-local diffusion constant is mapped along the transducer axis to search for high D values, which correspond to the nodule/lesion location.

Techniques for Detection of Solitary Pulmonary Nodules in Human Lung and Their Classifications -A Survey

Lung cancer is proving to be a catastrophic threat to the mankind and is main cause of deaths among other cancer related casualties. The presence of solitary pulmonary nodules in human lungs in the form of benign or malignant determines the gravity of lung ailment. This survey focusses on different techniques used to detect and classify the lung nodules which in turn will assist the domain experts for better diagnosis. Among many imaging modalities Computed Tomography (CT) being the most sought after because of its high resolution, isotropic acquisition which helps in locating the lung lesions. Since the volume of the CT scans are very large, Computer Aided Detection/Diagnosis (CAD/x) has more advantages in addition to manual interpretation with respect to speed and accuracy. This paper attempts to summarize various methods that have been proposed by several authors over the years of their research.

Imagerie des tumeurs myofibroblastiques inflammatoires du poumon

Inflammatory myofibroblastic tumors are ubiquitous but most frequently affect the lung. The imaging features are non-specific but the diagnosis may be suggested in the presence of solitary pulmonary nodule or mass in children or young adults. The tumor may appear locally and regionally aggressive suggesting malignancy. Diagnostic confirmation is obtained from histological evaluation of the surgical specimen. Treatment is surgical with oncologic surgical resection.

SU‐FF‐T‐189: Dosimetry of Small Pulmonary Nodules: A Comparison Between Treatment Planning Calculations and In‐Phantom Measurements

Purpose: To evaluate the accuracy of three commercially available treatment planning systems (Philips Pinnacle, Brainlab Brainscan, and Radionics Xknife) in their ability to calculate dose distributions delivered to small pulmonary nodules. Method and Materials: A radiological equivalent lung phantom consisting of cork (0.26 g/cm3) and acrylic spheres (∼1, 2, and 4 cm diameters) was constructed to simulate the presence of solitary pulmonary nodules. Single beam, 3D conformal, and IMRT treatment plans were generated for the lung phantom on each planning system. Evaluation was accomplished by comparing the dose distributions predicted by each planning system to the in‐phantom dose distributions measured with radiochromic film. Evaluations were made based on dose profiles and gamma analysis. Results: For single beams, the location of the largest disagreement between the measured and predicted dose distributions occurred at the distal side of the embedded nodule. The differences between measured and predicted doses in the distal edge of the medium sphere were 3%, 8%, and 23% for Pinnacle, Brainscan, and Xknife respectively. For 3D conformal medium sphere plans the largest differences between measured and predicted doses were 2%, 11%, and 13% for Pinnacle, Brainscan, and Xknife respectively. Gamma analysis showed the largest errors at the nodule/lung interface. Similar results were found for the IMRT plans. The largest errors were found for the smallest nodules in all three systems. Conclusion: As expected, the collapsed cone convolution algorithm of Pinnacle yielded the best agreement between predicted and measured doses in solitary lung nodules, with the largest differences at 3–5% for single beams, 3D conformal and IMRT plans. Brainscan and Xknife differed at points from 4% to 23% for the single beams, 3D conformal and IMRT plans. A systematic review of the results will be presented.