1250P - Assessing lung carcinoma: A retrospective study on volume evaluation, consolidation and infiltration using chest OMX

Background

We conducted a retrospective analysis to evaluate the volume of the lungs and determine the presence of infiltration and consolidation. To accurately interpret anisotropies and voxel spacings and to maintain resilience even when dealing with unbalanced class distributions, we used nnU-Net with quantitative and qualitative assessments to detect Lung infiltration. Utilizing TCGA-LUAD data (Lung Adenocarcinoma) and TCGA-LUSC (Lung Squamous cell carcinoma) this retrospective study on segmentation for volumetric and consolidation assessments are conducted. Chest OMX is a diagnostic tool that can assess lung volume, which in turn enables various applications such as monitoring recurrence from the changes in Lung volume; identifying infiltration and response to the treatment from Lung Volume and lobes, and detecting abnormalities in the lung from Consolidation. By providing quantitative score values, it assists in tracking changes over time and facilitating decision-making in clinical diagnosis.

Methods

We used nnU-Net, a popular deep-learning framework designed for medical image segmentation tasks. By analyzing the volume, infiltration, and consolidation characteristics of a lung carcinoma on CT scans, we can assess the tumor's behavior and response to treatment. From regional lung segmentation invasion, the burden is calculated. Additionally, measurements of discovered lung lesions and dedication to the relevant lung lobe are performed, along with fully automated lung lobe segmentation. Lobe 3D uses a deep learning system to measure the volume of the five lobes of the lung. HAA is also analyzed towards the end. Patient cases are selected irrespective of their ages from the TCGA cohort group. The primary outcome was the assessment of lung volume and the extent of the infiltration.

Results

Table: 1250P

Chest OMX: Generated diagnosis report for the case TCGA-LUSC

Conclusions

The diagnostic tool, Chest OMX can analyze the lung tissue from CT scans to determine the volume, consolidation and extent of infiltration by cancerous cells.

Clinical trial identification

Editorial acknowledgement

The dataset acknowledgment for,

1.Albertina, B., Watson, M., Holback, C., Jarosz, R., Kirk, S., Lee, Y., Rieger-Christ, K., & Lemmerman, J. (2016). The Cancer Genome Atlas Lung Adenocarcinoma Collection (TCGA-LUAD) (Version 4) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.JGNIHEP5.[Data Citation]

2. Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., & Prior, F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. In Journal of Digital Imaging (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC. \https://doi.org/10.1007/s10278-013-9622-7.[TCIA Citation]

3.Kirk, S., Lee, Y., Kumar, P., Filippini, J., Albertina, B., Watson, M., Rieger-Christ, K., & Lemmerman, J. (2016). The Cancer Genome Atlas Lung Squamous Cell Carcinoma Collection (TCGA-LUSC) (Version 4) [Data set]. The Cancer Imaging Archive. \https://doi.org/10.7937/K9/TCIA.2016.TYGKKFMQ.[Data Citation]

Legal entity responsible for the study

PMX.Inc., USA and PMX, South Korea.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.