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Spatial lung imaging advances offer non-invasive biomarkers for early lung disease detection and monitoring. Challenges in data handling and analysis persist despite progress in high-resolution imaging.

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Area of Science:

  • Pulmonary medicine
  • Medical imaging
  • Bioinformatics

Background:

  • Severe lung diseases require non-invasive biomarkers for early detection, diagnosis, and treatment monitoring.
  • Thoracic imaging presents challenges due to lung size, motion, and density variations.

Purpose of the Study:

  • To review recent advances in spatial lung imaging.
  • To discuss current challenges and future directions in the field.

Main Methods:

  • Review of current literature on spatial lung imaging techniques.
  • Analysis of technological advancements and their implications.

Main Results:

  • Spatial imaging now provides 3D lung structure and single-cell transcriptomic data.
  • Significant challenges include data storage, processing, AI integration, and multi-modal fusion.

Conclusions:

  • Spatial lung imaging is rapidly evolving, offering new diagnostic and monitoring capabilities.
  • Addressing data management and analytical challenges is crucial for realizing the full potential of this technology.