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This paper introduces NeoNet, an end-to-end 3D deep learning framework for non-invasive prediction of perineural invasion (PNI) in cholangiocarcinoma from MRI scans. NeoNet uses a 3D Latent Diffusion Model (LDM) conditioned on anatomical masks to generate synthetic image patches, balancing the dataset and improving prediction accuracy. The final classification module, PNI-Attention Network (PattenNet), leverages the frozen LDM encoder and 3D Dual Attention Blocks (DAB) to achieve a maximum AUC of 0.7903, outperforming baseline 3D models.
Overcoming the challenge of limited and inconsistent imaging criteria for perineural invasion (PNI) diagnosis, NeoNet achieves state-of-the-art prediction accuracy by generating synthetic training data with a 3D Latent Diffusion Model.
Minimizing invasive diagnostic procedures to reduce the risk of patient injury and infection is a central goal in medical imaging. And yet, noninvasive diagnosis of perineural invasion (PNI), a critical prognostic factor involving infiltration of tumor cells along the surrounding nerve, still remains challenging, due to the lack of clear and consistent imaging criteria criteria for identifying PNI. To address this challenge, we present NeoNet, an integrated end-to-end 3D deep learning framework for PNI prediction in cholangiocarcinoma that does not rely on predefined image features. NeoNet integrates three modules: (1) NeoSeg, utilizing a Tumor-Localized ROI Crop (TLCR) algorithm; (2) NeoGen, a 3D Latent Diffusion Model (LDM) with ControlNet, conditioned on anatomical masks to generate synthetic image patches, specifically balancing the dataset to a 1:1 ratio; and (3) NeoCls, the final prediction module. For NeoCls, we developed the PNI-Attention Network (PattenNet), which uses the frozen LDM encoder and specialized 3D Dual Attention Blocks (DAB) designed to detect subtle intensity variations and spatial patterns indicative of PNI. In 5-fold cross-validation, NeoNet outperformed baseline 3D models and achieved the highest performance with a maximum AUC of 0.7903.
NVIDIA