Histopathology is the gold standard in cancer diagnosis. However, attenuated total reflectance (ATR)-Fourier transform ...

In the validation cohort, the new model achieved an ROC-AUC of 0.83 for detecting lung cancer across all participants, with a sensitivity of 94%, a specificity of 63%, a PPV of 79%, and an NPV of 89%.

In the validation cohort, the eNose detected lung cancer in 72 of 121 (60%) participants, resulting in an ROC-AUC of 0.83, sensitivity of 94%, specificity of 63%, PPV of 79%, and NPV of 89%.

Slightly lower values were observed in the validation cohort with an AUC-ROC of 0.79 (95% CI, 0.72-0.85), 88% sensitivity, 52% specificity and 87% negative predictive value.

Dynamic MRI did not improve the AUC compared with three-dimensional MRI alone. However, the specificity of a washout pattern for 123 of 136 patients without cancer was 90.4% (95% CI, 84% - 95%).