# Microscopic EB-OCT imaging to predict progression in interstitial lung abnormalities

> **NIH NIH R01** · MASSACHUSETTS GENERAL HOSPITAL · 2024 · $837,883

## Abstract

Project Summary
Progressive pulmonary fibrosis (PPF) is debilitating with poor prognosis. Antifibrotic therapies in PPF slow
progression but do not reverse or stabilize disease. Thus, timing of therapy is key to improving outcomes,
especially if started in presymptomatic stages prior to lung function decline. To prove the efficacy of early therapy,
clinical trials will require prognostic enrichment with biomarkers to accurately identify presymptomatic individuals
at high risk of developing PPF. Interstitial lung abnormalities (ILA) on CT are linked to increased risk of PPF, but
not all ILAs will progress (progression rate ~30-60%) and CT is unable to distinguish ILAs that will progress to
PPF from those that are of no clinical consequence. The main limitation of CT is its resolution, which is insufficient
to detect microscopic features. Surgical lung biopsy (SLB) provides tissue for microscopy, but has high
morbidity/mortality risks. Over the last 10 years, we have developed and validated endobronchial optical
coherence tomography (EB-OCT) as a safe, minimally-invasive imaging modality to assess lung disease, with
microscopic resolution 200x higher than CT in tissue volumes 100x larger than SLB. We have established that
the subpleural space of both lungs can be practically and rapidly (10 sites in <10 min) evaluated in early PPF
using EB-OCT, with 100% sensitivity/specificity for early lung fibrosis as compared to SLB, without adverse
events. We have additionally developed and validated artificial intelligence methods for automated segmentation
and volumetric quantification of microscopic features on EB-OCT with sensitivity/specificity >0.9, allowing for
broad implementation of this technology to define an individual patient’s risk for ILA progression to PPF. With
these major developments in EB-OCT, we finally can safely investigate microscopic disease features in ILA that
may predict progression to PPF. In a preliminary cohort of ILA subjects, we identified high-risk features of early
architectural distortion by EB-OCT that predicted progression of ILA to PPF. Our compelling premise and
preliminary data support our central hypothesis that individuals with ILA who will progress to PPF have high-risk
microscopic features, defined as destructive fibrosis with microscopic honeycombing or traction bronchiolectasis,
that are detectable by EB-OCT. We are uniquely positioned to test this hypothesis due to our expertise in EB-
OCT and access to two large ILA cohorts with annual follow-up (with CT and PFT) to assess long-term outcomes
through our lung nodule CT screening program (smokers with ILA; Cohort 1) and existing ILA cohort (subjects
with ILA and family history of PPF; Cohort 2). In Aim 1, we will determine the accuracy of microscopic features,
as detected by EB-OCT, to predict progression to PPF in two independent ILA cohorts. In Aim 2, we will define
and validate an integrative prediction model for progression of ILA to PPF that combines EB-OCT, ...

## Key facts

- **NIH application ID:** 10893772
- **Project number:** 1R01HL169225-01A1
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Lida P Hariri
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $837,883
- **Award type:** 1
- **Project period:** 2024-06-01 → 2029-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10893772

## Citation

> US National Institutes of Health, RePORTER application 10893772, Microscopic EB-OCT imaging to predict progression in interstitial lung abnormalities (1R01HL169225-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10893772. Licensed CC0.

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