Computerized Imaging Tool Helps ID New IPF Subtype

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by Forest Ray PhD |

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new IPF subtype/ imaging scan helps ID

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Idiopathic pulmonary fibrosis (IPF) co-occurring with a second lung disorder represents a distinct new IPF subtype with a poor prognosis and its own set of treatment considerations, a recent study found.

The discovery of this new IPF subtype, made with the help of a computerized image analysis tool, could aid in the efforts to design better therapies that are adapted to the specific needs of each patient, according to researchers.

“Using this computerised tool we have identified the first [subtype] in IPF occurring in about 30% of IPF patients,” Joseph Jacob, MD, the study’s senior author, said in a University College London (UCL) press release.

Jacob said a key aim will be to develop “personalised patient management” for those diagnosed with new subtypes.

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The study, “Pleuroparenchymal fibroelastosis in idiopathic pulmonary fibrosis: Survival analysis using visual and computer-based computed tomography assessment,” was published in the journal EClinical Medicine.

IPF belongs to a family of interstitial lung diseases (ILDs), which are broadly characterized by scarring, or fibrosis, of lung tissue. Pleuroparenchymal fibroelastosis, known as PPFE, is another ILD that some studies have found to be associated with IPF.

People with both conditions represent a distinct subset of patients, whose treatment may differ from other subsets.

“Doctors have suspected for some time that there are distinct subgroups … of IPF that have unique functional or pathobiological disease mechanisms, which make the condition even more deadly,” said Jacob, a principle research fellow with the UCL division of medicine, whose research has focused on using computerized tools to quantify lung damages.

“Identifying IPF [subtypes] could allow a degree of personalized patient management,” he said.

Until now, however, there had been no specific attempts to describe the significance of this association, or how having both conditions affects an individual’s prognosis.

That void led Eyjolfur Gudmundsson, PhD, a colleague of Jacob’s at UCL, to design an automated computer image analysis algorithm for use with computed tomography (CT) imaging scans.

The two scientists, along with other colleagues, used that algorithm to identify PPFE scarring patterns in lung CT images from IPF patients.

Each scan was assessed both visually by a radiologist and by the algorithm. While both methods proved able to distinguish patients at risk of poor outcomes, computer-assisted assessments performed better at identifying patients experiencing faster lung function decline, as measured by one-year changes in forced vital capacity (FVC) and survival. Of note, FVC is a lung function parameter that measures the total amount of air a patient is able to exhale after a deep breath.

Computer-based assessments also identified more patients with worst outcomes, as compared with visual scores. Based on the algorithm’s results, the team determined that 87 of 287 IPF patients (30%) had clinically relevant PPFE and that this was associated with worse outcomes. Conversely, extensive PPFE was only identified in 31 IPF patients (11%) when CT scans were examined by a radiologist.

“Our computerised scoring system was developed to quantify disease extent with greater precision than visual scores and fulfilled its ambition of detecting more patients with severe disease,” the researchers wrote.

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IPF patients with signs of PPFE tended to experience worse outcomes, regardless of ILD severity, suggesting that PPFE may represent a distinct disease process, albeit one that still results in progressive clinical decline.

“The PPFE identified adversely affects survival and appears to occur and progress separate to the fibrosis in the patients’ lungs,” Jacob said.

Investigators also noted that antifibrotic medications improved survival in IPF patients with PPFE.

According to researchers, these findings could prove helpful when selecting patients for clinical trials, such as those measuring changes in FVC.

“Our computer algorithm identifies patients with the PPFE [subtype] of IPF which may inform patient selection in IPF drug trials and clinical management of disease,” Jacob said. “Our algorithm should be able to measure PPFE worsening over time in patients with IPF.”

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