Low-dose photon-counting CT measured myositis lung disease almost as standard dose

Design

Single-centre prospective feasibility study, paired scans

Population

48 adults with inflammatory myopathy–associated interstitial lung disease

Primary outcome

Agreement of quantified ILD patterns, low vs standard dose

Effect

CTDIvol 0.77 vs 5.40 mGy; mean differences <1% for all patterns

In this single-centre prospective feasibility study, 48 outpatients with inflammatory myopathy and interstitial lung disease had a standard-dose and a tin-filtered low-dose photon-counting CT in one sitting. Deep-learning software quantified ground-glass, reticulation, fibrosis and bronchiectasis.

The low-dose protocol used about one-seventh of the dose (CTDIvol 0.77 vs 5.40 mGy). Quantified patterns differed by less than 1% on average between protocols, with slightly more ground glass and slightly less fibrosis on low dose. Reticulation correlated with FVC and DLCO equally well on both. Ultrathin 0.4 mm reconstructions added little.

For patients who need repeated CT to monitor lung involvement, this is a promising way to cut cumulative dose. It is feasibility data in 48 people on one scanner type, it did not test longitudinal change, and photon-counting CT is not widely available in India.

• Consider low-dose protocols for follow-up CT in myositis-associated lung disease where scanner capability allows.
• Expect slightly more ground glass and slightly less fibrosis to be quantified on low dose.
• Use the same protocol at each follow-up so that change is not an artefact of dose.
• Do not rely on ultrathin reconstructions for added value in this setting.

Why it matters

Patients scanned repeatedly over years carry the most cumulative dose, and this targets them.

Don't overread it

This is a 48-patient feasibility study on one scanner type; it did not test monitoring change over time.

The statistics, in plain English

Mean differences under 1% mean the two protocols gave nearly the same answer on average. Bland–Altman agreement on average can still hide larger differences in individual patients, which matters for follow-up.

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