Automatic Quantification of Interstitial Lung Disease From Chest Computed Tomography in Systemic Sclerosis

Systemic sclerosis interstitial lung disease: unmet needs and potential solutions

Systemic sclerosis (SSc), or scleroderma, is a rare, complex, systemic autoimmune disease of unknown aetiology, characterized by high morbidity and mortality often resulting from cardiopulmonary complications such as interstitial lung disease and pulmonary arterial hypertension. Despite substantial progress in unravelling the pathways involved in the pathogenesis of SSc and the increasing number of therapeutic targets tested in clinical trials, there is still no cure for this disease, although several proposed treatments might limit the involvement of specific organs, thereby slowing the natural history of the disease. A specific focus of recent research has been to address the plethora of unmet needs regarding the global management of SSc-related interstitial lung disease, including its pathogenesis, early diagnosis, risk stratification of patients, appropriate treatment regimens and monitoring of treatment response, as well as the definition of progression and predictors of progression and mortality. More refined stratification of patients on the basis of clinical features, molecular signatures, identification of subpopulations with distinct clinical trajectories and implementation of outcome measures for future clinical trials could also improve therapeutic management strategies, helping to avoid poor outcomes related to lung involvement.

Quantification of diffuse parenchymal lung disease in non-small cell lung cancer patients with definitive concurrent chemoradiation therapy for predicting radiation pneumonitis

BACKGROUND

We sought to quantify diffuse parenchymal lung disease (DPLD) extent using quantitative computed tomography (CT) analysis and to investigate its association with radiation pneumonitis (RP) development in non-small cell lung cancer (NSCLC) patients receiving definitive concurrent chemoradiation therapy (CCRT).

METHODS

A total of 82 NSCLC patients undergoing definitive CCRT were included in this prospective cohort study. Pretreatment CT scans were analyzed using quantitative CT analysis software. Low-attenuation area (LAA) features based on lung density and texture features reflecting interstitial lung disease (ILD) were extracted from the whole lung. Clinical and dosimetric factors were also evaluated. RP development was assessed using the Common Terminology Criteria for Adverse Events version 5.0. Univariable and multivariable logistic regression analyses were performed to identify independent risk factors for grade ≥3 (≥GR3) RP.

RESULTS

RP was identified in 68 patients (73.9%), with nine patients (10.9%) experiencing ≥GR3 RP. Univariable logistic regression analysis identified excess kurtosis and high-attenuation area (HAA)_volume (cc) as significantly associated with ≥GR3 RP. Multivariable logistic regression analysis showed that the combined use of imaging features and clinical factors (forced expiratory volume in 1 second [FEV1], forced vital capacity [FVC], and CHEMO regimen) demonstrated the best performance (area under the receiver operating characteristic curve = 0.924) in predicting ≥GR3 RP.

CONCLUSION

Quantified imaging features of DPLD obtained from pretreatment CT scans would predict the occurrence of RP in NSCLC patients undergoing definitive CCRT. Combining imaging features with clinical factors could improve the accuracy of the predictive model for severe RP.

Dual-energy CT lung perfusion in systemic sclerosis: preliminary experience in 101 patients

OBJECTIVES

To investigate lung perfusion in systemic sclerosis (SSc).

METHODS

The study population included 101 patients who underwent dual-energy CT (DECT) in the follow-up of SSc with pulmonary function tests obtained within 2 months. Fifteen patients had right heart catheterization-proven PH.

RESULTS

Thirty-seven patients had no SSc-related lung involvement (Group A), 56 patients had SSc-related interstitial lung disease (Group B) of variable extent (Group B mild: ≤ 10% of lung parenchyma involved: n = 17; Group B moderate: between 11 and 50%: n = 31; Group B severe: > 50%: n = 8), and 8 patients had PVOD/PCH (Group C). Lung perfusion was abnormal in 8 patients in Group A (21.6%), 14 patients in Group B (25%), and 7 patients in Group C (87.5%). In Group A and Group B mild (n = 54), (a) patients with abnormal lung perfusion (n = 14; 26%) had a higher proportion of NYHA III/IV scores of dyspnea (7 [50%] vs 7 [17.5%]; p = 0.031) and a shorter mean walking distance at the 6MWT (397.0 [291.0; 466.0] vs 495.0 [381.0; 549.0]; p = 0.042) but no evidence of difference in the DLCO% predicted (61.0 [53.0; 67.0] vs 68.0 [61.0; 78.0]; p = 0.055) when compared to patients with normal lung perfusion (n = 40; 74%); (b) a negative correlation was found between the iodine concentration in both lungs and the DLCO% predicted but it did not reach statistical significance (r = -0.27; p = 0.059) and no correlation was found with the PAPs (r = 0.16; p = 0.29) and walking distance during the 6MWT (r = -0.029; p = 0.84).

CONCLUSIONS

DECT lung perfusion provides complementary information to standard HRCT scans, depicting perfusion changes in SSc patients with normal or minimally infiltrated lung parenchyma.

KEY POINTS

• In a retrospective observational study of 101 consecutive patients with SSc, dual-energy CT pulmonary angiography was obtained to evaluate lung perfusion. • Lung perfusion was abnormal in 14 out of 54 patients (26%) with no or mild SSc-related lung infiltration. • Patients with abnormal perfusion and no or mild SSc-related lung infiltration had more severe scores of dyspnea and shorter walking distance than patients with similar lung findings and normal perfusion, suggesting the presence of small vessel vasculopathy.