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The investigators investigated the associations between the imaging parameters of ⁶⁸Ga-FAPI and ¹⁸F-FDG dual-tracer PET/CT and concomitant interstitial lung disease (ILD) in patients with dermatomyositis (DM), developed a novel diagnostic model to predict DM complicated with ILD, and conducted external validation of this model. Meanwhile, the investigators compared the predictive performance of the imaging-only model with that of the classic clinical model and the clinical-radiological collaborative model.
For the features included in the final optimal model, between-group comparisons of continuous variables (interstitial lung disease group vs. non-interstitial lung disease group) were performed using the Wilcoxon rank-sum test. For categorical variables, the Chi-square test or Fisher's exact test was adopted as appropriate.In the comparison of model efficacy, the DeLong test was used to assess the statistical differences in AUC values between each machine learning classifier and the reference model.All statistical analyses were conducted using R software (version 4.4.1). The corresponding R packages applied included pROC for ROC analysis, caret for model training, and SHAP for the interpretability analysis of the XGBoost model. A two-tailed p-value < 0.05 was defined as the threshold of statistical significance for all analyses.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| ILD | The diagnosis of ILD was confirmed in line with the criteria of the American Thoracic Society (ATS). |
| |
| non-ILD | Patients in the non-ILD group had no evidence of ILD as judged by ATS criteria. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Observe the medical images | Other | Observe the medical images via work station or local image analysing software |
|
| Measure | Description | Time Frame |
|---|---|---|
| Imaging features of 68Ga-FAPI PET image | conventional PET parameters (SUVmax, SUVmin) and PET textural feature parameters (radiomics) | baseline |
| Measure | Description | Time Frame |
|---|---|---|
| Performance of Machine Learning and Reference Models | ROC curve (Receiver Operating Characteristic curve)、DCA curve (Decision Curve Analysis curve) | baseline |
| Measure | Description | Time Frame |
|---|---|---|
| SHAP Analysis of the Optimal Model | baseline | |
| Between-group Differences | DM-ILD and DM non-ILD Group comparison of important parameters in models | baseline |
Inclusion Criteria:
Exclusion Criteria: Patients with other connective tissue diseases.
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Between June 2023 and July 2025, 154 consecutive patients diagnosed with dermatomyositis (DM) who underwent 68Ga-FAPI-04 PET/CT imaging were initially considered. The diagnosis of DM was established based on Bohan and Peter criteria for classic DM [24], or Sontheimer criteria for clinically amyopathic dermatomyositis (CADM)[25]. The diagnosis of interstitial lung disease (ILD) was confirmed by a multidisciplinary team based on a combination of clinical symptoms (cough, dyspnea), physical findings (inspiratory crackles), high-resolution computed tomography (HRCT) evidence of interstitial changes, and pulmonary function tests showing restrictive ventilator defects.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Department of Nuclear Medicine & Institute for medical imaging technology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, | Shanghai | Shanghai Municipality | China |
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| Extracting image feature | Other | Extracting image feature via radiomics or machine learning methods |
|
| Correlation analysis | Correlation analysis of the various parameters in the model. | baseline |
| ID | Term |
|---|---|
| D003882 | Dermatomyositis |
| ID | Term |
|---|---|
| D017285 | Polymyositis |
| D009220 | Myositis |
| D009135 | Muscular Diseases |
| D009140 | Musculoskeletal Diseases |
| D009468 | Neuromuscular Diseases |
| D009422 | Nervous System Diseases |
| D003240 | Connective Tissue Diseases |
| D017437 | Skin and Connective Tissue Diseases |
| D012871 | Skin Diseases |
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