# Early Detection of Residual/Recurrent Lung Malignancies on Post-Radiation FDG PET/CT
## 2 Materials and Methods  
### Data Collection and Pre-Processing  
We selected PET/CTs from 95 patients (one PET/CT from each patient), retrospectively, who received radiation therapy from 1 October 2006 to 6 August 2019. The following criteria were used to select these PET/CTs:  
* Patients should have had an FDG PET/CT scan within two years after receiving radiation therapy to the lungs;
* Only the PET/CTs with abnormally increased radiotracer (FDG) uptake in the lungs were used;
* Abnormal radiotracer uptake should have been identified as benign post-radiation changes or malignant disease, by tissue sampling or follow-up imaging (CT or PET/CT) for at least 2 years;
* On follow-up imaging, stable or regressing lung parenchymal abnormalities at the site of radiation were considered benign. Progressively expanding lesions were considered malignant. Out of 95 patients, 26 patients had biopsies performed for indeterminant imaging findings after receiving radiation therapy. Out of these patients, 17 patients demonstrated positive findings for malignancy on biopsy, while 9 patients had benign findings (negative for malignancy). Follow-up CT and PET/CT images from the rest of the patients (69 patients) were evaluated for up to two years after the first post-radiation PET/CT. On follow-up imaging, 28 patients demonstrated progressive abnormalities indicating positive lung malignancy at the post-radiation site. Forty-one patients demonstrated regression of imaging abnormalities on two-year follow-up images, indicating non-malignant benign post-radiation changes on first post-radiation PET/CT. Table 1 summarizes the patient demographics and tumor characteristics, with data categorized into benign and malignant groups. The study cohort consisted of 95 patients, including 43 males and 52 females. The median age was 72 years, ranging from 46 to 94 years. Primary tumors were most frequently located in the upper lobe of the lung (58 cases), followed by the lower lobe (34 cases), and the middle lobe (3 cases). Laterality of disease was fairly balanced, with 52 cases on the right lung and 43 on the left. In terms of clinical staging, 49 patients were classified as early-stage (stages 0-1), 30 as intermediate-stage (stages 2-3), and 6 as advanced-stage (stage 4 or higher), while 10 cases remained unclassified. The breakdown between benign and malignant lesions revealed similar distributions across gender, age, and tumor location, with 50 benign cases and 45 malignant cases. This balance indicates the need for better diagnostic tools in distinguishing benign post-treatment changes from residual or recurrent malignancies. In this study, all PET/CT images were acquired using the same Siemens PET/CT scanner, following a standardized imaging protocol. PET images were reconstructed using either the OSEM2D 4i8s or PSF3i21s algorithms, with pixel spacing of 4.0728 mm and slice thickness of 5 mm. The administered radiopharmaceutical dose ranged from 298 MBq to 4030 MBq, with a median dose of 417 MBq. During pre-processing, all CT images were resampled to match the resolution of the PET images. Additionally, PET intensity values were converted to standardized uptake values (SUVs) to ensure consistency for model development and subsequent inference. A nuclear medicine physician manually delineated the region of interest (ROI) on the slice with the largest lesion area. This 2D contour was then extended to 3D using a similarity variation model, as described in a previous study [14]. Based on these 3D tumor representations, we developed radiomics, CNN, and fusion models. Figure 2 outlines the workflow, from data acquisition to the final prediction of whether post-radiation changes are benign or represent residual/recurrent malignancies based on the follow-up PET/CT images. To facilitate the evaluation of the proposed radiomics, CNN, and fusion models, we divided the dataset into five folders, each containing data from 20, 20, 18, 20, and 17 patients, respectively. This division allowed us to perform a five-folder cross-validation.