Patients with metastatic neuroendocrine tumors (NETs) can present with hundreds of lesions, and each lesion might have a unique response pattern to peptide receptor radiopharmaceutical therapy (PRRT). This response heterogeneity has been observed but is poorly understood. In this work, we perform a quantitative analysis of longitudinal PET/CT scans to comprehensively characterize the NET response to PRRT. Methods: NET patients treated with [177Lu]Lu-DOTATATE PRRT imaged at baseline, during, and after PRRT with [68Ga]Ga-DOTATATE PET/CT were enrolled in this retrospective single-institutional study. A deep-learning model was used to identify and contour regions of nonphysiological elevated tracer uptake (lesion-regions of interest [ROIs]). An automated analysis was performed to identify, contour, and quantify the individual lesion-ROI uptake, match ROI between time points, and categorize each lesion-ROI as disappearing, decreasing (ΔSUVtotal < −30%), stable (−30% ≤ ΔSUVtotal ≤ 30%), incr