Atherosclerosis is a widespread disease affecting coronary arteries. Diffuse atherosclerotic disease affects the whole vessel, posing difficulties in determining lesion significance by angiography. Research has confirmed that revascularization guided by invasive coronary physiology indices improves patients' prognosis and quality of life. Serial lesions can be a diagnostic challenge because the measurement of functional stenosis significance using invasive physiology is influenced by a complex interplay of factors. The use of fractional flow reserve (FFR) pullback provides a trans-stenotic pressure gradient (ΔP) for each of the lesions. The strategy of treating the lesion with greaterΔP first and then reevaluating another lesion has been advocated. Similarly, non-hyperemic indices can be used to assess the contribution of each stenosis and predict the effect of lesion treatment on physiology indices. Pullback pressure gradient (PPG) integrates physiological variables of coronary pressure along the epicardial vessel and characteristics of discrete and diffuse coronary stenoses into a quantitative index that can be used to guide revascularization. We proposed an algorithm that integrates FFR pullbacks and calculates PPG to determine individual lesion importance and to guide intervention. Computer modeling of the coronaries and the use of non-invasive FFR measurement together with mathematical algorithms for fluid dynamics can make predictions of lesion significance in serial stenoses easier and provide practical solutions for treatment. All these strategies need to be validated before widespread clinical use.