Incorporating volumetric illumination into rendering of volumetric data increases visual realism, which can lead to improved spatial comprehension. It is known that spatial comprehension can be further improved by incorporating multiple light sources. However, many volumetric illumination algorithms have severe drawbacks when dealing with multiple light sources. These drawbacks are mainly high performance penalties and memory usage, which can be tackled with specialized data structures or data under sampling. In contrast, in this paper we present a method which enables volumetric illumination with multiple light sources without requiring precomputation or impacting visual quality. To achieve this goal, we introduce selective light updates which minimize the required computations when light settings are changed. We will discuss and analyze the novel concepts underlying selective light updates, and demonstrate them when applied to real-world data under different light settings.