T follicular helper (TFH) cells are critical for B cell activation in germinal centers and are often observed in human inflamed tissue. However, it is difficult to know if they contribute in situ to inflammation. Expressed markers define TFH subsets associated with distinct functions in vitro. However, such markers may not reflect in situ function. The delivery of T cell help to B cells requires direct cognate recognition. We hypothesized that by visualizing and quantifying such interactions, we could directly assess TFH cell competency in situ. Therefore, we developed computational tools to quantify spatial relationships between different cell subtypes in tissue [cell distance mapping (CDM)]. Analysis of inflamed human tissues indicated that measurement of internuclear distances between TFH and B cells could be used to discriminate between apparent cognate and noncognate interactions. Furthermore, only cognate-competent TFH cell populations expressed high levels of Bcl-6 and interleukin-21. These data suggest that CDM can be used to identify adaptive immune cell networks driving in situ inflammation. Such knowledge should help identify diseases, and disease subsets, that may benefit from therapeutic targeting of specific T cell-antigen-presenting cell interactions.