Accurate prediction of brain dysfunction caused by disease or injury requires the quantification of resultant neural connectivity changes compared with the normal state. There are many methods with which to assess anatomical changes in structural or diffusion magnetic resonance imaging, but most overlook the topology of white matter (WM) connections that make up the healthy brain network. Here, a new neuroimaging software pipeline called the Network Modification (NeMo) Tool is presented that associates alterations in WM integrity with expected changes in neural connectivity between gray matter regions. The NeMo Tool uses a large reference set of healthy tractograms to assess implied network changes arising from a particular pattern of WM alteration on a region- and network-wise level. In this way, WM integrity changes can be extrapolated to the cortices and deep brain nuclei, enabling assessment of functional and cognitive alterations. Unlike current techniques that assess network dysfunction, the NeMo tool does not require tractography in pathological brains for which the algorithms may be unreliable or diffusion data are unavailable. The versatility of the NeMo Tool is demonstrated by applying it to data from patients with Alzheimer's disease, fronto-temporal dementia, normal pressure hydrocephalus, and mild traumatic brain injury. This tool fills a gap in the quantitative neuroimaging field by enabling an investigation of morphological and functional implications of changes in structural WM integrity.
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