342 analysis of thalamic structure and function is a continually researched theme in neuroimaging investigations, particu- larly using magnetic resonance imaging (MRI). Analysis of volume or shape using MRI techniques may provide impor- tant information with respect to the involvement of the thalamus in neurological and neuropsychiatric disorders, including generalized (Du, et al. 2011; Pulsipher, et al. 2009) and partial (Gong, et al. 2008; Pulsipher, et al. 2007) epilepsy, schizophrenia (Adriano, et al. 2010), Huntington’s disease (Douaud, et al. 2006; Kassubek, et al. 2005), Parkinson’s disease (McKeown, et al. 2008), and Alzheimer’s disease (de Jong, et al. 2008). Reliable mea- surement of thalamic structure is, however, notoriously dif- ficult to achieve, particularly given the typically poor between-tissue MR contrast of the thalamic nuclei and adjacent white matter (Amini, et al. 2004). It is there- fore important to develop new and improve and validate existing methodologies that provide thalamic metrics. Like for other subcortical brain structures, there are several approaches freely available to estimate thalamic volume from MR images. At either end of the MR image analysis spectrum, there are manual and automat- ed approaches; manual approaches are user-dependent, time consuming but are considered to be the gold stan- dard of MR image analysis techniques (Bonilha, et al. 2004; Collins and Pruessner 2010; Crum, et al. 2001; Pruessner, et al. 2000). Automated approaches remove the need of an expert anatomist, are dependent on computer algorithms, and are time efficient, but require a great deal of validation against manual methods to determine the specificity and validity of measurements (Chupin, et al. 2009; Morra, et al. 2008). The primary goal of the present study was to evaluate the validity of thalamic volume measurements obtained from a frequently used automated approach with respect to a reputable manual approach widely used in the imaging, anatomical and histological sciences. The fully automated approach investigated in the present study was the subcortical segmentation and volume estima- tion techniques (Fischl, et al. 2002) incorporated into FreeSurfer software (http://surfer.nmr.mgh.harvard.edu/), which provide observer-independent volumes for individual subcortical nuclei from conventional MR images. Similarly to other methods that automatically segment and estimate subcortical volume such as FIRST (Patenaude, et al. 2011) incorporated into FSL software (http://www.fmrib.ox.ac.uk/ fsl/first/index.html), there has been a recent proliferation of studies using FreeSurfer methods for volumetric studies, some of which have included comparison with manual methods, most notably for the hippocampus (Cherbuin, et al. 2009; Dewey, et al. 2010; Morey, et al. 2009; Pardoe, et al. 2009; Shen, et al. 2010; Tae, et al. 2008). To our knowl- edge, there has been no independent comparison between Neuroinform (2012) 10:341–350 manual methods and FreeSurfer methods for volume esti- mation of the thalamus. The manual approach used to eval- uated FreeSurfer-based thalamic volumes in the present study was the Cavalieri method of design-based stereology in conjunction with point counting (Gundersen and Jensen 1987; Gundersen, et al. 1999; Mayhew 1992; Roberts, et al. 2000), which is a 100 % investigator interactive technique that requires manual determination of sampling density for a given brain structure (i.e. the stereological parameters nec- essary to produce a reliable volume estimate) and investiga- tor decisions on whether or not sampling probes (i.e. points) intersect the brain region-of-interest (ROI). Stereology requires the use of a human anatomist with expert knowl- edge of anatomical boundaries that divide legitimate (i.e. thalamic) and illegitimate (i.e. non-thalamic) brain tissue. Manual approaches such as stereology are considered gold standard because it is assumed that human knowledge and perception is superior to computer algorithms that determine regional brain boundaries. We examined the consistency between manual and auto- mated thalamic volume estimation in two ways. Firstly, we compared thalamic volume estimates in a sample of neuro- logically and psychiatrically healthy subjects. Secondly, we compared the methods in their sensitivity in detecting tha- lamic atrophy in patients with juvenile myoclonic epilepsy (JME). JME is an electro-clinical syndrome that by defini- tion is non-lesional and without abnormality on convention- al magnetic resonance imaging (MRI) (Berg, et al. 2010; ILAE 1989), but has previously been shown to be associated with thalamic structural alterations (Deppe, et al. 2008; Kim, et al. 2007; Mory, et al. 2011; Pulsipher, et al. 2009), and is generally considered to be intimately associated with tha- lamic dysfunction (Holmes, et al. 2010). We therefore com- pared morphometric approaches for volume estimation of both healthy and diseased thalami. Methods Participants We studied a neurologically and psychiatrically healthy control group that was composed of 62 adult volunteers (32 females, mean age 27.9 ±4.3 SD, range 21–43), all of whom had normal neurological examination and normal MRI (T1-, T2-weighted, and FLAIR). We also studied ten patients (6 females, mean age 28.6±8.8 SD, range 19–42) with JME. Clinical information for these patients can be found elsewhere (Deppe, et al. 2008; Keller, et al. 2011a). There was no statistical difference in age between patients and controls (t0 0.38, p 0 0.70). All subjects gave written informed consent and the local ethics committee approved this study.