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-----Original Message-----
From: Chris Gottschalk, MD [mailto:[log in to unmask]]
Sent: Monday, June 26, 2000 4:47 PM
To: Bing Fang
Cc: [log in to unmask]
Subject: Re: Average Image-- SPECT data

Dr Fang-- you raise several important questions regarding SPM analysis of SPECT data.

For spatial normalization, there is no definite answer regarding the use of a custom template. With the latest version of SPM [SPM99], the algorithm for spm_spatial has changed considerably, and is much more robust-- especially for noisy images, or ones whose power spectra are very different from the templates provided in SPM [both of which are generally true for SPECT data, and I will leave the consideration of what fan-beam collimation does alone for the moment]. This newer method can be "regularised"-- restricted so that it does not warp images in unlikely or bizarre ways-- which means you can try out levels of regularisation on your images to see how it performs.

Several simple considerations:
you mention Coregister, which is used for matching functional data [e.g., SPECT] with MRI data. If you have anatomic scans for your controls, then your task is much easier-- you register each SPECT scan to its corrsponding MRI, and then normalize the MRI volumes to the SPM-MRI template [presumably T1 images], applying that transformation to the coregistered SPECT data as well. This process takes advantage of the much higher resolution of MRI data. As an aside, I also note that your selection criterion of "no assymetry >7%"--presumably in a set of predefined regions?-- appears unusual to me. Unless you have other data indicating that the range of asymmetry in SPECT scans of the [actual] normal population is less than 7%, I would say this requirement may produce comparison data that does not necessarily reflect the normal range.

If you do  not have anatomic images, then you must wrestle with what is "best" for your reference dataset. One very helpful published study deals with both this issue and the statistical concerns you raise:

Validation of Statistical Parametric Mapping (SPM) in Assessing Cerebral
Lesions: A Simulation Study
E. A. Stamatakis,* M. F. Glabus,† , ‡ D. J. Wyper,§ A. Barnes,§ and J. T. L. Wilson*
NeuroImage 10, 397-407 (1999)
Article ID nimg.1999.0477, available online at http://www.idealibrary.com

in this paper, the authors note that using their own template of an average SPECT image made no appreciable difference in spatial normalizatio,compared with using the PET template. Note, however, that these were Strichman images, and the spatial normalization and statisitcal analyses were performed in SPM96. More importantly, this paper also addresses the question of sensitivity-- the ability of SPM [96] to detect a lesion of known size and degree in a single SPECT image compared to a set of "normative" scans.
[Note that for this type of single-subject analysis, you would use "single subject:replication of conditions" as your model, since in SPM terms this is equivalent to one scan from each of many subjects in only one condition. ]

the lead author of that paper recently presented other data regarding SPECT data at the HBM conference in San Antonio [search "Stamatakis" at http://www.academicpress.com/www/journal/hbm2000/auindex.htm,  or I can send you the abstract as it appears there] which demonstrated an important concept: the process of spatial normalization can significantly alter a markedly abnormal signal in a given scan. If you are interested in the updated results of this work, I suggest you contact Dr Stamatakis. If he does not reply to this message, I will put you in touch with him.

"How many subjects" is a difficult question in high-dimensional statistical comparisons, even with massive univariate tests. Ultimately, you are asking about power, of course, and you see there have been several questions on this topic of late on this list.  My other reply today on this topic lists some papers on this subject, and Matthew Brett's reply today also links to some help for estimating power in SPM96. A related paper which also touches on many of your concerns is:

Influence of ANOVA Design and Anatomical Standardization
on Statistical Mapping for PET Activation
Michio Senda,* Kenji Ishii,* Keiichi Oda,* Norihiro Sadato,† Ryuta Kawashima,‡ Motoaki Sugiura,‡
Iwao Kanno,§ Babak Ardekani,§ Satoshi Minoshima,¶ and Itaru Tatsumi\
NEUROIMAGE 8, 283-301 (1998)
ARTICLE NO. NI980370

I hope this is helpful to you, and I look forward to additional responses from the community at large--

At 03:46 PM 06/26/2000 , you wrote:
>I am a physicist and try to help NM physician to set up a protocal for
>analyzing pediatric ADHD patient using SPM. My knowledge on SPM is very
>basic. I would like to ask your spmers to comment on the setting I post
>below and help me answer some questions . We use SPECT (Fan Beam) data.
>1). Collect a control group of subject under two criterions a).No
>asymmetry >7% with manual 9 pixel analysis by a experienced NM
>physician; b).ADHD is not primary diagnosis with Axis I standard.
>2). Since these are pediatric patient (age from 5-18), Should I create a
>average image from the control group instend of using SPM's PET template
>in Coregister and Reslice? Does it matter which one to be used as
>modality and target image?
>3). If  such a average image is prefered in my study, should I average
>on raw .img images or on snr .img images. If I should use snr .img
>images to do the average, should I use SPM's PET template or random
>selecting one of patient in my control group as the modality and target
>image in Coregister and Reslice?
>4). How many patients do I need to create such an average image under
>statistical consideration? If the subjects in this control group will be
>used as Group 1 for the design type "Compare - group; 1 scan per
>subject" in Statictics, how many patients do I need to reach a
>statistical satisfaction?
>
>Thank you all in advance.
>
>Bing Fang, B.M.,M.S.
>

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Christopher Gottschalk, MD                      *

Assistant Professor of Neurology & Psychiatry   *

Yale School of Medicine                 *

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