-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathindex.html
446 lines (343 loc) · 13.6 KB
/
index.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
<!doctype html>
<html lang="en">
<head>
<title> Project Nuisance </title>
<meta name="description" content="Use of MRI QC metrics, scanning
parameters and seasonal variation data to control for variance in MRI studies ">
<meta name="author" content=" Yaroslav O. Halchenko ">
<meta charset="utf-8">
<meta name="apple-mobile-web-app-capable" content="yes" />
<meta name="apple-mobile-web-app-status-bar-style" content="black-translucent" />
<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no, minimal-ui">
<link rel="stylesheet" href="css/main.css" id="theme">
<script src="js/printpdf.js"></script>
</head>
<body>
<div class="reveal">
<div class="slides">
<section>
<section>
<a href="http://centerforopenneuroscience.org/"><img data-src="pics/con-ccn-dartmouth-letterhead.svg"></a>
<h3>Use of MRI QC metrics, scanning parameters and seasonal variation data to control for variance in MRI studies</h3>
<!--
<table style="border:none">
<tr>
<td>
<img style="height:150px;margin-bottom:30px" data-src="pics/datalad_logo_wide.svg">
</td>
<td>
<h3>Use of MRI QC metrics, scanning parameters
and seasonal variation data to control for variance in MRI studies</h3>
</td>
</tr>
</table> -->
<div style="margin-top:0em;text-align:center">
<table style="border: none;">
<tr>
<td>Yaroslav O. Halchenko
<br><small>
<a href="https://twitter.com/yarikoptic" target="_blank">
<img data-src="pics/twitter.png" style="height:30px;margin:0px" />
@yarikoptic</a></small></td>
<td>Christopher P. Cheng
<br><small>
<a href="https://twitter.com/chrispcheng="_blank">
<img data-src="pics/twitter.png" style="height:30px;margin:0px" />
@chrispcheng</a></small></td>
</tr>
<tr>
<td>
<small><a href="http://centerforopenneuroscience.org/" target="_blank">Center for Open Neuroscience</a>
<br><a href="https://pbs.dartmouth.edu/" target="_blank">Department of Psychological and Brain Sciences</a>
<br><a href="https://www.dartmouth.edu/ccn/" target="_blank">Center for Cognitive Neuroscience</a><br>
<a href="http://www.dartmouth.edu" target="_blank">Dartmouth College</a></small>
<!--<img style="height:150px;" data-src="pics/con-logo_blue_big.svg">-->
</td>
</tr>
</table>
</div>
<br>
<small>
<a href="http://repronim.org" target="_blank"> <img style="height:150px;margin:20px" data-src="pics/repronim-logo-vertical.svg"/></a>
<a href="http://datalad.org" target="_blank"> <img style="height:150px;margin:20px" data-src="pics/datalad_D.svg"/></a>
<a href="http://neuro.debian.net" target="_blank"> <img style="height:150px;margin:20px" data-src="pics/neurodebian.png"/></a>
<a href="https://bids.neuroimaging.io" target="_blank"> <img style="height:150px;margin:20px" data-src="pics/BIDS_Logo.png"/></a>
<a href="https://github.com/myyoda/poster/blob/master/ohbm2018.pdf" target="_blank"> <img style="height:150px;margin:20px" data-src="pics/yoda.svg"/></a>
</small>
</section>
<section>
<h2>Acknowledgements</h2>
<table>
<tr style="vertical-align:middle">
<td style="vertical-align:middle">
<dl>
<dt style="margin-top:20px">QA data & DBIC support</dt>
<dd style="margin-left:5px!important">
<ul style="margin-left:5px!important">
<li>Chandana Kodiweera</li>
<li>Terry Sackett</li>
</ul>
</dd>
<dt style="margin-top:20px">MRI data</dt>
<dd style="margin-left:5px!important">
<ul style="margin-left:5px!important">
<li>Ida Gobbini</li>
<li>James Haxby</li>
<li>Luke Chang</li>
<li>Eshin Jolly</li>
</ul>
</dd>
</dl>
</td>
<td style="vertical-align:middle">
<div style="margin-left:40px;margin-bottom:-20px;text-align:center"><strong>Funders</strong></div>
<div style="margin-left:40px;text-align: left">
<br>
<img style="height:150px;margin-right:50px" data-src="pics/nsf1.jpg" />
<ul style="margin-left:5px!important">
<li>1429999</li>
<li>1912266</li>
<li>1835200<br></li>
</ul>
<br><br><img style="height:150px;margin-right:50px" data-src="pics/nih.png" />
<ul style="margin-left:5px!important">
<li>P41EB019936</li>
<li>R01MH116026</li>
<li>R56MH080716</li>
<li>R01MH116026</li>
</ul>
</div>
</td>
</tr>
</div>
<!--
<div style="margin-top:40px;margin-bottom:20px;text-align:center"><strong>Collaborators</strong></div>
<div style="margin-top:-20px">
<img style="height:100px;margin:20px" data-src="pics/hbp_logo.png" />
<img style="height:100px;margin:20px" data-src="pics/conp_logo.png" />
<img style="height:100px;margin:20px" data-src="pics/vbc_logo.png" />
</div>
<div style="margin-top:-40px">
<img style="height:120px;margin:20px" data-src="pics/openneuro_logo.png" />
<img style="height:120px;margin:20px" data-src="pics/cbrain_logo.png" />
<img style="height:140px;margin:20px" data-src="pics/brainlife_logo.png" />
</div>
-->
</td>
</tr>
</table>
</section>
</section>
<section>
<section data-markdown data-separator="^\n----\n" data-vertical="^\n---\n"><textarea data-template>
## Why scan Phantoms?
They
- are "cheap"
- don't mind
- have known stable characteristics
----
## Say Hi to Emmet
- they can be fun to build
<!-- .element: style="height: 400pt" -->
http://datasets.datalad.org/?dir=/dbic/QA/sub-emmet
<!-- .element: style="font-size: 12pt" -->
----
## But how stable are those?
<!-- .element: style="height: 500pt" -->
https://www.dartmouth.edu/dbic/research_infrastructure/qualityassurance.html
<!-- .element: style="font-size: 16pt" -->
----
## What that data can tell us?
### QA
#### If scanner operational characteristics changed:
- identify the reason
- address the issue and return back to "normal"
- the new "normal" might be different
----
## What that data can tell us?
### QA
#### If scanner operational characteristics did not change:
- all is good, bury the data
- phantom data is not considered useful beyond QA
----
## But we saw that it does change!
- *Q1: Why/What?*
- factors effecting phantom data effect human participants data too
- *What factors effect QA metrics?*
- *How well could we explain variance in QA metrics?*
- *Q2: How to account for "scanner mood" in human data?*
- some factors could not be easily accounted for directly in human data
- *Can we use phantom QA metrics as a "proxy" of current "effects"?*
</textarea>
</section>
</section>
<section>
<h2>Study: Nuisance</h2>
<img data-src="pics/f1000-webshot-20200930.png"/>
<small>
Cheng CP and Halchenko YO. A new virtue of phantom MRI data: explaining variance in human participant data [version 1; peer review: awaiting peer review]. F1000Research 2020, 9:1131 (<a href=https://doi.org/10.12688/f1000research.24544.1>https://doi.org/10.12688/f1000research.24544.1</a>)
</small>
</section>
<section>
<section data-markdown data-separator="^\n----\n" data-vertical="^\n---\n"><textarea data-template>
## What (Data sources)
- 3.0 Tesla Siemens Prisma
- duration: 10/30/2017--08/28/2018
- 32-channel head coil
- Agar phantom (Ethics: did not mind)
- QA is typically done (almost) each Monday
- 206 participants (Ethics: consented to data re-sharing)
- see https://open-brain-consent.readthedocs.io
- data comes from studies of 3 PIs at DBIC
- 18-64 years of age
- 78 male/128 female
----
## With what (Software etc)
- DICOM-to-BIDS: [HeuDiConv](https://github.com/nipy/heudiconv/) with [ReproIn](https://github.com/repronim/reproin/) heuristic
- Base OS: [Debian GNU/Linux](http://debian.org) + [NeuroDebian](http://neuro.debian.net)
- QA: [MRIQC](https://github.com/poldracklab/mriqc) (BIDS-App)
- Morphometrics: ["Simple Workflow"](https://github.com/ReproNim/simple_workflow)
- [FSL](https://fsl.fmrib.ox.ac.uk/fsl/fslwiki): BET, FAST, FIRST
- code/data/details: [10.12688/f1000research.10783.2](http://dx.doi.org/10.12688/f1000research.10783.2)
- Data wrangling and analyses:
- [Python](http://python.org/), [pandas](https://pandas.pydata.org/), [statsmodels](https://www.statsmodels.org/stable/index.html), [Jupyter notebooks](https://jupyter.org/)
- Containerization: [Singularity](https://singularity.lbl.gov)
- Version control/distribution:
- [DataLad](http://datalad.org), [datalad-container](http://handbook.datalad.org/en/latest/basics/101-133-containersrun.html?), [///ReproNim/containers](https://github.com/ReproNim/containers)
- Organization: follows [YODA principles](https://github.com/myyoda/poster/blob/master/ohbm2018.pdf)
- https://github.com/proj-nuisance/nuisance
</textarea></section></section>
<section>
<section data-markdown data-separator="^\n----\n" data-vertical="^\n---\n"><textarea data-template>
## Phantom
### Q1: Why/What?
- *What factors effect QA metrics?*
- *How well could we explain variance in QA metrics?*
----
## Phantom: Variables
----
## Phantom: Let's model snr_total
- Add a simplistic seasonal model
- we had only 1 year of data!
- cos and sin (period: year)
- Simple OLS model
- variables sequentially orthogonalized in the order presented
- t-test for individual variables (SAR, Date, etc)
- F-test for Position (IOPDs) and Seasonal
----
## Phantom
### Model: Total SNR
----
## Phantom
### Model: Total SNR (variables)
----
## Human(s)
- *Q2: How to account for "scanner mood" in human data?*
- *Can we use phantom QA metrics as a "proxy" of current "effects"?*
----
## Human(s): Let's model total Gray volume
- Basic demographics (age, sex, weight)
- Take Phantom Total SNR, interpolate for human participant scanning dates
- no other scanner specific factor (e.g., TxRefAmp)
- Add subject position in the scanner
- Add a simplistic seasonal model
- Simple OLS model
- variables sequentially orthogonalized
- t-test for individual variables
- F-test for Position (IOPDs) and Seasonal
----
### Model: Gray brain matter
----
### Model: Gray brain matter (variables)
----
## Human(s)
### Model: CSF, Gray, White + 14 sub-cortical structures
Q3: *What if we check other structures from simple_workflow?*
- Check Total SNR and Seasonal variables only
- no fishing expedition (yet)
- Result: Nothing passes test after FDR correction
- only Total SNR for Gray brain matter volume
----
## Conclusions
- *Somewhat surprising*:
- Variance in SNR through time can **very well** be explained by intrinsic factors
- *Confirming others*:
- Seasonal variations (but not in 1 year of Phantom)
- *Our hypothesis confirmed*:
- **A proxy measure of scanner health from phantom data can explain variance in human data results**
- **Include your QA data in your normative databases!**
----
## Future Directions
- Fish a little more (other metrics)
- Validate on new data from DBIC
- Investigate explanatory power of scanning characteristics (TxRefAmp, etc)
- Inspect magnitude of an effect on statistics
- Apply to fMRI data (resting state connectivity)
- Apply to larger (other) datasets (e.g. ABCD, HCP)
</textarea></section></section>
<section>
<h2>Further Information</h2>
<ul>
<li>Data/code:
<ul>
<li><a href="https://github.com/proj-nuisance">github.com/proj-nuisance</a> </li>
<li><a href="http://datasets.datalad.org/?dir=/con/nuisance">datasets.datalad.org/?dir=/con/nuisance</a></li>
</ul>
<li>DataLad: <a href="https://datalad.org">datalad.org</a></li>
<li>ReproNim: <a href="https://repronim.org">repronim.org</a></li>
<li>
Slides: <ul><li>"Sources": <a href="https://github.com/proj-nuisance/talk-2020-NNL" target="_blank">
https://github.com/proj-nuisance/talk-2020-NNL</a></li>
<li>View <a href="http://datasets.datalad.org/con/nuisance/presentations/2020-NNL/#/">here</a></li>
</ul>
</ul>
</section>
<section>
<h1>Thanks!</h1>
</section>
</section>
</div> <!-- /.slides -->
</div> <!-- /.reveal -->
<script src="reveal.js/js/reveal.js"></script>
<script>
// Full list of configuration options available at:
// https://github.com/hakimel/reveal.js#configuration
Reveal.initialize({
// The "normal" size of the presentation, aspect ratio will be preserved
// when the presentation is scaled to fit different resolutions. Can be
// specified using percentage units.
width: 1280,
height: 960,
// Factor of the display size that should remain empty around the content
margin: 0.1,
// Bounds for smallest/largest possible scale to apply to content
minScale: 0.2,
maxScale: 1.0,
controls: true,
progress: true,
history: true,
center: true,
transition: 'slide', // none/fade/slide/convex/concave/zoom
// not supported? transition-speed: 'fast',
// Optional reveal.js plugins
dependencies: [
{ src: 'reveal.js/plugin/highlight/highlight.js', async: true, condition: function() { return !!document.querySelector( 'pre code' ); }, callback: function() { hljs.initHighlightingOnLoad(); } },
{ src: 'reveal.js/plugin/markdown/marked.js', condition: function() { return !!document.querySelector( '[data-markdown]' ); } },
{ src: 'reveal.js/plugin/markdown/markdown.js', condition: function() { return !!document.querySelector( '[data-markdown]' ); } },
{ src: 'reveal.js/plugin/zoom-js/zoom.js', async: true },
{ src: 'reveal.js/plugin/notes/notes.js', async: true }
],
markdown: {
smartypants: true
}
});
</script>
</body>
</html>