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In oducing he Open and Rep oducible
Musculoskele al Imaging Resea ch (ORMIR) communi y
Se ena Bona e i
1
, Leona do Ba zaghi
2
, Moj aba Ba zega i
3
, And ew J. Bu gha d
4
, Donnie Came on
5
, Julio
Ca ballido-Gamio
6
, Gianluigi C imi
7
, Pholpa Du ongbhan
8
, Michelle Espinosa He nandez
9
, Giulia
F a e igo7,
10
, Lo enzo G assi
11
, Has ings G ee
12
, Gianluca Io i
13
, Michael Kuczynski
14
, Sa ah Manske14,
Ma hew McCo mick
15
, Na han Nee eson14, Ma c Nie hamme 12, Ma ino Pani
16
, Jilmen Quin iens
17
, Majid
Mohammad Sadeghi
18
, F ancesco San ini
19
, En ico Schileo7, Ka h yn S. S ok8, Ful ia Taddei7, Jus in J. Tse14,
Ja ed Vico y15, Ma iska Wesseling
20
, Andy Kin On Wong
21
, Dženan Zukić15
1
Swiss Cen e o Musculoskele al Imaging, Balg is Campus, Zu ich, Swi ze land
2
Ad anced Imaging and Radiomics cen e , Neu o adiology Depa men , IRCCS Mondino Founda ion, Pa ia, I aly
3
Biomechanics sec ion, Depa men o Mechanical Enginee ing, KU Leu en, Leu en, Belgium
4
Depa men o Radiology and Biomedical Imaging, Uni e si y o Cali o nia, San F ancisco, Uni ed S a es
5
C.J. Go e MRI Cen e , Depa men o Radiology, Leiden Uni e si y Medical Cen e , Leiden, Ne he lands
6
Depa men o Radiology, Uni e si y o Colo ado Anschu z Medical Campus, Den e , Uni ed S a es
7
Bioenginee ing and Compu ing Labo a o y, IRCCS Is i u o O opedico Rizzoli, Bologna, I aly
8
Depa men o Biomedical Enginee ing, The Uni e si y o Melbou ne, Pa k ille, Aus alia
9
Rehabili a ion Sciences Ins i u e, The Uni e si y o To on o, To on o, Canada and Depa men o Biomedical Enginee ing, The
Uni e si y o Melbou ne, Pa k ille, Aus alia
10
Depa men o Mechanical and Ae ospace Enginee ing. Poli ecnico di To ino, To ino, I aly
11
Depa men o Biomedical Enginee ing, Lund Uni e si y, Lund, Sweden
12
Depa men o Compu e Science, The Uni e si y o No h Ca olina a Chapel Hill, Chapel Hill, Uni ed S a es
13
Synch o on-ligh o Expe imen al Science and Applica ions in he Middle Eas , Allan, Jo dan
14
Depa men o Biomedical Enginee ing, McCaig Ins i u e o Bone and Join Heal h, Cumming School o Medicine, Uni e si y o
Calga y, Calga y, Canada
15
Medical Compu ing Depa men , Ki wa e, Inc, Uni ed S a es
16
School o Mechanical and Design Enginee ing, Uni e si y o Po smou h, Po smou h, UK
17
Depa men o Mechanical Enginee ing, Biomechanics Sec ion, KU Leu en, Leu en, Belgium
18
Depa men o O hopedic Su ge y, Maas ich Uni e si y, The Ne he lands
19
Basel Muscle MRI, Depa men o Biomedical Enginee ing, Uni e si y o Basel, Basel, Swi ze land and Depa men o Radiology,
Uni e si y Hospi al Basel, Basel, Swi ze land
20
Depa men o Biomechanical Enginee ing, TU Del , Del , he Ne he lands
21
Join Depa men o Medical Imaging, Uni e si y Heal h Ne wo k, On a io, Canada
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ABSTRACT
In musculoskele al (MSK) imaging esea ch, scien is s ex ac quan i a i e in o ma ion om
medical images o in es iga e ch onic and debili a ing diseases such as a h i is, os eopo osis, and
neu omuscula diseases. The compu a ional ools used o pe o m analyses a e usually highly agmen ed
and o en in ol e p op ie a y so wa e, causing esou ce was e in e-implemen a ions and ul ima ely
slowing he ad ancemen o he esea ch ield as a whole. The use o di e en code o e alua ing simila
p ocesses also unde mines scien i ic compa ison and igo . The ORMIR communi y aims o c ea e and
dissemina e open, ep oducible, well- es ed, and well-documen ed so wa e o analyze musculoskele al
images. Any in e es ed scien is s a e welcome o join and con ibu e o he communi y.
ARTICLE
In musculoskele al (MSK) imaging esea ch, scien is s ex ac quan i a i e in o ma ion om
medical images o join s, bones, and muscles o in es iga e ch onic and debili a ing diseases such as
a h i is, os eopo osis, and muscula dys ophies (1–9). Compu a ional ools used o pe o m analyses
consis o wo k lows wi h a common s uc u e: 1) acquisi ion o medical images using, e.g., compu ed
omog aphy o magne ic esonance, ei he a he o gan le el (mm esolu ion) o issue le el (µm esolu ion
in he o de o ); 2) segmen a ion o images o ex ac he MSK o gans and issues o in e es —p ima ily
bone, muscle, and ca ilage; and 3) compu a ion o me ics o quan i y o gan o issue mo phology,
composi ion, and mechanical esponse. Va ia ions ac oss compu a ional wo k lows a e de e mined by
implemen a ion choices, including algo i hms, compu a ional pa ame e s, and e alua ion me ics.
Bo h wi hin and ac oss esea ch labo a o ies, he unde lying de elopmen o compu a ional
wo k lows is subjec o se e al challenges. In esea ch g oups, locally de eloped code is usually
agmen ed, as i mainly consis s o a combina ion o p op ie a y so wa e and in-house algo i hms.
P op ie a y so wa e is o en dis ibu ed wi h p e-se pipelines; hus, scien is s can a ely e i y
pa ame e s and implemen a ions, c ea ing di icul ies in adap ing he code o new images o ana omies.
In addi ion, in-house so wa e is o en c ea ed as pa o a speci ic p ojec o limi ed du a ion.
Consequen ly, code li e is s ic ly linked o he employmen o he code c ea o s, es ic ing code euse
and expansion by newe lab membe s. I can also educe he in eg i y o scien i ic esul s when s udies
canno be di ec ly compa ed due o dissimila analysis app oaches, limi ing esea ch ep oducibili y and
alsi ica ion.
In he b oade MSK imaging esea ch communi y, so wa e is usually no open sou ce and, e en
when i is, i is o en di icul o euse because o lack o documen a ion (10), o i depends on p op ie a y
languages and en i onmen s, such as MATLAB o Ma hema ica. Consequen ly, labo a o ies can a ely
euse exis ing code, unless hey alloca e esou ces o e-implemen ing algo i hms om publica ions,
which o en lack implemen a ion de ails (11,12). Fu he , absence o openly sha ed code a a communi y
le el limi s compa ibili y wi h e ol ing echnologies, expansion o code unc ionali ies (13), compa ison
wi h new algo i hms, and c ea ion o alida ed s anda d p ocedu es ha can be us ed by he scien i ic
communi y as a whole (14). Collabo a ions ac oss labo a o ies would sol e hese challenges and
po en ially accele a e scien i ic disco e ies in musculoskele al esea ch (15,16).
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Se e al esea ch communi ies in o he disciplines ha e sough o ackle code agmen a ion by
c ea ing open so wa e dis ibu ion pla o ms. In genomic esea ch, ‘Bioconduc o ’ is a so wa e
dis ibu ion ha collec s mo e han 2,000 packages w i en in he R p og amming language o analyze
da a anging om single-cell sequencing o low cy ome y (17). In geoscience esea ch, ‘Pangeo’ is a
high-pe o mance-compu ing en i onmen wi h co e packages o big da a esea ch, showcased by a ich
Jupy e no ebook galle y (18); he Pangeo communi y is ollowed by mo e han 5,000 esea che s on
Twi e and by mo e han 800 people on i s blog medium.com/pangeo. In he b ain imaging communi y,
esea che s coding in R can bene i om ‘Neu oconduc o ’, an open-sou ce pla o m o apid es ing and
dissemina ion o compu a ional imaging so wa e, cu en ly hos ing 86 packages (19).
Following he example o success ul communi ies in o he esea ch ields, we es ablished he
Open and Rep oducible Musculoskele al Imaging Resea ch (ORMIR) communi y, cu en ly including mo e
han 30 scien is s om in e na ional academic ins i u ions and indus y. The p oposal o code sha ing,
openness, and ep oducibili y as a solu ion o code agmen a ion s a ed ci cula ing wi hin he MSK
imaging esea ch communi y du ing sa elli e e en s
1
o he Quan i a i e Musculoskele al Imaging
(QMSKI) Wo kshop in 2019. A ew mon hs la e , a g oup o nine esea che s
2
ook o mal ini ia i e and
success ully applied o unds o hold a Jupy e Communi y Wo kshop. O iginally planned o 2020, i
was e en ually held in 2022 due o he global pandemic (wo kshop epo a (21)). Since he communi y
was ounded, he membe ship has inc eased in numbe , and membe s ha e s a ed collabo a ing on
compu a ional wo k lows in ou speci ic ields ha add ess he musculoskele al bu den o a h i is,
os eopo osis, and muscula dys ophies: quan i ica ion o bone and join mo phology om High-
Resolu ion pe iphe al Quan i a i e Compu ed Tomog aphy (HR-pQCT) images, image-based mic o ini e
elemen modeling, s anda diza ion o da a o ma s o magne ic esonance (MR) muscle imaging, and
analysis o MR images o he knee (Table 1). Ini ial esul s we e dissemina ed du ing concomi an e en s
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a he QMSKI 2022 wo kshop, and packages a e cu en ly unde u he de elopmen o main enance.
The ORMIR communi y aims o con inue c ea ing and dissemina ing open, ep oducible, well-
es ed, and well-documen ed so wa e o analyzing musculoskele al images. Fu u e ini ia i es will
include c ea ing empla es o homogenize code documen a ion and a ce i ica ion sys em o s anda dize
code. In he longe e m, he communi y aims o sha e images and expe imen al da a o c ea e la ge
da ase s o c oss- alida ion o algo i hms and la ge -scale compu a ions. We will also seek o engage
u he wi h clinicians and clinical ial specialis s o use hese app oaches o answe clinical ques ions
ela ing o a h i is, os eopo osis, and neu omuscula diseases.
The ORMIR communi y egula ly sha es upda es on eleases, mee ings, and e en s h ough a
websi e (o mi communi y.gi hub.io) and a Twi e accoun (@ORMIR_Communi y), and aims o con ene
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“Hands-on T anspa en QMSKI esea ch: Open da a, ep oducible wo k lows, and in e ac i e publica ions” o ganized by S.
Bona e i (20), and “Wo king g oup on s anda diza ion o quan i a i e me ics o 3D imaging” o ganized by A. Bu gha d , P.
Shneide , and S. Boyd
2
Ba zega i M., Bona e i S., Bu gha d A., Ca ballido-Gamio J., G assi L., Manske S., Schileo E., S ok K., Taddei, F.
3
“In oducing he Open and Rep oducible Musculoskele al Imaging Resea ch (ORMIR) communi y” o ganized by S. Bona e i, E.
Schileo, and S. Manske (22), and “A e open and ep oducible wo k lows necessa y o CT in clinical ials and esea ch” o ganized
by S. Manske, A. Bu gha d , and K. S ok
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in-pe son a ound he ime o he QMSKI wo kshop e e y wo yea s. We in i e any in e es ed scien is s o
join ou ORMIR communi y and con ibu e o accele a ing and suppo ing ad ancemen o quan i a i e
MSK imaging esea ch.
Py hon package name
Desc ip ion
Gi Hub eposi o y
Packages de eloped wi h he suppo o he ORMIR communi y
Ciclope
P ocessing o mic o compu ed
omog aphy images o gene a e mic o
ini e elemen models.
gi hub.com/gian hk/ciclope
MuscleBIDS
Reading and w i ing a s anda dized da a
o ma o muscle MR imaging ha is
based on BIDS
gi hub.com/muscle-bids/muscle-bids
ORMIR_XCT
Compu ing bone mic oa chi ec u e and
join space om HR-pQCT images
gi hub.com/Spec aCollab/ORMIR_XCT
P e-exis ing packages c ea ed and main ained by membe s o he ORMIR communi y
pyKNEE
Segmen ing and analyzing emo al knee
ca ilage om MR images
gi hub.com/sbona e i/pyKNEE
OAI analysis 2
Segmen ing, egis e ing, and analyzing
emo al and ibial knee ca ilage om
he MR images o he whole OAI da ase
gi hub.com/uncbiag/OAI_analysis_2
ITKIOScanco
An ITK module o ead and w i e Scanco
mic oCT .isq iles
gi hub.com/Ki wa eMedical/ITKIOScanco
Da ne
A segmen a ion ool o muscle MR
images based on ede a ed deep
lea ning
gi hub.com/da ne-imaging
Table 1. Py hon packages cu en ly suppo ed by he ORMIR communi y. Each Gi Hub eposi o y con ains he Py hon
package and in o ma ion on how o use i . S anda diza ion o code s yle, documen a ion s yle, and ile o ma s is
unde de elopmen . Abb e ia ions: MR: Magne ic Resonance; BIDS: B ain Imaging Da a S uc u e (23); OAI:
Os eoA h i is Ini ia i e (24); HR-pQCT: High-Resolu ion pe iphe al Quan i a i e Compu ed Tomog aphy.
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