i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n f o r m a t i c s 7 8 ( 2 0 0 9 ) 503–512

journa l homepage: www. int l .e lsev ierhea l th .com/ journa ls / i jmi

Evaluation of a web-based network for reproducible T2* MRIassessment of iron overload in thalassemia

A. Melonia,∗, A. Ramazzotti a, V. Positanoa, C. Salvatoria, M. Mangionea,P. Marcheschia, B. Favilli a, D. De Marchia, S. Pratob, A. Pepea, G. Sallustiod,M. Centrae, M.F. Santarelli a, M. Lombardia, L. Landinia,c

a MRI Laboratory, “G. Monasterio” Foundation and Institute of Clinical Physiology, CNR, Via Moruzzi, 1 - 56124 Pisa, Italyb GE Healthcare, Milano, Italyc Department of Information Engineering, University of Pisa, Pisa, Italyd Radiology Department, “John Paul II” Catholic University, Campobasso, Italye Centro Microcitemia - D.H. Thalassemia Poliambulatorio “Giovanni Paolo II”, Ospedale Casa Sollievo della Sofferenza IRCCS,Opera di Padre Pio da Pietrelcina, San Giovanni Rotondo (FG), Italy

a r t i c l e i n f o

Article history:

Received 25 August 2008

Received in revised form

9 January 2009

Accepted 27 February 2009

Keywords:

Thalassemia

Magnetic resonance

Cardiac disease

Patient monitoring

Network

a b s t r a c t

Purpose: To build and evaluate a national network able to improve the care of thalassemia,

a genetic disorder in haemoglobin synthesis often associated with iron accumulation in a

variety of organs, due to the continuous blood transfusions.

Methods: The MIOT (Myocardial Iron Overload in Thalassemia) network is constituted

by thalassemia and magnetic resonance imaging (MRI) centers. Thalassemia centers are

responsible for patient recruitment and collection of anamnestic and clinical data. MRI

centers have been equipped with a standardized acquisition technique and an affordable

workstation for image analysis. They are able to perform feasible and reproducible heart

and liver iron overload assessments for a consistent number of thalassemia patients in a

robust manner. All centers are linked by a web-based network, configured to collect and

share patient data.

Results: On 30th March 2008, 695 thalassemia patients were involved in the network. The

completion percentage of the patient records in the database was 85 ± 6.5%. Six hundred

and thirteen patients (88%) successfully underwent MRI examination. Each MRI center had a

specific absorption capacity that remained constant over time, but the network was capable

of sustaining an increasing number of patients due to continuous enrollment of new centers.

The patient’s comfort, assessed as the mean distance from the patient home locations to

the MRI centers, significantly increased during the network’s evolution.

Conclusion: The MIOT network seems to be a robust and scalable system in which T2* MRI-

based cardiac and liver iron overload assessment is available, accessible and reachable for

a significant and increasing number of thalassemia patients in Italy (about 420 per year),

reducing the mean distance from the patient locations to the MRI sites from 951 km to

387 km. A solid, wide and homogeneous database will constitute an important scientific

resource, shortening the time scale for diagnostic, prognostic and therapeutical evidence-

based research on the management of thalassemia disease.

© 2009 Elsevier Ireland Ltd. All rights reserved.

∗ Corresponding author. Tel.: +39 050 315 2820; fax: +39 050 3152166.E-mail address: antomeloni@gmail.com (A. Meloni).

1386-5056/$ – see front matter © 2009 Elsevier Ireland Ltd. All rights reserved.doi:10.1016/j.ijmedinf.2009.02.011

i c a l

504 i n t e r n a t i o n a l j o u r n a l o f m e d

1. Introduction

Thalassemia is the most common genetic disorder world-wide [1], characterized by decreased or altered synthesis ofhemoglobin [2]. Based on clinical severity, three forms of tha-lassemia are distinguished: major, intermediate and minor,thalassemia major (TM) being the most severe. People affectedby TM suffer from anemia and require continuous bloodtransfusions, which can lead to iron overload in tissues.Although the survival rate of these patients has improvedin recent years, the prevalence of severe complications isstill high. Heart failure secondary to myocardial iron over-load remains the main cause of morbidity and mortality [3].The iron-induced cardiomyopathy is treatable and reversible ifintensive chelation treatment is instituted in time [4–6]. Thus,precise and effective measurements of iron overload in theheart and liver, where iron deposition seems to be primarilynoticeable [7], are important for the early diagnosis, treatmentand follow-up of thalassemia patients.

Several methods have been proposed for this purpose[8]. Measurement of serum ferritin concentrations is widelyused but it has poor specificity. Liver iron concentration (LIC)measured on needle biopsy is currently considered the goldstandard. Although liver biopsy generally represents totalbody iron load, it does not reflect myocardial iron deposi-tion [9]. Cardiac biopsy has poor sensibility: the myocardialiron deposition is patchy and the test may not provide a trueestimate of iron content, particularly in the early stages ofdisease [10]. Additionally, the biopsy is an invasive techniqueand not easily repeatable. The limitations of these methodshave prompted a search for non-invasive direct means, like themedical imaging techniques. However, iron deposition is notdetectable at ultrasound examination and computed tomog-raphy is not specific for iron [8]. To date, magnetic resonanceimaging (MRI) is the only technique that quantitatively andnon-invasively assesses both myocardial and liver burden [11].MRI multi-echo T2-star (T2*) sequences allow fast monitoringof iron deposition, exploiting the fact that paramagnetic ironcompounds produce variability in susceptibility, shorteningthe T2* relaxation time [12]. T2* cardiac MRI, with a single mea-surement in the mid-ventricular septum [9,13,14] or with amultislice segmental approach [15–17], has been validated forquantitative evaluation of myocardial iron overload (MIO). Inthe liver, the T2* measurement is performed in a small regionof interest of standard dimension, manually drawn in a homo-geneous area of parenchyma without blood vessels [9,16,18].There is a significant correlation between liver T2* and the ironoverload assessment performed through biopsies [9,18].

Despite the previously described advantages, MRI mea-surements may depend on several factors, such as thescanner, the MRI sequence, and the image analysis proce-dure. Hence, in countries with a large number of thalassemiapatients, it may be useful to create a network of MRI cen-ters suitable for performing feasible and reproducible ironoverload assessments under homogeneous standards. In fact,

thalassemia major patients require lifelong MIO monitoringto assess the effectiveness of chelation therapies. Hence, itis highly desirable that MRI be performed near the patientlocations and that the patients be able to safely move

i n f o r m a t i c s 7 8 ( 2 0 0 9 ) 503–512

between different MRI centers. Furthermore, data sharingbetween MRI centers would allow the creation of a largeclinical database in a short time, overcoming the drawbackto obtain a significant amount of data in a single centerfor a rare disease like thalassemia. Moreover, the databasewould allow to develop diagnostic, prognostic and therapeu-tical evidence-based treatments for thalassemia patients andcould constitute an important resource for scientific research.A collaborative network approach is generally recognized asan effective, flexible way to achieve the previously describedobjectives. Several examples of collaborative networks existin thalassemia care. The NIH-funded Thalassemia ClinicalResearch Network (TCRN) includes over 700 patients with allforms of thalassemia. Clinical history is recorded in a centraldatabase [19]. The electronic infrastructure for thalassemiaresearch network (ITHANET) is a euro-mediterranean net-work of research centers conducting molecular and clinicalresearch of thalassemia and related hemoglobinopathies [20].The European Network for Rare and Congenital Anemias(ENERCA) is a network that allows to share all the advancesand experience in the field of rare anaemias, congenital andnon-congenital [21]. The Deniz project implements an elec-tronic database for �-thalassemia mutations in the Arab worldwith a web interface [22]. None of these projects involve quan-titative medical imaging.

The present study describes the MIOT (Myocardial IronOverload in Thalassemia) network, built in Italy in 2006to accomplish the integration of medical imaging withclinical–anamnestic data in thalassemia patient care. Theeffectiveness of the MIOT network in improving the care ofthalassemia major patients has been evaluated on a databaseof about 700 patients who joined the network over 18 months.

2. Methods

2.1. The MIOT network design

The MIOT network was designed to achieve three main objec-tives:

• increase the number of TM patients that can access ironoverload assessment by MRI;

• reduce the distance traveled by a patient to have the MRIexam performed;

• share clinical data between thalassemia and MRI centers.

To address the first two points the network has been opento any haematological and pediatric center specialized in tha-lassemia care. Centers can join the network on voluntarybasis. As shown in Fig. 1, thalassemia centers are mainlylocated in regions with a high prevalence of thalassemia [23].It assures the involvement of a large TM patient population.

Recruitment of MRI centers has been based on epidemio-logical data about the prevalence of thalassemia [23], assuringthe presence of an MRI center at a reasonable distance from

places where patients live. Possession of technical equipmentand availability of medical competencies are also required forMRI sites. Each MRI center joins the MIOT network after valida-tion procedures that assure appropriate standardization of the

i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n

Fig. 1 – Locations of the MIOT thalassemia centers (circles)and MRI centers (stars; the coordinator center in Pisa isindicated by a heart) in Italy. One circle may represent morethan one thalassemia center, if they belong to the samepc

MvPb

ac

((

(

rovince. In gray areas, the incidence of thalassemia traitarriers is greater than 2% [23].

RI acquisition and image analysis protocol. Training is pro-ided by internships at the reference center (the MRI center inisa) and investigator meetings. These activities are supported

y sponsorships.

The third, effective data exchange between thalassemiand MRI centers has been obtained by the creation of a sharedlinical database, easily accessible via a web interface.

Fig. 2 – Flowchart representing the proc

f o r m a t i c s 7 8 ( 2 0 0 9 ) 503–512 505

The study was approved by the Local Ethics Commit-tees and follows the principles outlined in the Declaration ofHelsinki [24].

Fig. 2 shows the flowchart of the procedures undertakenby the centers enrolled in the network. Patient iron overloadassessment in the MIOT network is scheduled as follows.

The thalassemia centers:

a) enroll thalassemia patients;b) inform them about the procedures;(c) verify that the patients do not match exclusion criteria for

MRI;d) obtain informed consent to the project;(e) require the patient’s first examination for iron overload

assessment at one of the MIOT MRI centers;(f) manage the follow-up MRI exam at 18 ± 3 months from the

first evaluation;(g) upload patient anamnestic and clinical data into the

database.

The required anamnestic and clinical data are summarizedin Table 1. There are thirteen sheets, each composed of severalfields. Sheets can only be saved when all mandatory data fieldsare completed.

The MRI centers:

(a) perform image acquisition on liver and heart using the MRImulti-echo T2* technique;

(b) analyze the T2* images to assess heart and liver iron over-

load. T2* results are automatically sent to the database.Hence, the database allows not only easy access to patientclinical history but also fast transmission of MRI results tothe thalassemia center.

edures followed by MIOT centers.

506 i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n f o r m a t i c s 7 8 ( 2 0 0 9 ) 503–512

Table 1 – Synthesis of clinical–anamnestic data in the database. There are thirteen sheets, each consisting of differentfields. For a sheet to be saved, all mandatory fields must be completed. The completion percentage of the patient recordsin the database is also indicated.

Sheet Description Number offields

Number ofmandatory

fields

Completionof data (%)

Identity Data univocally identifying the patient 5 5 100Informed consent Data about signature of informed consent 1 1 93Main pathology Type of thalassemia and transfusional

history14 4 93

General pathological history Other disease 3 3 91Cardiac risk factors Cardiovascular risk factors 20 13 87Cardiac history Cardiac history (i.e. treatment,

hospitalization)25 3 85

Hepatic history Hepatic history and laboratory analysis 20 13 88Haemato-chemical profile Blood tests 18 6 87ECG Parameters extracted from ECG closer to

MRI23 19 81

Echocardiogram Parameters extracted fromechocardiogram closer to MRI

44 10 84

Chelation therapy Previous and current chelation therapiese)

10 3 87

(i.e. dosage, frequency, complianc

Other therapy Eventual other therapiesAdverse events Serious adverse events form

2.2. MRI acquisition and image processing

At all MRI centers, exams are performed using a 1.5-TMRI scanner (GE Signa/Excite HD). For the measurements ofmyocardial T2*, a fast-gradient-echo multi-echo sequence isused with electrocardiogram triggering. Three parallel short-axis views (basal, medium and apical) of the left ventricle (LV)are obtained. Each single short-axis view is acquired at nineincreasing echo times in a single end-expiratory breath-holdto ensure image alignment. For the measurement of liver ironoverload, a T2* gradient–echo multi-echo sequence is used. Asingle transverse slice through the liver is obtained at nineTEs in a single end-expiratory breath-hold. The multi-echosequence parameters are provided in detail in [17,25].

Images are transferred to a dedicated MIOT workstation,developed and installed at each MRI center by the coordinatorcenter. The MIOT workstation includes several DICOM (DigitalImaging and Communications in Medicine) services to han-dle, store, print and transmit MRI images [26]. The DICOMserver was developed by means of Perl DICOM libraries andseveral DICOM tools such as the DCMTK DICOM toolkit fromKuratorium OFFIS [27] and D. Clunie dicomtools [28]. The work-station acts like a SCP (Service Class Provider) and is able toreceive and store the images coming from the MRI scanner orfrom other DICOM-compliant PACS used at each MRI center[29]. The workstation is based on a standard PC architecture(2400 MHz AMD processor, 1 GB RAM, 200 GB RAID1 disk array,1 Gbit/s network interface) and employs Linux as the operat-ing system (OpenSuse 10.1 distribution). The Linux file systemis the ext3 journaled, which is able to avoid any data loss orig-inating from unexpected reboots, unexpected power failure orsystem lock-ups.

MRI image analysis is performed using a custom-written,previously validated software (HIPPO MIOT®, IFC-CNR) devel-oped in the IDL (Interactive Data Language) 6.0 environment[30]. The software runs by exploiting the IDL Virtual Machine

6 3 752 2 72

without need of a license. The software is able to mapthe myocardial T2* distribution into a 16-segment LV modelaccording to the American Heart Association (AHA)/AmericanCollege of Cardiology (ACC) standardized myocardial segmen-tation [31]. The intra-observer, inter-observer and inter-studyvariability of the proposed methodology was previouslyassessed [15]. Briefly, for each short-axis slice, the endocardialand epicardial contours of the LV wall are manually traced inone image corresponding to the first or second echo time. Areference point in the anterior septal insertion of the right ven-tricle is also defined. The two contours and the reference pointare automatically replicated along all the multi-echo images.The myocardium defined in the previous step is automaticallysegmented into equiangular segments starting from the ref-erence point. Six segments are used in the basal and mediumslices, and four are used in the apical slice. For each segment,the mean value of the signal intensity along all TE values iscalculated. The calculated decay curve is fitted to an expo-nential model and the T2* value for the segment is obtained.The global T2* value is obtained by averaging segmental T2*values. When the T2* values related to all segments are cal-culated, they are mapped using a bull’s-eye representation.T2* > 20 ms is considered as a “conservative” normal value forall 16 segments and for the entire heart [9,13].

For the liver, the decay curve is extracted from a large regionof interest of standard dimension, chosen in a homogeneousarea of liver parenchyma without blood vessels, and the valueof T2* is calculated by fitting the decay curve model with asingle exponential with a constant offset [7,25].

All data obtained from heart and liver analysis are saved inPDF format for archiving and further clinical uses, and also asan XML (eXtensible Markup Language) file.

An appropriate script sends the XML file to the MIOT datamanagement system and the relative data are stored in thecentralized MIOT database. Data are transmitted to the centraldatabase by means of an encrypted channel using SSL (Secure

i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n f o r m a t i c s 7 8 ( 2 0 0 9 ) 503–512 507

Fig. 3 – T2* report as seen on the MIOT web site. Patient-specific identifiers are removed to assure privacy. Fiscal code (taxID) is used as a unique identifier of the patient. In the upper part: schematic representation of the myocardium segments inbasal, medium and apical slices following the 16-segment AHA/ACC model. In the lower part: bull’s-eye representation oft t). Hr

SaSm

2

TplairR

itn

he standard segments (left) with corresponding names (righeported to the right of the segment names.

ocket Layer) web services technology. Data transmission isccomplished using the AXIS open source framework and theOAP (Simple Object Access Protocol) protocol. The data areade available through the MIOT web site (Fig. 3).

.3. The MIOT data management system

he MIOT data management system was created to shareatient data between MRI and thalassemia centers. It is modu-

ar and scalable, able to support an increasing number of usersnd patients. The system consists of three components: a web

nterface for data entry, a web service application to automaticallyeceive T2* analysis data from the MIOT workstations, and aelational Database Management System (RDBMS) to store data.

The MIOT web interface is a collection of web pages fornserting and publishing anamnestic and clinical data abouthalassemia patients. To each user is assigned a unique user-ame and password to access to the MIOT web site. The users

eart and liver T2* values obtained from analysis are

at thalassemia centers register the enrolled patients and writeand update the anamnestic and clinical data. Indeed, the userhas to enable the MRI center where patients are sent for theexam to read this information. The MIOT network administra-tors create the user profiles and have access to the anamnestic,clinical, and T2* data of all patients. The website adminis-trators also provide maintenance services for the MIOT website.

The MIOT web service application allows communicationswith the HIPPO MIOT software, to receive the XML files withT2* analysis data from the MRI centers and then to store theMRI data in the MIOT relational database. Therefore, both theMIOT web site and the MIOT web service application feel theMIOT relational database.

Both web interface and web service applications are imple-mented using the Bio Medical Framework (BMF). The BMF isan open source-based framework used to develop distributedhealthcare web applications [32]. In its base installation, the

i c a l i n f o r m a t i c s 7 8 ( 2 0 0 9 ) 503–512

Fig. 4 – Number of thalassemia centers in the MIOTnetwork from September 2006 to March 2008.

Fig. 5 – Number of patients enrolled in the MIOT network

508 i n t e r n a t i o n a l j o u r n a l o f m e d

BMF is able to produce a ready-to-use web site for dataentry, statistical reports (e.g. tables and graphics), single sign-on, role-based access (by means of profiles), multi-language,secure authentication, and transactions. Moreover, the BMFcan use every browser that supports javascript (e.g. InternetExplorer, Mozilla Firefox, Apple Safari) and can be installed ondifferent operating systems. The use of open source softwarelike Apache 2.2, Tomcat 5.5, JfreeChart, log4j and Axis, makesthe framework feasible and cost-effective. The BMF frame-work uses specific tables for its internal functionalities (e.g.authentication of a user and authorization of a user to performsome operations depending on the user profile). The data areencrypted and transmitted across the Internet network usingthe secure http protocol HTTPS, instead of the standard HTTP,to assure patient privacy.

The RDBMS controls the organization, storage, manage-ment and retrieval of data and is implemented with Oracle®

10 g Enterprise. The interface between the RDBMS and the webinterface/service applications exploits the Apache Excaliburconnection pool.

3. Results

3.1. The MIOT network evolution

The MIOT network was created in September 2006, and wasconstituted on that date by the MRI coordinator center in Pisaand 18 haematological or pediatric centers specialized in tha-lassemia. After validation of the T2* MRI technique, Romaand Palermo were activated in November and December 2006,respectively, Ancona and Campobasso in August and Septem-ber 2007, respectively, and Catania in February 2008. Severalother thalassemia centers also have joined the network overtime. On 30th March 2008, 49 thalassemia centers were inthe network (Fig. 4). The centers had a distribution seeminglymatching the prevalence of thalassemia throughout Italy [23](Fig. 1).

3.2. The MIOT patients enrollment

The presence of several MRI centers, located in differentregions of Italy, and the rising number of thalassemia centersleaded to the absorption of a large number of patients. On 30thMarch 2008, 695 thalassemia patients were registered in thedata management system. 613 patients already have under-gone MRI examination (Fig. 5). Twenty patients refused MRIexamination, mainly due to claustrophobia. The remainingpatients were scheduled for future examination.

As can be inferred from Fig. 5, the total number of patientswithin the MIOT network increased almost linearly over time,with a mean increase of 35 new patients per month. The num-ber of MRI examinations followed similarly. Linear regressionanalysis of the two curves (gray lines in Fig. 5) showed a differ-ence of 1.6 between the angular coefficients, corresponding to

a slightly increasing delay between the patient enrollment andT2* analysis. The difference between the number of enrolledpatients and the number of MRI analyses was 33 in September2006 and it is 82 in March 2008.

compared to the number of patients examined by MRI fromSeptember 2006 to March 2008.

3.3. The patient distribution among MRI centers

Linear regression analysis showed that each MRI center had aspecific capacity of absorption that remained constant overtime (Fig. 6). Pisa studied 319 patients in 19 months (16

i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n f o r m a t i c s 7 8 ( 2 0 0 9 ) 503–512 509

Fig. 6 – Cumulative number of patients examined at eachMRI center from September 2006 to March 2008. No datawa

pp((m

3

T(tmltitowtSa2A3P

3

Ftfi

Fig. 7 – For each MRI center, average distances from thethalassemia centers which sent the patients for MRIexamination are plotted versus time. With the activation of

ere yet available for the MRI center in Catania, which wasctivated in February 2008.

atients/month), Roma studied 94 patients in 16 months (6atients/month), Palermo studied 84 patients in 16 months

5 patients/month), Ancona studied 61 patients in 9 months6 patients/month), and Campobasso studied 55 patients in 7

onths (8 patients/month).

.4. Evaluation of the patients comfort

halassemia major patients need continuous transfusions2–4 per month) at thalassemia centers. Hence, patients chosehalassemia centers very close to their place of residence. It

ay be reasonable to take the mean distance from the tha-assemia centers which enrolled patients for the MRI examo the MRI centers where patients undergone the exams as anndicator of patient comfort. Fig. 7 depicts the modifications ofhis index during the project progression. In September 2006,nly the Pisa MRI center was active and the mean distanceas 951 km. In March 2007, when Palermo and Roma joined

he MIOT network, the mean distance reduced to 427 km. Ineptember 2007, when Ancona and Campobasso were alsoctive, the mean distance reduced again to 292 km. In March008, the mean distance to the MIOT MRI centers was 387 km.t this latter time, the mean distances were 480 km to Pisa,77 km to Ancona, 264 km to Campobasso and 238 km toalermo.

.5. Evaluation of the MIOT database

or each patient enrolled, the anamnestic and clinical collec-ion in the database consists of 13 sheets, for a total of 191elds. Out of these fields, 85 are mandatory. The database

new MRI centers, average distances leaded to the samevalue.

allows compilation of different sheets in different sessions,due to the fact that clinical data can be available at differenttimes. However, each sheet can be saved only if all manda-tory fields in the sheet have been compiled. As shown inTable 1, on 30th March 2008 the completion percentage of thesheets for all patients ranged from 72% (adverse events) to 93%(informed consent and basic pathology) (mean value = 85%,standard deviation = 6.5%).

The centralized database is exploited to perform sev-eral tasks. As previously described, the database is useful inpatient management, providing easy access to patient clinicalhistory. The database also allows effective management of thefollow-up MRI exam at 18 ± 3 months from the first evaluation.In fact, the system warns the thalassemia centers about theneed to require the follow-up MRI exam, taking into accountthe length of the current waiting list. Finally, the database isused to conduct several scientific studies on thalassemia, asthe ones on the prevalence of myocardial fibrosis and predic-tive value of electrocardiogram [33].

4. Discussion

At this time, there are about 5000 thalassemia major patientsin Italy who are subjected to continuous blood transfusions. Amajor complication of this treatment is iron overload, whichleads to organ dysfunction. In particular, iron-induced heart

failure remains the main cause of morbidity and mortality inthis population. Chelation therapy, used to remove iron fromthe body, has significantly improved the survival rate in thethalassemia population. However, chelation therapy requires

i c a l

510 i n t e r n a t i o n a l j o u r n a l o f m e d

effective and strict monitoring of organ-specific iron burden,due to the presence of significant side effects and the differentefficacy on specific organs of different chelators. In particular,it is critical to know the heart iron burden in order to man-age thalassemia patients. Moreover, serum ferritin levels andliver iron concentrations have been proven to be insufficientlyreliable markers of myocardial iron overload [9]. The MRIT2* technique based on iron-induced relaxation enhancementallows non-invasive, rapid and reproducible quantification ofboth myocardial and hepatic iron overloads in thalassemiapatients [11,15]. The MRI T2* technique has become a preciousand reliable method in the design of tailor-made chelationtherapies customized for each patient and in the evaluationof their efficacy. However, effective sharing of scientific dataand clinical knowledge between haematologists and cardio-radiologists is needed for full clinical exploitation of the MRIT2* technique.

In our knowledge, the MIOT network represents thefirst example of integration of medical imaging withclinical–anamnestic data in thalassemia patient care. A com-mon solution adopted for image data sharing in medicalimaging are web-based PACS systems [34] that allow easyremote access to image data. Content-based visual informa-tion retrieval systems (CBVIR) can be integrated with PACSfor effective image data access [35]. PACS-CBVIR solution maybe preferable when local availability of images is needed toperform qualitative, eye-based diagnosis. In MRI-based ironoverload assessment, images are exploited only as the input ofan image analysis software that provides iron overload quan-tification, as described in Section 2.2, and do not representitself an useful source of information for thalassemia doctor.Hence, in the MIOT network MRI images are locally stored atMRI centers. This avoids the need of centralized expensivePACS systems and high-speed networks for images transmis-sion. Automatic integration of quantitative imaging data inthe clinical database is achieved using the XML protocol thatis demonstrated optimal for medical data sharing [36].

Integration of thalassemia and MRI centers in the samenetwork represents also an important factor in assuring net-work growing. The MIOT network started in September 2006with the reference center in Pisa and 18 thalassemia centers.Many thalassemia centers have joined the network over time,with 49 enrolled by 30th March 2008 (Fig. 4). This exponen-tial growth, which reflects the success of the network, can beattributed to a combination of factors mainly related to theprogressive creation of information channels in response tothe high request for MRI iron overload assessments. Hence,the access to MRI technology represents a key factor in tha-lassemia centers involvement.

MRI centers have progressively joined the network afterthe validation procedures. On 30th March 2008 five MRI siteswere involved, chosen on the basis of their technical charac-teristics and cardiovascular medical knowledge. Furthermore,their localization attempted to match the prevalence of tha-lassemia through the Italian territory, which was also reflectedby the distribution of the thalassemia centers (Fig. 1). MRI cen-

ters, that joined the network on voluntary basis, were mainlyattracted by the access to a new acquisition technique. In fact,MRI multi-echo T2* sequences able to quantify iron overloadare still non-commercial and their installation requires the

i n f o r m a t i c s 7 8 ( 2 0 0 9 ) 503–512

special involvement of the MRI scanner vendor, assured bythe participation in the project.

The possibility to participate in a clinical and scientificproject involving a significant percentage of the thalassemiapopulation in Italy is also attractive for both thalassemiaand MRI centers. The MIOT network has been presented innational and international meetings, and word-of-mouth haspromoted it among physicians.

We have found that the temporal pattern of the number ofpatients analyzed by all the MRI centers was comparable to thenumber of patients progressively enrolled. This suggests thatthalassemia and MRI centers seem to have reached a good syn-ergy. There was a mean gap of 1.6 patients per month betweenthe enrollment and the analysis, resulting in a greater dif-ference between the number of patients examined and thoseenrolled in March 2008, compared to September 2006 (Fig. 5).Some patients did not get an MRI for medical or personal rea-sons. This may partially explain this finding. A slight increasein the mean waiting time for patients to have the examina-tion performed, due to the fact that requests from thalassemiacenters for MRI assessment exceed the availability of examsper month specific to each MRI center, was also observed. Theanalysis capacity of MRI centers was not easily expandable;due to constraints mainly related to the fact that the MRI siteswithin the MIOT network had to share facilities with routineclinical non-cardiac activities. Activation of other MRI centersis planned for the near future to address this issue and toavoid excessive waiting times, which could also influence theeffectiveness of patient follow-up.

Pisa, which is a cardio-dedicated MRI center, was able toperform a mean of 16 MIOT exams per month (Fig. 6). Thisexplains why about 50% of the total patients were examinedin Pisa. The date of activation had also significantly influ-enced the total number of patients examined per center. Forinstance, Pisa suspended its activities for technical reasonsduring August 2007, and Roma from December 2007 to March2008; moreover, Catania did not begin to perform the clinicalexams by March 2008, although the center had been validated.These aspects affected the global delay.

Although the MIOT network is able to assess a consistentnumber of thalassemia patients (about 420 per year) by T2* MRIthroughout Italy, it will be difficult to satisfy the requests fromthalassemia centers, given the wide indications for cardiacMRI T2* evaluations [11].

One of the main positive consequences of instituting theMIOT network was a decrease in the distances traveled fromthe thalassemia centers, which were close to the patient loca-tions, to the MRI centers (Fig. 7). In other words, as soon as theywere able, the thalassemia centers sent patients to the nearestMRI center, which was more amenable to the patient comfort.This is clearly shown by the descending trend of Pisa. In fact,Pisa is situated in an area little concerned with thalassemiaand is quite distant from the areas where thalassemia hasa high incidence, as opposed to the other MRI centers. Theascending trend of the peripheral centers showed that therespective radius of influence in terms of kilometers tended

to be comparable.

The design and the maintenance of the MIOT database hasthe scientific goals of producing diagnostic, prognostic andtherapeutical evidence-based research in short time periods

i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n

Summary pointsWhat is known before the study?

• Magnetic Resonance Imaging (MRI) allows the quan-titative and non-invasive assessment of both myocar-dial and liver burden in thalassemia patients.

• Thalassemia major patients require lifelong monitor-ing, so it may be useful to create a network of MRIcenters suitable to perform feasible and reproducibleiron overload assessment with homogeneous stan-dards.

What has the study added to the body of knowledge?

• It is possible to build a web-based network ofthalassemia and MRI centers able to assure avail-able, accessible T2* MRI-based cardiac and liver ironoverload assessments for a significant number of tha-lassemia patients.

• The network increases the patient comfort, due to thedecrease in distances traveled from the thalassemiacenters, which are close to the patient locations, to theMRI centers.

• Facilitating data exchange between centers is a keyissue in the creation of a clinical database useful forthe management of thalassemia disease.

ferpisratb

snsmArMtTmewb

A

TC

r

(1993) 1276–1278.

or the management of a rare disease like thalassemia. Consid-ring the high number of data fields to fill out, the completionate was generally satisfying (Table 1). The presence of uncom-leted sheets might be due to difficulty in finding specific

nformation. For instance, for data from instrumental analy-is (echocardiogram, ECG), often the thalassemia doctor mustefer to other specialists. To improve the completion percent-ge of the database, the MIOT users will be monitored, alertedo the scientific value of the database and eventually tutoredy the coordinating center.

In conclusion, the MIOT network seems to be a robust andcalable system through which a substantial and increasingumber of thalassemia patients (about 420 per year) can becanned using homogeneous standard procedures to quantifyyocardial and liver iron overload by the MRI T2* technique.lthough the institution of the MIOT network has significantly

educed the mean distance from the patient locations to theRI sites, other MRI centers should be recruited to redistribute

he overflow requests for T2* exams within the MIOT network.heir location should meet the need to further reduce theean distance traveled by the patients to have the T2* MRI

xam performed. A solid, wide and homogeneous databaseill allow profitable scientific research to collect evidence-ased results about a rare disease like thalassemia.

cknowledgements

he MIOT project has received “no profit support” fromhiesi, Bayer-Schering and GE Healthcare. It is also sup-

f o r m a t i c s 7 8 ( 2 0 0 9 ) 503–512 511

ported by the Italian Foundation “Leonardo Giambrone” andis undertaken on behalf of the Society for Thalassemia andHemoglobinopathies (SOSTE).

We would like to thank the cardio-radiologists at the fol-lowing MRI centers: E. Cracolici, E. Grassedonio and M. Midiri(University of Palermo); M.G. Brizi and L. Natale (CatholicUniversity, Roma); A. Giovagnoni and G. Valeri (University ofAncona); G. Restaino (Catholic University, Campobasso); A.Luciani and V. Magnano (Garibaldi Hospital, Catania); and alsothe haematologists involved in the MIOT project. We finallythank all patients for their cooperation.

Authors’ contributions: A. Meloni contributed in study designand manuscript drafting, A. Ramazzotti in manuscript draftingand data collection, V. Positano in image analysis softwaredesign and development, manuscript revision and approval offinal version, and C. Salvatori contributed in web server designand development, manuscript revision and approval of finalversion. M. Mangione helped with web server design and devel-opment, manuscript revision and approval of the final version,P. Marcheschi with DICOM services design and development,manuscript revision and approval of final version, B. Favilliwith literature research, data collection, manuscript revisionand approval of final version and D. De Marchi helped withMRI sequence optimization, data acquisition, manuscriptrevision and approval of final version. S. Prato contributedin MRI sequence installation and optimization, manuscriptrevision and approval of final version, A. Pepe in study con-cept, MRI data analysis and acquisition, manuscript revisionand approval of final version, G. Sallustio in data acquisition,manuscript revision and approval of final version, M. Centrain data acquisition, manuscript revision and approval of finalversion, M. Lombardi in study concept, manuscript revisionand approval of final version, M.F. Santarelli in data analysisand interpretation, manuscript revision and approval of finalversion and L. Landini contributed in approval of final versionof manuscript and guarantor of integrity of entire study.

e f e r e n c e s

[1] D.J. Weatherall, J.B. Clegg, Thalassemia—a global publichealth problem, Nature Medicine 2 (1996) 847–849.

[2] D.J. Weatherall, Fortnightly review. The thalassaemias,British Medical Journal 314 (1997) 1675–1678.

[3] C. Borgna-Pignatti, S. Rugolotto, P. De Stefano, H. Zhao, M.D.Cappellini, G.C. Del Vecchio, et al., Survival andcomplications in patients with thalassemia major treatedwith transfusion and deferoxamine, Haematologica 89(2004) 1187–1193.

[4] M.A. Aldouri, B. Wonke, A.V. Hoffbrand, D.M. Flynn, S.E.Ward, J.E. Agnew, et al., High incidence of cardiomyopathy inbeta thalassemia patients receiving regular transfusion andiron chelation: reversal by intensified chelation, ActaHaematologica 84 (7) (1990) 113–117.

[5] P. Wacker, D.S. Halperin, D. Balmer-Ruedin, I. Oberhansli, M.Wyss, Regression of cardiac insufficiency after ambulatoryintravenous deferoxamine in thalassemia major, Chest 103

[6] B.A. Davis, J.B. Porter, Long-term outcome of continuous24-hour deferioxamine infusion via indwelling intravenouscatheters in high-risk beta-thalassemia, Blood 95 (2000)1229–1236.

i c a l

512 i n t e r n a t i o n a l j o u r n a l o f m e d

[7] L.J. Noetzli, S.M. Carson, A.S. Nord, T.D. Coates, J.C. Wood,Longitudinal analysis of heart and liver iron in thalassemiamajor, Blood 112 (2008) 2973–2978.

[8] S.I. Mavrogeni, Role of magnetic resonance imaging inmyocardial iron assessment, Current Cardiology Reviews 1(2005) 85–88.

[9] L.J. Anderson, S. Holden, B. Davis, E. Prescott, C.C. Charrier,N.H. Bunce, et al., Cardiovascular T2 star (T2*) magneticresonance for early diagnosis of myocardial iron overload,European Heart Journal 22 (2001) 2171–2179.

[10] L.J. Olson, W.D. Edwards, J.T. Mccall, D.M. Ilstrup, B.J. Gaersh,Cardiac iron deposition in idiopathic hemochromatosis:histologic and analytic assessment of 14 hearts fromautopsy, Journal of the American College of Cardiology 10 (6)(1987) 1239–1243.

[11] T. Cogliandro, G. Derchi, L. Mancuso, M.C. Maye, B. Pannone,A. Pepe, et al., Guideline recommendations for heartcomplications in thalassemia major, Journal ofCardiovascular Medicine 9 (5) (2008) 515–525.

[12] Y. Gossuin, M.R. Muller, P. Gillis, Relaxation induced byferritin: a better understanding for an improved MRI ironquantification, NMR in Biomedicine 17 (2004) 427–432.

[13] M. Westwood, L.J. Anderson, D.N. Firmin, P.D. Gatehouse,C.C. Charrier, B. Wonke, et al., A single breath-holdmultiecho T2* cardiovascular magnetic resonance techniquefor diagnosis of myocardial overload, Journal of MagneticResonance Imaging 18 (2003) 33–39.

[14] J.C. Wood, J.M. Tyszka, S. Carson, M.D. Nelson, T.D. Coates,Myocardial iron loading in transfusion-dependentthalassemia and sickle cell disease, Blood 103 (2004)1934–1936.

[15] A. Pepe, V. Positano, M.F. Santarelli, F. Sorrentino, E.Cracolici, D. De Marchi, et al., Multislice Multiecho T2*cardiovascular magnetic resonance for detection ofheterogeneous distribution of myocardial ironoverload, Journal of Magnetic Resonance Imaging 23(2006) 662–668.

[16] A. Pepe, M. Lombardi, PositanoV, E. Cracolici, M. Capra, R.Malizia, et al., Evaluation of the efficacy of oral deferipronein �-thalassemia major by multi-slice multi-echo T2*,European Journal of Haematology 76 (2006) 183–192.

[17] V. Positano, A. Pepe, M.F. Santarelli, B. Scattini, D. De Marchi,A. Ramazzotti, et al., Standardized T2* map of normalhuman heart in vivo to correct T2* segmental artefacts, NMRin Biomedicine 20 (2007) 578–590.

[18] J.C. Wood, C. Enriquez, N. Ghugre, J.M. Tyzka, S. Carson, M.D.Nelson, et al., MRI R2 and R2* mapping accurately estimateshepatic iron concentration in transfusion-dependentthalassemia and sickle cell disease patients, Blood 106 (2005)1460–1465.

[19] M.J. Cunningham, E.A. Macklin, E.J. Neufeld, A.R. Cohen,

Complications of thalassemia major in North America,Blood 104 (1) (2004) 34–39.

[20] M. Kleanthous, Ithanet Consortium, E-infrastructure forThalassemia Research Network (Ithanet), Blood Cells,Molecules, and Diseases 40 (2) (2008) 272.

i n f o r m a t i c s 7 8 ( 2 0 0 9 ) 503–512

[21] ENERCA Homepage on the Internet. Available from:http://www.enerca.org/, Last accessed on December 2008.

[22] G.O. Tadmouri, R.I. Gulen, Deniz: The electronic database for�-thalassemia mutations in the Arab world, Saudi MedicalJournal 24 (11) (2003) 1192–1198.

[23] I. Bianco Silvestroni, Storia della microcitemia in Italia,Pagine di Scienza e di vita, Giovanni Fioriti Editore, 2002.

[24] World Medical Association declaration of Helsinki,Recommendations guiding physicians in biomedicalresearch involving human subjects, Journal of AmericanMedical Association 277 (11) (1997) 925–926.

[25] V. Positano, B. Salani, A. Pepe, M.F. Santarelli, D. De Marchi,A. Ramazzotti, et al. Improved T2* assessment in liver ironoverload by magnetic resonance imaging. MagneticResonance Imaging 2 (2009) 188–197.

[26] DICOM Homepage on the Internet, Available from:http://medical.nema.org/, Last Accessed on December 2008.

[27] Homepage on the Internet. Available from:http://www.dcmtk.org/, Last Accessed on December 2008.

[28] Homepage on the Internet. Available from:http://www.dclunie.com/, Last Accessed on December 2008.

[29] P. Marcheschi, V. Positano, E.M. Ferdeghini, A. Mazzarisi, A.Benassi, An open source based application for integrationand sharing of multi-modal cardiac image data in aheterogeneous environment, Computers in Cardiology 30(2003) 367–370.

[30] http://www.ittvis.com/ProductServices/IDL.aspx? LastAccessed on December 2008.

[31] M.D. Cerqueira, N.J. Weissman, V. Dilsizian, A.K. Jacobs, S.Kaul, W.K. Laskey, et al., Standardized myocardialsegmentation and nomenclature for tomographic imagingof the heart: a statement for healthcare professionals fromthe Cardiac Imaging Committee of the Council on ClinicalCardiology of the American Heart Association, Circulation105 (2002) 539–542.

[32] M. Mangione, Bio Medical Framework, Manuale delProgrammatore v.1.3. Pisa (Italy): IFC-CNR; 2006. Report No.:2006-TR-001. Contract No.: 2499- ME.P06.008.001.

[33] A. Ramazzotti, A. Pepe, V. Positano, B. Scattini, M.F.Santarelli, L. Landini, et al., Standardized T2* map of anormal human heart to correct T2* segmental artefacts;myocardial iron overload and fibrosis in thalassemiaintermedia versus thalassemia major patients andelectrocardiogram changes in thalassemia major patients,Haemoglobin 32 (2008) 97–107.

[34] H.K. Huang, Enterprise PACS and image distribution,Computerized Medical Imaging and Graphics 27 (2003)241–253.

[35] H. Müller, N. Michoux, D. Bandon, A. Geissbuhler, A reviewof content-based image retrieval systems in medicalapplications–

clinical benefits and future directions, International Journalof Medical Informatics 73 (2004) 1–23.

[36] C.T. Liu, A.G. Long, Y.C. Li, K.C. Tsai, H.S. Kuo, Sharingpatient care records over the World Wide Web, InternationalJournal of Medical Informatics 61 (2001) 189–205.