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J A C C February 1997 ABSTRACTS -Poster 35A D 915116 ThreaDimensional MRIReconstructions of Congenital Cardioveeculer DiaeasewithPersonal Computers G.W. Vick, Ill, T. Geva, R. Rekey. Baylor College of Medicine, Houston TX, USA, Marshfield Clinic, Marahfield W/, USA Magnetic resonance imaging (MRI) data isinherentlythree-dimensional (3D). However, additional processing is required to obtain 3D images of cardio- vascular structures from the arraya of two dimensional tomcgrams produced by cardiac synchronized MRI acquisitions. We have developed techniques for producing 3D images from spin echo and gradient echo MRI data sets with standard desktop personal computers using modified public domain and ayetem software. Our methods included 1) digital transfer of raw Fourier re- constructed image data, 2) interactive semi-automated image segmentation, 3) stepped sequential rotation of the segmented data set with concomitant projection onto a plane using several algorithm-maximal intensity, mean intensity, and surface projection. Animation sequences were thus created, with each frame of the sequence representing a different viewing angle. We created 3D depth-shaded reconstructions of cardiovascular structures of clinical importance from the MRI studies of 114 patients. Patient diagnoses included coerctation of aorta (n = 42), aneurysm of aorta (n = 7), vascular ring (n = 8), pulmonav atresie/Tetralogy of Fallot (n = 11), Fontan (n = 6), Bidirectional Glenn (n = 9), anomalous pulmonary venous connection (n = 9), Transposition (n= 8), Heterotaxy (n = 14). Segmentations were typically accomplished in lees than 20 minutes, and projection reconstruction in 5 minutes or less. Quantitative comparison of linear and cross-sectional mea- surements taken from the 3D reconstructions and from original tomograms showad no significant differences. Pulmonary artery and aortic malforma- tions were best displayed using aurface projection. Pulmonaty and systemic venous and ventricular malformations were best displayed with maximal in- tensity projection. Three dimensional reconstructions are easily performed with standard personal mmputers. They facilitate characterization of torfu- ous vascular and malposed cardiac structures and should be a routine part of MRI analysis of complex congenital cardiovascular disease. m ,nternet 915117 Echocardiography WithSteganographyon the D.M. Shindler. UMDNJ, Robert Wood Johnson Medical School, New Brunswick, NJ, USA InApril 1995,the authorcreatedaWebsiteon the Internetto provideechocar- diographic text, still images, and animation in the format of a free electronic journal. Phyaician letters-to-the-editor about their patients are channeled through atendard electronic mail. This can be intercepted by other Internet usare. In order for e-mail to serve as a foundation for telemedicine, confi- dentiality must be preserved. Public key cryptography provides the means to securely encrypt e-mail communications. It can also be used to digitally sign electronic images and text, and thereby confirm mathematically, both the authenticity and integrity of the e-mail document. Echocarcfiographicimages can also be transformed into encrypted and signed text that can then be sent see-mail. As another option, those same eehoeerdiographic images that we are publicly displaying on the World Wide Web can be easily altered (without knowledge of programming) so that they hold visually imperceptible, en- crypted, and extractable, patient histories as part of the actual image. This is known as steganography. We prepared an explanation of these techniques, using clinical echoesrdiographic examples, at the following Internet address: hffp://w2.umdnj. edui-Shindler/telemedicine.html m 915118 ClinicalUaafulnessofa NeuralNetworkModelfor EvaluationofPrognosticFactorsinCHFin PredictingMortality D.L. Hudson, M.E. Cohen, K.M. Gul, P.C. Deedwania. Univeraityof California, San Francisco VAMedical Centec Fresno, CA, USA We have previously described a connactionist expeti system derived from a neural network model for prognostic factors in congestive heart failure (CHF). The initial model was based on a sample of 100 CHF patients: 50 surviving and 50 deceased. The learning algorithm we have developed ganerates a non-linear decision surface which divides eases into two or more categories based on non-statistical technique. Output from the model is easy to interpret. An equation of the fo~: D (x) = z wi xi + X wi,jxi xj is obtained. The weighting factorwi on each xi indicates the relative importance of that parameter; wi,j indicates the relative importance of the interaction of XIand xj. The variables identified in the initial model were: symptom status (decreased, ateble, increaaad), BUN, orthopnea (yin), dyapnea at rest (y/n), heart rate, edema (y/n), functional impairment (levels 1-3), PND (y/n). In tha current study, an additional 446 patients were included who have been treated for CHF and followed at our center between 1992 and 1996. The parameters from the original model were used with the new expanded data set to test stability. The following measures were obtained: Sensitivity SDecificitv Accuracv InitialModsl 79% so% 79”/. Exoanded Model 70% 73% 71% Conclusion: The data indicate that the neural network model which we have developed is useful in predicting survival in patients with CHF. 1915-119[DiagnosticContentofDigtital Coronary Arteriograms isUnaffectedby12:1Image Compression R. Kirkeeide, P, Bereffa 1, R.W. Smalling, H.V, Anderson, G. Schroth, K.L. Gould, University of Texas-Houston,USA, 1Phiiips Medical Systems, Best, The Netherlands Image compression offers benefits in storing and distributing digital arteri- ograms, but its effect on image diagnostic content is unclear. Methods: We examined the effects of image compression on visual scoring of coronary dis- ease in 24 diagnostic cases. Each case was processed to yield 4 case image sets: the original uncompressed ease (Orig), a replicate of Orig (Repeat), a 12:1 JPEG compressed version of Orig (JPEG), and a 12:1 Lapped Orthog- onal Transform compressed version of Orig (LOT). Each set was blindly and separately read by 4 angiographers, assessing disease severity in 15 pre- define coronaty segments on a C-5 scale (normal to occluded). Agreement in scoring the four sets of each case was evaluated by the Kappa statistic and the Lin concordance coefficient (Lin). The effect of image compression on arteriogram scoring was determined by comparison of the Kappa and Lin values for each treatment with thosefrom the repeat scoring of the original angiograms (Repeat vs Orig). Resu/fs.’Therewas good agreement in scoring coronary segments irrespective of image treatment (Kappa = 0.48 and Lin = 0.79 for all treatments). No significant differences in angiogram scoring due to image compression were found. Conclusion: Inspite of some quali- tative differences in image texture, the 12:1 image compression treatments examined here did not alter the perceived diagnostic eontent of coronary arferiograms. I 915-1201 ,nviv~v~ifd~ti~n of~N~wThr-Dim~~=i~n~! VectorModelofDistancainHumanCoronary Arteries T. Dodge, M. Goal, E. A1-Mousa,W. Daley, G. Brown, M. Gibson. Brigham and Women’s Hospital & West Roxbury Veterans Affairs Medical Centec Boston, MA, USA A previously described three dimensional vector model of coronary artery spatial locations has been extended to develop a new model of distances within the coronary tree. The goal of this study was to determine how closely actual measured distances using a PTCA guidewire corresponded to pre- dicted distances in the spatial kwetion model and the new distance model. The distance model was created from orthogonal angiograms of 30 RCAS and 27 LCAS after normalizing for differences in heart size. The distance from the left main to the previously described LAD TIMI Frame Count (TFC) landmark at the apex of the heart and from the RCA ostium to the RCA TFC landmark were calculated from each angiogram pair. These distances were also calculated in the spatial iocation model from the mean locations of these points, a process which excludes any affect of vessel tortuosity on the Calculateddistances. In 35 pts undergoing PTCA, the length of the guidewire between the coronary ostium and the TFC landmark in the LCA (n = 14) or the RCA (n = 21) was directly measured. Length(cm): Measured DiatanceModel SpatialModel tAD 15.7 ● 1.2* 15,7 * 0,s” 14,9 RCA 11,1 i 1.5” 11.2 * 1.5* 10.4 ‘ P = NS for comparisonsbetween measured and distance modelprediction Vessel tortuosity accounts for 6% (i.e. 15.7 – 14.9/15.7 = 6%) of the distance between locations in the human coronary artery tree. Cone/usion:.A 3-dimensional vector model of the human coronary artery tree haa bean extended to create a new model which accurately predicts mean distances along coronary arteries for groups of patienta with normal sized hearta.
Transcript of Abstract
J A C CFebruary 1997 ABSTRACTS -Poster 35A
D915116 ThreaDimensionalMRIReconstructionsofCongenitalCardioveeculerDiaeasewithPersonalComputers
G.W. Vick, Ill, T. Geva, R. Rekey. Baylor College of Medicine, Houston TX,USA, Marshfield Clinic, Marahfield W/, USA
Magnetic resonance imaging (MRI) data isinherentlythree-dimensional (3D).However, additional processing is required to obtain 3D images of cardio-vascular structures from the arraya of two dimensional tomcgrams producedby cardiac synchronized MRI acquisitions. We have developed techniquesfor producing 3D images from spin echo and gradient echo MRI data setswith standard desktop personal computers using modified public domain andayetem software. Our methods included 1) digital transfer of raw Fourier re-constructed image data, 2) interactive semi-automated image segmentation,3) stepped sequential rotation of the segmented data set with concomitantprojection onto a plane using several algorithm-maximal intensity, meanintensity, and surface projection. Animation sequences were thus created,with each frame of the sequence representing a different viewing angle.We created 3D depth-shaded reconstructions of cardiovascular structures ofclinical importance from the MRI studies of 114 patients. Patient diagnosesincluded coerctation of aorta (n = 42), aneurysm of aorta (n = 7), vascularring (n = 8), pulmonav atresie/Tetralogy of Fallot (n = 11), Fontan (n = 6),Bidirectional Glenn (n = 9), anomalous pulmonary venous connection (n =9), Transposition (n= 8), Heterotaxy (n = 14). Segmentations were typicallyaccomplished in lees than 20 minutes, and projection reconstruction in 5minutes or less. Quantitative comparison of linear and cross-sectional mea-surements taken from the 3D reconstructions and from original tomogramsshowad no significant differences. Pulmonary artery and aortic malforma-tions were best displayed using aurface projection. Pulmonaty and systemicvenous and ventricular malformations were best displayed with maximal in-tensity projection. Three dimensional reconstructions are easily performedwith standard personal mmputers. They facilitate characterization of torfu-ous vascular and malposed cardiac structures and should be a routine partof MRI analysis of complex congenital cardiovascular disease.
m ,nternet915117 EchocardiographyWithSteganographyonthe
D.M. Shindler. UMDNJ, Robert Wood Johnson Medical School, NewBrunswick, NJ, USA
InApril 1995,theauthorcreatedaWebsiteon the Internettoprovideechocar-diographic text, still images, and animation in the format of a free electronicjournal. Phyaician letters-to-the-editor about their patients are channeledthrough atendard electronic mail. This can be intercepted by other Internetusare. In order for e-mail to serve as a foundation for telemedicine, confi-dentiality must be preserved. Public key cryptography provides the means tosecurely encrypt e-mail communications. It can also be used to digitally signelectronic images and text, and thereby confirm mathematically, both theauthenticity and integrity of the e-mail document. Echocarcfiographicimagescan also be transformed into encrypted and signed text that can then be sentsee-mail. As another option, those same eehoeerdiographic images that weare publicly displaying on the World Wide Web can be easily altered (withoutknowledge of programming) so that they hold visually imperceptible, en-crypted, and extractable, patient histories as part of the actual image. This isknown as steganography. We prepared an explanation of these techniques,using clinical echoesrdiographic examples, at the following Internetaddress:hffp://w2.umdnj. edui-Shindler/telemedicine.html
m915118 ClinicalUaafulnessofa NeuralNetworkModelforEvaluationof PrognosticFactorsinCHFinPredictingMortality
D.L. Hudson, M.E. Cohen, K.M. Gul, P.C.Deedwania. UniveraityofCalifornia, San Francisco VAMedical Centec Fresno, CA, USA
We have previously described a connactionist expeti system derived froma neural network model for prognostic factors in congestive heart failure(CHF). The initial model was based on a sample of 100 CHF patients:50 surviving and 50 deceased. The learning algorithm we have developedganerates a non-linear decision surface which divides eases into two ormore categories based on non-statistical technique. Output from the modelis easy to interpret. An equation of the fo~: D (x) = z wi xi + X wi,j xi xj isobtained. The weighting factorwi on each xi indicates the relative importanceof that parameter; wi,j indicates the relative importance of the interaction ofXIand xj. The variables identified in the initial model were: symptom status(decreased, ateble, increaaad), BUN, orthopnea (yin), dyapnea at rest (y/n),heart rate, edema (y/n), functional impairment (levels 1-3), PND (y/n). Intha current study, an additional 446 patients were included who have beentreated for CHF and followed at our center between 1992 and 1996. The
parameters from the original model were used with the new expanded dataset to test stability. The following measures were obtained:
Sensitivity SDecificitv Accuracv
InitialModsl 79% so% 79”/.ExoandedModel 70% 73% 71%
Conclusion: The data indicate that the neural network model which wehave developed is useful in predicting survival in patients with CHF.
1915-119[ DiagnosticContentofDigtitalCoronaryArteriogramsis Unaffectedby12:1ImageCompression
R. Kirkeeide, P,Bereffa 1, R.W. Smalling, H.V, Anderson, G. Schroth,K.L. Gould, University of Texas-Houston,USA, 1Phiiips Medical Systems,Best, The Netherlands
Image compression offers benefits in storing and distributing digital arteri-ograms, but its effect on image diagnostic content is unclear. Methods: Weexamined the effects of image compression on visual scoring of coronary dis-ease in 24 diagnostic cases. Each case was processed to yield 4 case imagesets: the original uncompressed ease (Orig), a replicate of Orig (Repeat), a12:1 JPEG compressed version of Orig (JPEG), and a 12:1 Lapped Orthog-onal Transform compressed version of Orig (LOT). Each set was blindly andseparately read by 4 angiographers, assessing disease severity in 15 pre-define coronaty segments on a C-5 scale (normal to occluded). Agreementin scoring the four sets of each case was evaluated by the Kappa statisticand the Lin concordance coefficient (Lin). The effect of image compressionon arteriogram scoring was determined by comparison of the Kappa and Linvalues for each treatment with thosefrom the repeat scoring of the originalangiograms (Repeat vs Orig). Resu/fs.’Therewas good agreement in scoringcoronary segments irrespective of image treatment (Kappa = 0.48 and Lin= 0.79 for all treatments). No significant differences in angiogram scoringdue to image compression were found. Conclusion: Inspite of some quali-tative differences in image texture, the 12:1 image compression treatmentsexamined here did not alter the perceived diagnostic eontent of coronaryarferiograms.
I 915-1201 ,nviv~v~ifd~ti~n of~N~wThr-Dim~~=i~n~!VectorModelof Distancain HumanCoronaryArteries
T. Dodge, M. Goal, E. A1-Mousa,W. Daley, G. Brown, M. Gibson. Brighamand Women’sHospital & West Roxbury Veterans Affairs Medical CentecBoston, MA, USA
A previously described three dimensional vector model of coronary arteryspatial locations has been extended to develop a new model of distanceswithin the coronary tree. The goal of this study was to determine how closelyactual measured distances using a PTCA guidewire corresponded to pre-dicted distances in the spatial kwetion model and the new distance model.
The distance model was created from orthogonal angiograms of 30 RCASand 27 LCAS after normalizing for differences in heart size. The distancefrom the left main to the previously described LAD TIMI Frame Count (TFC)landmark at the apex of the heart and from the RCA ostium to the RCA TFClandmark were calculated from each angiogram pair.
These distances were also calculated in the spatial iocation model fromthe mean locations of these points, a process which excludes any affect ofvessel tortuosity on the Calculateddistances.
In 35 pts undergoing PTCA, the length of the guidewire between thecoronary ostium and the TFC landmark in the LCA (n = 14) or the RCA (n =21) was directly measured.
Length(cm): Measured DiatanceModel SpatialModeltAD 15.7 ● 1.2* 15,7 * 0,s” 14,9RCA 11,1 i 1.5” 11.2 * 1.5* 10.4
‘ P = NS for comparisonsbetween measured and distance modelprediction
Vessel tortuosity accounts for 6% (i.e. 15.7 – 14.9/15.7 = 6%) of thedistance between locations in the human coronary artery tree.
Cone/usion:.A 3-dimensional vector model of the human coronary arterytree haa bean extended to create a new model which accurately predictsmean distances along coronary arteries for groups of patienta with normalsized hearta.
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