Standardized unfold mapping: a technique to permit left atrial regional data display and analysis
Standardized unfold mapping: a technique to permit left atrial regional data display and analysis
Steven E. Williams 0 1 2
Catalina Tobon-Gomez 0 1 2
Maria A. Zuluaga 0 1 2
Henry Chubb 0 1 2
Constantine Butakoff 0 1 2
Rashed Karim 0 1 2
Elena Ahmed 0 1 2
Oscar Camara 0 1 2
Kawal S. Rhode 0 1 2
0 PhySense, Universitat Pompeu Fabra , Barcelona , Spain
1 Translational Imaging Group, Centre for Medical Image Computing, University College London , London , UK
2 Division of Imaging Sciences and Biomedical Engineering, King's College London , 4th Floor North Wing, St. Thomas' Hospital , 249 Westminster Bridge Road, London SE1 7EH , UK
3 Steven E. Williams
Purpose Left atrial arrhythmia substrate assessment can involve multiple imaging and electrical modalities, but visual analysis of data on 3D surfaces is time-consuming and suffers from limited reproducibility. Unfold maps (e.g., the left ventricular bull's eye plot) allow 2D visualization, facilitate multimodal data representation, and provide a common reference space for inter-subject comparison. The aim of this work is to develop a method for automatic representation of multimodal information on a left atrial standardized unfold map (LA-SUM).
Atrial fibrillation; Catheter ablation; Cardiac magnetic resonance; Unfold map; Regional analysis; Contact-force analysis
SEW and CTG contributed equally to this study.
A new, standardized, two-dimensional left atrial unfold map (LA-SUM)
is developed allowing simultaneous visualization of all regions of the
Using the LA-SUM, a 24-region LA segmentation is proposed in order
to facilitate regional assessment of left atrial arrhythmia substrates.
Application of the LA-SUM for intra-patient comparison of imaging
and electrophysiological datasets is demonstrated.
The LA-SUM also facilitates inter-patient comparisons of regional LA
parameters, as demonstrated for segmental PV force-time integrals
Left ventricular imaging data has long been visualized and
compared using surface flattening techniques (‘polar’ or
‘bull’s eye’ plots). A wide variety of data input sources have
been used to create such plots, including echo strain mapping,
SPECT imaging, and cardiac magnetic resonance imaging [
]. By resolving different data sources onto a single spatial
domain, direct comparisons between substrate analysis
techniques for the left ventricle become possible . Meanwhile,
left atrial (LA) electrophysiological substrate assessment has
progressed in recent years with voltage mapping, activation
mapping, rotor mapping, complex signal analysis, CT
imaging, and CMR imaging [
], all providing valuable information
in various settings. To deal with such an abundance of
information, we recently proposed a technique to allow
simultaneous representation of multiple parameters on a single 3D
cardiac chamber model [
Against this background, surface flattening techniques
offer some advantages over 3D shells by (1) enabling
simultaneous visualization of all available information and (2)
facilitating intra- and inter-subject comparisons of datasets. For
example, unfold maps have been used to compare pre- and
post-ablation maps of the same subject [
]. Since the shape of
these unfold maps changes with the geometry of the left
atrium, this approach is limited to intra- rather than inter-patient
comparisons. Therefore, in this study, we generate a
standardized regional unfold map (LA-SUM) that follows the same
template for all subjects. Akin to the ventricular ‘bull’s eye’
plot, the proposed LA-SUM allows for intra-patient
comparison of multimodal data and provides a common reference
space for inter-subject analysis. After developing the
LA-SUM, we demonstrate its application in representing
post-ablation atrial enhancement on CMR imaging, and
comparing ablation parameters between cases undergoing
pulmonary vein isolation.
2.1 Study population and data collection
The study population comprised 28 patients who underwent
clinically indicated electroanatomic mapping procedures.
Data collection was approved by the National Research
Ethics Service (REC reference numbers: 10/H0802/77 and
08/H0802/68), and all patients gave written informed consent.
The cases were divided into two sets (see Fig. 1a, b) as
Set A was used to develop the LA-SUM technique,
including the determination of 2D LA-SUM correlates of
3D LA regions. Set A consisted of 18 patients
(61 ± 12 years, 9 males, 13 paroxysmal AF, 3 persistent
AF, 2 left-sided accessory pathways) undergoing left
atrial local activation time (LAT) mapping prior to
pulmonary vein isolation or accessory pathway ablation.
Set B was used to test the application of the LA-SUM
technique, including intra-patient comparison of
post-ablation scar formation. Set B consisted of ten
patients (60 ± 11 years, seven males, five persistent AF)
undergoing wide area circumferential ablation (WACA)
for pulmonary vein isolation (PVI) using a contact force
sensing catheter (SmartTouch, Biosense Webster,
Diamond Bar, CA, USA).
2.1.1 Electroanatomic mapping
Following trans-septal puncture, a 3D geometry of the left
atrium was created using either the Velocity (St Jude
Medical Inc., St Paul, MN, USA) or Carto3 (Biosense
Webster, Diamond Bar, CA, USA) EAM platforms. Bipolar
electrograms were collected throughout the left atrium using
the PentaRay mapping catheter (Biosense Webster, Diamond
Bar, CA, USA) during pacing from the high right atrium
(HRA) or mid-coronary sinus (CS). Electrode positions for
each LAT sampling site were recorded on the 3D geometry.
LAT for each recording site was defined as the time from
pacing stimulus to the earliest sharp deflection on each local
electrogram. LAT maps were created by interpolating LAT
times across each 3D geometry, with a distance fill threshold
of 10 mm.
2.1.2 Cardiac magnetic resonance imaging
Post-ablation atrial CMR imaging was performed in set B at a
median of 4 (range 3–12) months post-ablation using an
Achieva 3.0T MRI scanner (Philips, Best, The Netherlands).
3D whole heart (WH) and 3D late gadolinium enhancement
(LGE) datasets were obtained and processed using a
maximum intensity projection in order to quantify the extent of
post-ablation injury, as previously described [
] (see online
2.2 LA-SUM generation
We defined the LA-SUM as an unfold template of an
average LA mesh (Fig. 1c). The average mesh was
unfolded using a fast surface parameterization technique
developed for texture mapping [
]. With this mapping
method, a predefined unfold template was constructed where
the mitral valve annulus is constrained to a disk, the
boundary of each PV to circles, and the LA appendage
to an ellipse (see Fig. 1d). Circles in the unfold template
corresponding to the PVs were slightly offset to preserve
the proportions of the 3D average mesh (i.e., longer
distance to the mitral valve annulus along the septal wall
than along the lateral wall). To generate an LA-SUM, a
surface mesh (e.g., from EAM or CMR imaging) is first
semi-automatically pre-processed to define the mitral
Fig. 1 Input datasets and LA-SUM processing schematic. a, b Example
datasets from set A and set B showing local activation time measurements
from the coronary sinus (CS) and high right atrial (HRA), contact-force
measurements during ablation and post-ablation late gadolinium
enhancement. c–e The LA-SUM processing pipeline. An average mesh
was constructed from an average atlas image (c). The average mesh was
standardized and unfolded to fit a predefined template. The LA-SUM
transforms the mitral edge to an outer circle, each PV to a spaced circle
and the LAA to an ellipse (d). A case is processed by manually selecting
four seed points (one per main PV) for mesh standardization, mitral valve
clipping, and pulmonary vein clipping before the case data is projected
onto the average mesh using affine followed by elastic registration.
Finally, circumferential, longitudinal, and area coverage calculation is
performed for quantification (see text)
valve annulus [
] and the pulmonary veins are clipped
10 mm distal to the ostia. Next, the surface mesh is
registered to the LA average mesh before unfolding onto the
2D LA-SUM. Further details are given in the online
supplement. For each case, the LA-SUM was completed by
two independent observers to evaluate the robustness of
the technique to variations in the pre-processing steps.
Root mean square deviation (RMSD) is reported as a
measure of inter-observer variability.
To split the LA-SUM into clinically relevant regions, eight
LA regions (anterior, lateral, appendage, roof, posterior, mitral
isthmus, floor, and septum) were defined [
]. These regions
were marked on all 3D meshes from set A. An LA-SUM was
computed for each case, and a cumulative LA-SUM (all
patients, all regions) was visualized to define the regions in 2D
(Fig. 2a). The boundaries between LA regions on the
LA-SUM maps were optimized by consensus of two
electrophysiologists. The final regions were mapped back to the 3D
average mesh to test for consistency (Fig. 2c). Four quadrants
(Q1, Q2, Q3, and Q4) were also defined around each PV.
These quadrants were included in the SUM for the purpose
of computing the circumferential coverage of post-ablation
injury (see LA-SUM Applications, below). In total, there are
24 regions in the proposed LA-SUM.
2.3 LA-SUM applications
2.3.1 Lesion and contact force correlation
Using the defined SUM template, the relationship between
LGE and FTI was analyzed for cases in set B. To define areas
of enhancement from the LGE meshes, the intensity histogram
was normalized to a 16-bit window [
] from the intensity
values obtained from the LGE images. Subsequently, an
optimal threshold value was chosen per case [
] (50 ± 10% of
maximum intensity) and contours corresponding to the extent
of enhancement were overlaid onto the matching FTI
LA-SUM. For each LA-SUM region, the ablation coverage
(FTI > 100 gs) was correlated with the percentage of lesion
coverage (see below).
2.3.2 Percentage of lesion coverage
To quantify the extent of post-ablation lesion coverage
(defined by LGE CMR or EAM FTI), the LA-SUM was used to
compute three metrics: circumferential coverage, longitudinal
coverage, and area coverage (see Fig. 1e—quantification).
For circumferential coverage, the four quadrants
corresponding to each PV were extracted and sampled radially around the
from posterior to mitral annulus; region 8 = septum—medial border of
chamber between anterior and floor regions. In addition, four quadrants
around each PV were defined, numbered as follows: regions 9–12 =
LSPV quadrants Q1–Q4; regions 13–16 = LIPV quadrants Q1–Q4;
regions 17–20 = RSPV quadrants Q1–Q4; regions 21–24 = RIPV
quadrants Q1–Q4. The region definitions were mapped back to the 3D
average mesh to test for consistency (c). d Example LA-SUM
representations for a LAT map from set A and a post-ablation LGE
CMR scan from set B. e, f Intra-patient comparison of LA datasets is
demonstrated for two cases from set A (LAT during CS pacing and LAT
during HRA pacing) and two cases from set B (force-time integral during
ablation and post-ablation scar demonstrated by LGE CMR)
PV opening at one degree intervals. Circumferential coverage
was defined as the ratio of the number of sampling lines
crossing any lesion to the total number of sampling lines (n = 360).
Longitudinal coverage was evaluated on the roof and the
posterior walls by sampling 100 vertical lines along a horizontal
axis of each region. Longitudinal coverage was defined as the
ratio of the number of sampling lines crossing any lesion to the
total number of sampling lines (n = 100). Area coverage was
computed for all SUM regions and was defined as the ratio of
the area covered by a lesion to the total region area.
Figure 2a–c shows the LA-SUM template generated using set
A. Electrogram recording sites were ‘tagged’ with one of eight
regions on the native 3D shell before representing all set A
cases on a single LA-SUM (Fig. 2a). In doing so, LA-SUM
regions were defined using the boundaries between recording
sites to represent boundaries between LA regions. Figure 2b
shows these 8 LA regions with the addition of the 16 PV
quadrants (4 per vein). For validation, the defined LA-SUM
regions were projected back onto the average LA shell (Fig.
2c). Examples of LA-SUM representations created from 3D
LA maps representing LAT and LGE are shown on the left and
right of Fig. 2d, respectively.
Representative LA-SUM maps from set A and set B are
shown in Fig. 2e, f, respectively. In Fig. 2e, LA-SUM maps
displaying LAT are shown for two cases during CS pacing and
Fig. 3 Quantitative intra- and
inter-patient comparisons using
the LA-SUM. a–c Intra-patient
coverage of LA-SUM regions
during ablation (FTI > 100 gs) is
compared with lesion formation
assessed by LGE on post-ablation
CMR imaging, showing a weak
but significant correlation (a).
Examples of cases showing close
correlation (b) and weak
correlation (c) between FTI and
LGE on a region-by-region basis
are shown. d LA-SUM facilitates
demonstrated here for average
FTI applied in each WACA
quadrant for each vein during
HRA pacing. In contrast to 3D LA shells, the LA-SUM
displays activation times for the entire chamber in a single view
allowing propagation of activation to be seen. Inter-observer
differences between LA-SUM LAT maps were negligible
( C S - R M S D = 0 . 0 0 7 ± 0 . 0 0 5 m s ;
HRA-RMSD = 0.008 ± 0.010 ms), confirming that the
LASUM technique is robust to minor changes in the
semiautomatic mesh pre-processing steps. In Fig. 2f, correlation
between post-ablation CMR LGE and ablation FTI is shown
for two cases in set B (one case per row). On the left of Fig. 2f,
the LGE LA-SUM is shown, with black contours representing
the identified regions of enhancement. On the right, these
contours are overlaid in white on the FTI LA-SUM.
Interobserver differences between CMR-derived SUM maps were
also minimal (FTI-RMSD = 0.068 ± 0.063 gs;
LGERMSD = 0.031 ± 0.026 au).
The use of the LA-SUM for intra-patient comparisons is
demonstrated in Fig. 3a–c. Using the LA-SUM to quantify
region coverage by ablation and by enhancement on
post-ablation CMR revealed a weak but significant correlation
between FTI coverage and LGE coverage (R2 = 0.18,
P < 0.0001, Fig. 3a). Examples of cases showing close
correlation and weak correlation between FTI and LGE coverage
on a region-by-region basis are shown in Fig. 3b, c,
respectively. The use of LA-SUM for inter-patient comparisons is
demonstrated in Fig. 3d, where the median FTI applied to each
PV quadrant across all the cases in set B is represented.
Overall, there was no significant difference between the
median FTI applied at any of the quadrants (P = 0.5039) between
any of the patients.
This study developed, validated, and demonstrated the
application of a standardized 2D left atrial unfold mapping
technique (LA-SUM). The rationale behind developing the
LA-SUM representation was to provide a reference template
facilitating the comparison of different datasets, both within
patients and between individuals. Such unfolded visualization
has long been used in the ventricle owing to several
advantages: (1) it allows intra-patient comparison of multimodal
data in a single view; (2) it provides a common reference
space for inter-subject analysis; (3) data visualization does
not require user interaction (i.e., map manipulation); and (4)
unfold maps can be easily included in clinical reports.
The experiments on set A demonstrate the consistency of the
LA-SUM technique. By manually defining LA regions on each
3D LA surface, prior to LA-SUM processing, the final
LA-SUM representation of all cases in set A displayed the
position of each region without bias from the original geometry.
As can be seen from Fig. 2a, the final position of each region on
the SUM map was highly consistent between cases. Given the
variation in LA morphology seen in patients with atrial
], this robustness provides a unique method of comparing
data between LA subregions of different cases. Consistent with
their use for PVI procedures, the 3D LA shells in set A were
characterized by detailed PV anatomy and sometimes a
protrusion marking the position of the trans-septal puncture. Despite
these differences in mesh anatomy, LA-SUM representations
could be successfully computed for all cases.
Compared to traditional 3D LAT maps, LA-SUM LAT maps
have the advantage of allowing the observer to visualize the
activation of the entire chamber without requiring any user
interaction as demonstrated for two cases under HRA pacing and
CS pacing in Fig. 2e. Such LAT representation may be
particularly useful for the visualization of atrial tachycardia circuits,
where the entire mapped cycle length could be visualized on the
single disk of the SUM map. The advent of ultra-high resolution
mapping technologies leading to extremely detailed atrial maps
will be ideally suited to this application [
Datasets from set B were used to demonstrate the use of the
LA-SUM technique for performing intra- and inter-patient
comparisons. For example, overlying multimodal information
onto the LA-SUM facilitated comparison of LGE CMR
images with ablation contact force on the same coordinate
system. The data presented here show a weak but significant
relationship between FTI and LGE which is consistent with
prior working indicating that factors other than force (e.g.,
ablation power, catheter stability) are as important in the
success of lesion generation [
]. Although thresholding was
used in the present study to overlay datasets (e.g., white
lines in Fig. 2f), we have previously developed a tool (termed
dot mapping) for representing multiple scalar datasets in a
single spatial domain [
]. Combining dot mapping with the
LA-SUM would allow simultaneous visualization of multiple
pan-atrial arrhythmia substrate characterization modalities.
Numerous previous studies have performed regional
analysis of structural and electrical parameters in the LA [
and yet to date there is no standardized method of comparing
regions between patients. The LA-SUM provides a tool for
performing such inter-patient comparisons. For example, in
Fig. 3d, the LA-SUM was used to compare the average FTI
applied in each PV region between ten cases undergoing PVI.
By providing a reproducible method for LA regional
assessment, the LA-SUM could enable standardization of future
studies performing arrhythmia substrate characterization of
the left atrium.
The proposed LA-SUM template was designed for the most
common topological LA variant with four pulmonary veins
]). Modification of the template would be required
to support LA-SUM generation of five-vein or common ostia
This study developed an approach to compute a template
standardized unfold map of the left atrium. This approach is
applicable to multiple types of input data and displays a unified
holistic unfold for multimodal information. It also allows
computing metrics per region in an automatic manner. The
proposed standardized unfold map for the left atrium is
analogous to the bull’s eye plot for the left ventricle. To facilitate
use of this technique, code for generating the LA-SUM will be
made available in an online repository.
Funding This work was supported by the National Institute for Health
Research (NIHR) Biomedical Research Centre at Guy’s and St Thomas’
NHS Foundation Trust and King’s College London. The views expressed
here are those of the authors and not necessarily those of the NHS, the
NIHR, or the Department of Health. M.A. Zuluaga is funded by the
EPSRC (EP/H046410/1). C. Butakoff and O. Camara are funded by the
Seventh Framework Programme (FP7/2007-2013) under grant agreement
n° 611823 and by the Spanish Ministry of Economy and Competitiveness
Compliance with ethical standards
Conflict of interest None.
Open Access This article is distributed under the terms of the Creative
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license, and indicate if changes were made.
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