<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">WJCD</journal-id><journal-title-group><journal-title>World Journal of Cardiovascular Diseases</journal-title></journal-title-group><issn pub-type="epub">2164-5329</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/wjcd.2018.86027</article-id><article-id pub-id-type="publisher-id">WJCD-85219</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Medicine&amp;Healthcare</subject></subj-group></article-categories><title-group><article-title>
 
 
  Detection of Regional Wall Motion Abnormalities in Compressed Sensing Cardiac Cine Imaging
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Juliane</surname><given-names>Goebel</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Felix</surname><given-names>Nensa</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Haemi</surname><given-names>Schemuth</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Stefan</surname><given-names>Maderwald</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Harald</surname><given-names>H. Quick</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Thomas</surname><given-names>Schlosser</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Kai</surname><given-names>Nassenstein</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany</addr-line></aff><aff id="aff2"><addr-line>Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen, Germany</addr-line></aff><author-notes><corresp id="cor1">* E-mail:<email>juliane.goebel@uk-essen.de(JG)</email>;</corresp></author-notes><pub-date pub-type="epub"><day>11</day><month>06</month><year>2018</year></pub-date><volume>08</volume><issue>06</issue><fpage>277</fpage><lpage>287</lpage><history><date date-type="received"><day>20,</day>	<month>April</month>	<year>2018</year></date><date date-type="rev-recd"><day>9,</day>	<month>June</month>	<year>2018</year>	</date><date date-type="accepted"><day>12,</day>	<month>June</month>	<year>2018</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  Background:
   Recently faster cardiac magnetic resonance (CMR) cine sequences basing on k-t compressed sensing have been developed. <b>Purpose:</b> To compare two compressed sensing CMR sequences-one in breath-hold technique and one during free breathing—with the standard SSFP sequence with respect to regional left ventricular function assessment.<b> Material and Methods:</b> Left ventricular
   
  short-axis stacks
   
  of two compressed sensing sequences in breath-hold technique (sparse_HB) and during free breathing (sparse_FB; both
   
  spatial resolution, 1.8 
  &#215; 1.8 &#215; 8 mm<sup>3</sup>) and a standard SSFP cine sequence (spatial resolution, 1.9 &#215; 1.9 &#215; 8 mm<sup>3</sup>) were acquired in 50 patients on a 1.5
   
  T MR system. Regional wall motion abnormalities (RWMA) were rated qualitatively (normal/hypo-/a-/dyskinesia) by two experienced readers in consensus for all cardiac segments (
  American Heart Association’s 
  segment model) and sequences. RWMA detection rates were compared between sequences by kappa statistic.<b> Results:</b> In 13 patients
  ,
   RWMA were detected in at least one cardiac segment. The RWMA detection rates were similar between CMR sequences (hypokinesia, 7.2% to 7.9%;
   
  akinesia, 0.8% to 1.3%; dyskinesia 0.3% to 0.4%) and kappa statistics revealed an almost perfect agreement in RWMA detection between both sparse and the standard SSFP sequence (standard versus sparse_HB: kappa, 0.918, p value, &lt;0.001; standard versus sparse_FB: kappa, 0.868, p value, &lt;0.001).<b> Conclusion:</b> Compressed sensing cine CMR acquired during breath-hold or free-breathing allows reliable RWMA detection, thus, might alternatively be used in cine CMR for regional left ventricular function assessment.
 
</p></abstract><kwd-group><kwd>Cardiac Imaging Techniques</kwd><kwd> Cine Magnetic Resonance Imaging</kwd><kwd> Cardiac Muscle</kwd><kwd> Cardiac Volume</kwd><kwd> Myocardial Contraction</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Cardiac magnetic resonance imaging (CMR) is an established imaging tool in the diagnostic workup of patients with suspected heart disease and plays an important role in risk stratification (e.g. in coronary artery disease or myocarditis) and non-invasive therapy monitoring [<xref ref-type="bibr" rid="scirp.85219-ref1">1</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref2">2</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref3">3</xref>] . Due to continuous technical progress in CMR sequence design, hopefully the time consuming acquisition of standard breath-hold steady-state free precession (SSFP) cine sequences might be replaced by faster alternatives, which allow either a significant reduction in breath-hold times or even image acquisition during free breathing, which would be extremely helpful in patients with limited breath-hold capability. In this context, the recently developed k-t compressed sensing sequence technique with parallel imaging and iterative reconstruction seems very promising [<xref ref-type="bibr" rid="scirp.85219-ref4">4</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref5">5</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref6">6</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref7">7</xref>] . Provided that special conditions regarding image properties, aliasing artifacts, and image reconstruction are fulfilled, this technique allows a considerable acceleration of CMR data acquisition due to noticeable k-space under sampling [<xref ref-type="bibr" rid="scirp.85219-ref4">4</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref5">5</xref>] . Until now, several slightly different SSFP sequences basing on this new technical approach have been evaluated by different groups with the main focus on global left ventricular (LV) function [<xref ref-type="bibr" rid="scirp.85219-ref8">8</xref>] - [<xref ref-type="bibr" rid="scirp.85219-ref13">13</xref>] . Regarding global LV function, the overall consensus of these studies was that compressed sensing cine SSFP sequences are as reliable as conventional cine SSFP imaging. Despite the fact that regional wall motion abnormality (RWMA) detection is also of high clinical relevance in many settings (e.g. assessment of ischemic heart disease, high-dose dobutamine stress CMR, where an ischemia is defined as a stress-induced new or aggravated RWMA [<xref ref-type="bibr" rid="scirp.85219-ref14">14</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref15">15</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref16">16</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref17">17</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref18">18</xref>] ), only limited data exists concerning regional wall motion assessment by compressed sensing cine imaging.</p><p>Thus, the aim of the present study was to compare two different compressed sensing CMR sequences-one acquired in breath-hold technique, with reduced breath-hold times and one during free breathing―with the current standard SSFP sequence with the focus on regional left ventricular function assessment.</p></sec><sec id="s2"><title>2. Material and Methods</title><p>Prospective analysis and use of data was approved by the local ethic committee. All included patients gave written informed consent for CMR examination and study participation.</p><sec id="s2_1"><title>2.1. Cardiovascular Magnetic Resonance Imaging</title><p>All CMR scans were performed on a 1.5-Tesla system (Magnetom Aera, Siemens Healthcare, Erlangen, Germany). Three stacks of short-axis slices covering the complete left ventricle were acquired in every patient using the following sequences: [A] retrospectively ECG-gated, segmented cine steady-state free precession sequence in breath-hold technique (standard SSFP; TR: 44.54 ms; TE: 1.1 ms; matrix: 192 &#215; 156; FOV: 370 &#215; 301 mm<sup>2</sup>; flip angle: 59˚; 17 segments; 25 calculated phases; spatial resolution: 1.9 &#215; 1.9 &#215; 8 mm<sup>3</sup>; bandwidth: 930 Hz/px; median breath-hold time (for acquisition of all short-axis slices): 130 sec), [B, C] prospectively ECG-triggered segmented compressed sensing cine SSFP sequence in breath-hold technique (B, sparse_HB; median breath-hold time (for acquisition of all short-axis slices): 21 sec) and during free breathing (C, sparse_FB) (sparse_HBand sparse_FB: TR: 39,75 ms; TE: 1.1 ms; matrix: 224 &#215; 146; FOV: 400 &#215; 300 mm<sup>2</sup>; flip angle: 60˚; 15 segments; spatial resolution: 1.8 &#215; 1.8 &#215; 8 mm<sup>3</sup>; vendor provided sparse acceleration factors, A (defined as the acceleration factor in the central part of the k-space): 3 and B (defined as the acceleration factor in the k-space periphery): 14; number of iterations: 80; bandwidth: 893 Hz/px).</p></sec><sec id="s2_2"><title>2.2. Assessment of Regional Wall Motion Abnormalities and Left Ventricular Volumetry</title><p>Analysis for RWMA was performed in consensus by two experienced readers (CMR experience &gt; 12 years and &gt;6 years). Presence and severity of RWMA were evaluated visually and graded as “normal”, “hypokinesia”, “akinesia”, or “dyskinesia” in all CMR sequences and in all cardiac segments, except for segment 17 (in accordance to the American Heart Association’s segmental model) [<xref ref-type="bibr" rid="scirp.85219-ref14">14</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref19">19</xref>] . Thus, a total of 800 cardiac segments in each CMR sequence were analyzed (50 patients with 16 analyzed cardiac segments each).</p><p>Left ventricular volumetry was performed in all patients and CMR sequences by one reader (CMR experience &gt; 6 years) using the Argus software (Siemens Healthcare, Erlangen, Germany; employed standard values based upon [<xref ref-type="bibr" rid="scirp.85219-ref20">20</xref>] ). Because excellent inter-rater agreement for left ventricular volumes has been repeatedly reported for segmented compressed sensing cine SSFP sequences in breath-hold technique and during free breathing, we waived this subanalysis [<xref ref-type="bibr" rid="scirp.85219-ref10">10</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref11">11</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref13">13</xref>] . The papillary muscles and trabecullae were attributed to the ventricular cavity, and the most basal short-axis slice to be included into volumetry was defined by having at least 270˚ of the chamber circumference surrounded by visible myocardium [<xref ref-type="bibr" rid="scirp.85219-ref21">21</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref22">22</xref>] .</p></sec><sec id="s2_3"><title>2.3. Statistical Analysis</title><p>For statistical analysis MedCalc (version 12.3.0.0, MedCalc Software, Mariakerke, Belgium) and SPSS software package (version 19.0, IBM, Armonk, NY, USA) were used. Testing for normal distribution was performed by D’Agostino- Pearson test. Normally distributed data are presented as mean &#177; standard deviation, otherwise medians and interquartile ranges are given. To analyze for differences in RWMA detection between the three employed CMR sequences kappa statistic was performed and interpreted as proposed by Landis and Koch [<xref ref-type="bibr" rid="scirp.85219-ref23">23</xref>] . Comparison of volumetric data between the CMR sequences was done by Wilcox on test, and inter-rater agreement was assessed by Bland-Altman analysis. A p value less than 0.05 was considered statistically significant.</p></sec></sec><sec id="s3"><title>3. Results</title><sec id="s3_1"><title>3.1. Patients</title><p>Fifty consecutive unselected patients (17 female, 33 male) referred for clinical CMR examination and willed to participate in the present study were examined. Patients were referred to CMR for suspected myocarditis (n = 14), pericarditis (n = 1), cardiac infarction (n = 5), cardiomyopathy (n = 12), congenital heart disease (n = 2), cardiac tumor (n = 1), or unclear reduction of heart output or dysrhythmia (n = 15). Mean patient age was 41.5 &#177; 20.2 years (range: 8 - 77 years). Median weight was 75 kg (interquartile range: 27 kg; range: 30 - 152 kg), median height 175 cm (interquartile range: 12 cm; range: 130 - 195 cm), and median body mass index 24.8 &#177; 7.2 kg/m<sup>2</sup> (range: 13.1 - 51.4kg/m<sup>2</sup>). The median heart rate was 68 beats/minute (interquartile range: 16 beats/ minute; range: 46 - 113 beats/minute).</p></sec><sec id="s3_2"><title>3.2. Regional Wall Motion Abnormalities (RWMA)</title><p>In all 50 patients well analyzable data sets of all three CMR sequences were acquired (<xref ref-type="fig" rid="fig1">Figure 1</xref> and <xref ref-type="fig" rid="fig2">Figure 2</xref>). In 37 patients no RWMA was detected. In 13 patients RWMA was found in at least one cardiac segment (<xref ref-type="fig" rid="fig2">Figure 2</xref>). Comparison of the RWMA detection rate between CMR sequences showed quite equal detection rates ranging from 7.2% to 7.9% for hypokinesia, 0.8% to 1.3% for akinesia, and 0.3% to 0.4% for dyskinesia (<xref ref-type="table" rid="table1">Table 1</xref>). Kappa statistics revealed an almost perfect agreement in RWMA detection between standard SSFP and sparse_HB (Cohens kappa, 0.918, p value, &lt;0.001), between standard SSFP and sparse_FB (Cohens kappa, 0.868, p value, &lt;0.001), and between sparse_HBand sparse_FB (Cohens kappa, 0.880, p value, &lt;0.001).</p></sec><sec id="s3_3"><title>3.3. Left Ventricular Volumetry</title><p>Left ventricular volumetric values of all three CMR sequences are presented in <xref ref-type="table" rid="table2">Table 2</xref>. Comparing standard SSFP and sparse_HB, small, but significant median</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Detection rates of regional wall motion abnormalities given in absolute numbers and percent values (in brackets) for the three CMR sequences</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >normokinesia</th><th align="center" valign="middle" >hypokinesia</th><th align="center" valign="middle" >akinesia</th><th align="center" valign="middle" >dyskinesia</th></tr></thead><tr><td align="center" valign="middle" >standard SSFP</td><td align="center" valign="middle" >729 (91.1%)</td><td align="center" valign="middle" >63 (7.9%)</td><td align="center" valign="middle" >6 (0.8%)</td><td align="center" valign="middle" >2 (0.3%)</td></tr><tr><td align="center" valign="middle" >sparse_HB</td><td align="center" valign="middle" >725 (90.6%)</td><td align="center" valign="middle" >62 (7.8%)</td><td align="center" valign="middle" >10 (1.3%)</td><td align="center" valign="middle" >3 (0.4%)</td></tr><tr><td align="center" valign="middle" >sparse_FB</td><td align="center" valign="middle" >731 (91.4%)</td><td align="center" valign="middle" >58 (7.2%)</td><td align="center" valign="middle" >9 (1.1%)</td><td align="center" valign="middle" >2 (0.3%)</td></tr></tbody></table></table-wrap><p>SSFP, steady-state free precession sequence; sparse, compressed sensing sequence; HB, breath-hold; FB, free breathing.</p><p>differences were found for EDV (difference of median, 8 ml; p value &lt; 0.001), SV (difference of median, 8 ml; p value &lt; 0.001), and EF (difference of median, 1%; p value, 0.016), but not for ESV (p value, 0.198). Comparing standard SSFP and sparse_FB, small, but significant median differences were found for ESV (difference of median, 4 ml; p value &lt; 0.001), SV (difference of median, 4ml; p value, 0.004), and EF (difference of median, 2%; p value&lt; 0.001), but not for EDV (p value, 0.817). These findings were confirmed by the Bland-Altman analysis (<xref ref-type="table" rid="table3">Table 3</xref>, <xref ref-type="fig" rid="fig3">Figure 3</xref>), where an overall good agreement in volumetric values between the standard SSFP sequence and both sparse sequences was found.</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Volumetric values (presented as median and interquartile range (in brackets)) of all 50 investigated patients comparing the three CMR sequences</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >standard SSFP</th><th align="center" valign="middle" >sparse_HB</th><th align="center" valign="middle" >sparse_FB</th></tr></thead><tr><td align="center" valign="middle" >EDV [ml]</td><td align="center" valign="middle" >128 (43)</td><td align="center" valign="middle" >120 (39)</td><td align="center" valign="middle" >127 (38)</td></tr><tr><td align="center" valign="middle" >ESV [ml]</td><td align="center" valign="middle" >45 (33)</td><td align="center" valign="middle" >45 (25)</td><td align="center" valign="middle" >49 (24)</td></tr><tr><td align="center" valign="middle" >SV [ml]</td><td align="center" valign="middle" >76 (20)</td><td align="center" valign="middle" >68 (20)</td><td align="center" valign="middle" >72 (26)</td></tr><tr><td align="center" valign="middle" >EF [%]</td><td align="center" valign="middle" >61 (11)</td><td align="center" valign="middle" >60 (10)</td><td align="center" valign="middle" >59 (11)</td></tr></tbody></table></table-wrap><p>SSFP, steady-state free precession sequence; sparse, compressed sensing sequence; HB, breath-hold; FB, free breathing; EDV, end-diastolic volume; ESV, end-systolic volume; SV, stroke volume; EF, ejection fraction.</p><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Results of the Bland-Altman analysis comparing the volumetric values of the standard SSFP sequence with both sparse sequences</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >standard SSFP vs.</th><th align="center" valign="middle" >bias</th><th align="center" valign="middle" >SD</th><th align="center" valign="middle" >95%-CI</th></tr></thead><tr><td align="center" valign="middle"  rowspan="2"  >EDV [ml]</td><td align="center" valign="middle" >sparse_HB</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >−10, 24</td></tr><tr><td align="center" valign="middle" >sparse_FB</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >−19, 20</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >ESV [ml]</td><td align="center" valign="middle" >sparse_HB</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >−10, 12</td></tr><tr><td align="center" valign="middle" >sparse_FB</td><td align="center" valign="middle" >−4</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >−18, 9</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >SV [ml]</td><td align="center" valign="middle" >sparse_HB</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >−10, 22</td></tr><tr><td align="center" valign="middle" >sparse_FB</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >−15, 24</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >EF [%]</td><td align="center" valign="middle" >sparse_HB</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >−6, 10</td></tr><tr><td align="center" valign="middle" >sparse_FB</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >−6, 13</td></tr></tbody></table></table-wrap><p>SSFP, steady-state free precession sequence; sparse, compressed sensing cine sequence; HB, breath-hold; FB, free breathing; SD, standard deviation; 95%-CI, 95%-confidence interval; EDV, end-diastolic volume; ESV, end-systolic volume; SV, stroke volume; EF, ejection fraction.</p></sec></sec><sec id="s4"><title>4. Discussion</title><p>In this study we could demonstrate for the first time that not only our compressed sensing CMR sequence acquired in breath-hold technique, but also our compressed sensing CMR sequence during free breathing allowed reliable regional left ventricular function assessment. This result is in line with the findings of Allen et al. who compared an iteratively reconstructed k-t under sampled breath-hold SENSE cine sequence with a conventional breath-hold SSFP cine sequence based on GRAPPA (acceleration factor, 2) with respect to RWMA detection in 20 patients and in 9 healthy volunteers [<xref ref-type="bibr" rid="scirp.85219-ref7">7</xref>] . They rated the RWMA qualitatively as dichotomous variable (RWMA present or absent) and found a good to excellent agreement between both CMR sequences with Cohens kappa ranging from 0.61 to 0.77. Similar results were described by Lin et al. who investigated the detect ability of RWMA using a compressed sensing CMR sequence with high spatial and temporal resolution in breath-hold technique (acceleration factor: 8; temporal resolution: 30 ms; in-plane resolution: 1.5 &#215; 1.5 mm<sup>2</sup>) in comparison to a conventional SSFP sequence (acceleration factor: 2; temporal resolution: 30 ms; in plane resolution 1.25 &#215; 1.25 mm<sup>2</sup>) in 50 patients [<xref ref-type="bibr" rid="scirp.85219-ref24">24</xref>] . They evaluated the RWMA quantitatively by use of the dedicated post processing software cvi42 (Circle Cardiovascular Imaging, Canada) and reported a strong correlation for RWMA detection between both sequences (Pearson correlation: r, 0.87; p value &lt; 0.001), thus, stated that their investigated compressed sensing sequence might replace the conventional time-consuming multiple breath-hold sequences. Based on our results, we totally agree with Lin et al. and believe that the faster compressed sensing CMR sequences, which were proven to reliable detect RWMA, have the potential to replace standard cine SSFP imaging in clinical routine for the assessment of regional and global LV function. Moreover, compressed sensing cine imaging is extremely interesting for high-dose dobutamine stress CMR. The latter is often hampered by motion artifacts caused by dobutamine induced tachycardia. And these motion artifacts might considerably be reduced by the faster CMR data acquisition of our tested compressed sensing sequences. This anticipated improvement by use of compressed sensing sequences in high-dose dobutamine stress CMR should be investigated in further studies.</p><p>Beyond the discussed studies, no other compressed sensing CMR sequence study dealt with RWMA detection, and to the best of our knowledge our study is the first investigating a compressed sensing CMR sequence during free breathing with respect to RWMA detection. And given that many patients undergoing CMR suffer from shortness of breath, CMR data acquisition during free breathing improves not only CMR acceptance by the patient but also patient’s comfort.</p><p>Regarding the global left ventricular function, only small, not relevant differences in left ventricular values were found between the standard SSFP sequence and both compressed sensing CMR sequences. For the sparse_HB sequence slightly lower EDV, SV, and EF values were found which might be caused by an insufficient capture of the end-diastole [<xref ref-type="bibr" rid="scirp.85219-ref10">10</xref>] . For the sparse_FB sequences lightly higher ESV and consecutively lower EF values were found. But overall a sufficient agreement between the standard SSFP sequence and both sparse sequences was found which is in accordance to recently published studies where a sufficient to excellent agreement between the investigated sparse and reference sequences were reported [<xref ref-type="bibr" rid="scirp.85219-ref10">10</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.85219-ref13">13</xref>] .</p><p>Our study is not without limitations. First, we analyzed the RWMA exclusively visually. Although this is common practice, accuracy might benefit from a quantitative RWMA analysis. Second, only a limited number of patients/cardiac segments with RWMA were included, which was due to our unselected patient cohort.</p></sec><sec id="s5"><title>5. Conclusion</title><p>In conclusion, compressed sensing cine imaging of the left ventricle acquired either during breath-hold or during free breathing allows the reliable detection of regional wall motion abnormalities. Thus, these fast cine sequences can alternatively be used for the assessment of LV function.</p></sec><sec id="s6"><title>Acknowledgements</title><p>The authors thank Marcel Gratz for his technical assistance and fruitful discussions.</p></sec><sec id="s7"><title>Conflict of Interest</title><p>The SPARSE-SENSE sequence prototype was provided by Siemens Healthcare GmbH, Erlangen, Germany. The authors declare that there is no conflict of interest to this article.</p></sec><sec id="s8"><title>Cite this paper</title><p>Goebel, J., Nensa, F., Schemuth, H., Maderwald, S., Quick, H.H., Schlosser, T. and Nassenstein, K. (2018) Detection of Regional Wall Motion Abnormalities in Compressed Sensing Cardiac Cine Imaging. World Journal of Cardiovascular Diseases, 8, 277-287. https://doi.org/10.4236/wjcd.2018.86027</p></sec></body><back><ref-list><title>References</title><ref id="scirp.85219-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Grothues, F., Smith, G.C., Moon, J.C., Bellenger, N.G., Collins, P., Klein, H.U. and Pennell, D.J. (2002) Comparison of Interstudy Reproducibility of Cardiovascular Magnetic Resonance with Two-Dimensional Echocardiography in Normal Subjects and in Patients with Heart Failure or Left Ventricular Hypertrophy. 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