Skip to main content
Download PDF
  • Research article
  • Open access
  • Published:

Current T1 and T2 mapping techniques applied with simple thresholds cannot discriminate acute from chronic myocadial infarction on an individual patient basis: a pilot study

BMC Medical Imaging volume 16, Article number: 35 (2016) Cite this article

Abstract

Background

Studying T1- and T2-mapping for discrimination of acute from chronic myocardial infarction (AMI, CMI).

Methods

Eight patients with AMI underwent CMR at 3 T acutely and after >3 months. Imaging techniques included: T2-weighted imaging, late enhancement (LGE), T2-mapping, native and post-contrast T1-mapping. Myocardial T2- and T1-relaxation times were determined for every voxel. Abnormal voxels as defined by having T2- and T1-values beyond a predefined threshold (T2 > 50 ms, native T1 > 1250 ms and post-contrast T1 < 350 ms) were highlighted and compared with LGE as the reference.

Results

Abnormal T2-relaxation times were present in the voxels with AMI (=> delete acute infarction; unfortunately this is not possible in your web interface) acute infarction only in half of the subjects. Abnormal T2-values were also present in subjects with CMI, thereby matching the chronically infarcted territory in some. Abnormal native T1 times were present in voxels with AMI in 5/8 subjects, but also remote from the infarcted territory in four. In CMI, abnormal native T1 values corresponded with infarcted voxels, but were also abnormal remote from the infarcted territory. Voxels with abnormal post-contrast T1-relaxation times agreed well with LGE in AMI and CMI.

Conclusions

In this pilot-study, T2- and T1-mapping with simple thresholds did not facilitate the discrimination of AMI and CMI.

Peer Review reports

Background

Cardiovascular magnetic resonance enables myocardial tissue characterization by combining native and contrast-enhanced techniques with differences in T2- and T1-weighting. Native T2-weighted imaging has been reported to detect myocardial edema [1, 2], and T1-weighted late Gadolinium enhancement imaging (LGE) has been established to show necrosis and fibrosis. Recent studies demonstrated that the use of these techniques allows the differentiation of acute from chronic myocardial infarction (AMI, CMI) [3]. However, there is an ongoing controversial debate about the technical limitations and the pathophysiologic background of conventional T2-weighted edema imaging [4, 5]. Recently, myocardial T1- and T2-mapping were introduced to quantify the T1- and T2-relaxation times, which may be superior to the semiquantitative or qualitative image assessment used with conventional T2-weighted imaging [6–8]. For patients with AMI, prolonged native T2- and T1-relaxation times as well as decreased post-contrast T1-relaxation times were reported for the infarcted areas [9–12]. In patients with CMI, increased native and decreased post-contrast T1-relaxation times were reported [12]. However, whether the utilization of T2- and T1-mapping helps to differentiate AMI and CMI in the individual patient has not been examined in detail. We hypothesized that applying T1- and T2-mapping with simple thresholds based on reference values from healthy controls will discriminate AMI and CMI on an individual patient basis.

Methods

Study population

Eight male patients (mean age 56 ± 13 years) underwent CMR within 9 ± 3 days (range 5-14 <space>days) after acute ST-segment elevation myocardial infarction and in a chronic state 139 ± 50 days (range 92–210 days) after the acute event. Repeated troponin measurements were not performed. But all patients remained clinically without onset of new cardiovascular symptoms or any cardiovascular event between both CMR scans. Patients’ characteristics are described in Table 1. Note that patient two and four have the lowest release of myocardial enzymes but the lowest ejection fraction. In patient 2, this is attributable to a preexisting three-vessel disease with prior inferior infarction. In patient four, left-to-left collaterals might have compensated the cellular damage during LAD-occlusion. The results were compared to previously published T1- and T2-relaxation times in healthy controls [8].

Table 1 Patients’ characteristics at acute presentation
Full size table

CMR examination

All CMR examinations were performed with a 3 T MR system (Magnetom Verio, Siemens Healthcare, Erlangen, Germany). The protocol was identical for patients and healthy controls. An integrated body RF coil was employed for RF transmission and a 32-channel cardiac RF coil for signal reception if not otherwise stated. ECG was used for cardiac gating/triggering.

Cine imaging

Steady-state free-precession (SSFP) 2D cine images were obtained during repeated breath-holds in three long axes and in a stack of short axes (SAX) covering the left ventricle (LV) to assess wall motion and for cardiac chamber quantification. Imaging parameters were as reported recently [8].

T2-weighted imaging

Data were acquired in basal, mid-ventricular, and apical SAX planes in end-diastole using a breath-hold, black-blood, T2-weighted triple inversion recovery fast-spin-echo based technique: Imaging parameters were: repetition time = 2 × R-R-interval; TE = 43 ms; inversion time for fat (TIfat) = 170 ms, FOV = (340×255)mm2, matrix = 256×192, slice thickness = 10 mm, acquisition voxel size 1.3 × 1.3 × 10 mm3, BW = 235Hz/px, The integrated body RF coil was used for signal transmission and reception.

T2-mapping

Data were acquired in basal, mid-ventricular, and apical SAX planes using a T2-prepared single-shot SSFP technique [6] as described recently [8]. Three SSFP images with different T2 preparation times were acquired in end-diastole within a single breath-hold. Imaging parameters were: TR = 2.4 ms, TE = 1 ms, FA = 70°, FOV = (340x278) mm2, matrix = 176×144, slice thickness = 6 mm, acquisition voxel size 1.9 × 1.9 × 6 mm3, BW = 1093Hz/px, GRAPPA acceleration factor R = 2. Images were motion corrected and a pixel-wise myocardial T2-map was generated. The principal accuracy of this technique has been demonstrated in previous phantom experiments [6].

T1-mapping

Data were acquired in basal, mid- ventricular, and apical SAX planes before and after administration of 0.2 mmol/kg i.v. gadobutrol (Gadovist®, Bayer Healthcare Germany). The acquisition of the post-contrast T1-maps was started in every examination exactly 10 minutes after gadobutrol administration, ensured by a countdown and always beginning with the basal slice. Data were obtained in end-diastole using a cardiac-gated, SSFP-based Modified Look-Locker Inversion Recovery (MOLLI) technique [7, 8]. Imaging parameters were: TR = 2.6–2.7 ms, TE = 1.0–1.1 ms, FA = 35°, FOV = (270 × 360) mm2, matrix = 156 × 208 to 168 × 224, slice thickness = 6 mm, acquisition voxel size 1.6–1.7 × 1.6–1.7 × 6 mm3, BW = 1045-1028Hz/px, GRAPPA acceleration factor 2. The hypersec adiabatic inversion pulse achieved an inversion factor of about -0.925. To generate a pixel-wise myocardial T1-map, single-shot SSFP images were acquired at different inversion times (pattern 3-3-5) and registered prior to a non-linear least-square curve fitting. The principal accuracy of this technique has been demonstrated in previous phantom experiments [7]. The heart rate of each subject during the MOLLI acquisition in the acute and chronic state was as follows: patient 1:59/62 beats per minute (bpm); patient 2: 83/62 bpm; patient 3: 56/55 bpm; patient 4: 51/51 bpm; patient 5: 77/65 bpm; patient 6: 62/62 bpm; patient 7: 51/50 bpm; patient 8: 57/66 bpm.

LGE imaging (LGE)

LGE imaging was performed 15 min after the administration of gadobutrol in the same planes as SSFP CINE imaging using a segmented inversion-recovery gradient-echo sequence. Imaging settings were as reported recently, with an acquisition voxel size 1.4 × 1.6 × 6 mm3 [8].

Image analysis

Defining the myocardium within the maps was done using CMR42 (Circle Cardiovascular Imaging, Calgary, Canada) as previously described [8]. Much attention was invested to manually draw the endocardial and epicardial contours as accurate as possible to omit the inclusion of blood or epicardial fat.

Based on the 95 % tolerance interval of the T2- and T1-relaxation times from a previous study in healthy controls [8], thresholds that discriminate normal from abnormal T1 and T2 were defined. The cut-off for abnormal T2-times was >50 ms, native T1 > 1250 ms and post-contrast T1 < 350 ms. All myocardial pixels that were abnormal based on these thresholds were automatically highlighted in color in the corresponding map. The distribution of abnormal pixels was correlated with the LGE, which was regarded as the reference for the localization and extent of the infarct.

Phantom experiments

Phantom experiments were done to evaluate the accuracy of the T2- and T1-mapping method, using the same MR scanner and coil as for the in-vivo exams. An agar-based phantom representing a range of T1 and T2 times was used. The T1-values were verified using an inversion recovery sequence with acquisition matrix 256x256, TR 15 s, 1 line/inversion, 90° FLASH readout, T1 range 200 ms–1090 ms. T1 values were calculated using a non-linear least square three-parameter fit. The T2-values were verified using a multi-echo spin echo (MESE) approach with matrix 256×256, TR 15 s, 1 segment, T2-range 16–235 ms. T2 values were calculated using a mono-exponential least square fit. For comparison, the T2- and T1-mappings technique as described for the in-vivo-measurements were applied. All phantom studies were performed with a simulated heart rate of 60 beats per minute. The signal-to-noise ratio (SNR) was estimated as the signal intensity from a manually drawn region of interest within the corresponding compartment of the phantom and the standard deviation of the signal intensity from a region of interest in the background. For T1, the last image of the series was used, for T2 the first.

Results

Phantom experiments

The results of the phantom experiments are shown in Table 2. They show that the applied mapping techniques provide estimates of the T1- and T2-relaxation times close to the reference technique, with MOLLI underestimating the T1-times. This finding is in concordance with previous studies that tested the same techniques in phantom experiments [6, 7].

Table 2 Relaxation times (in ms and ± SD) and estimates of the signal-to-noise ratio (SNR) of the phantom experiments
Full size table

In-vivo-measurements

All patients had evidence of AMI using LGE and T2-weighted imaging during the initial scan. Figure 1 provides images of the various imaging techniques for all subjects. Note that patient #2 had an old inferior infarction (red asterisk) but actually presented with LAD occlusion. Figure 2a and b provides the T2- and T1-maps for each patient with all myocardial pixels that were beyond the predefined threshold highlighted in color. The absolute T2- and T1-relaxation times for every subject and every myocardial segment are given in Table 3.

Fig. 1
figure 1

Representative images obtained with T2-weighted imaging, late enhancement (LGE), T2-map, native T1-map and post-contrast T1-map for each patient. The order of the patients corresponds to Table 1. The red arrows in the LGE images highlight the infarct region. Note that patient #2 had an old inferior infarction (red asterisk) but actually presented with LAD occlusion. Patient five had microvascular obstruction with hemorrhage (white arrow)

Full size image
Fig. 2
figure 2

a and b. Thresholds that discriminate normal from abnormal T1 and T2 relaxation times for every myocardial pixel were defined based on reference T2-and T1-values from healthy controls. These thresholds were applied on the T2- and T1-maps so that all abnormal pixels in the myocardium (between the red and green contour) that were outside the normal range became highlighted in a color (blue in T2-map, brown in T1-maps). The red arrows in the LGE images highlight the infarct region. Note that patient #2 had an old inferior infarction (red asterisk) but actually presented with LAD occlusion. Patient 5 had microvascular obstruction with hemorrhage (white arrow). a = subjects 1-4; b = subjects 5-8

Full size image
Table 3 The T2-and T1-relaxation times for each patient (#1-8) and each myocardial segment (Sg. 1-16)
Full size table

Only in half of the subjects with AMI, abnormal T2-relaxation times corresponded well with the infarcted pixels as defined by LGE [subjects 1–3, 6]. In the others [subjects 4, 5, 7, 8], pixels with T2-values higher than the normal range were present, but did not match with the infarcted territory as defined clinically and by LGE. In CMI (where no increase of the T2-relaxation time was expected), pixels with T2-values higher than the normal range were present in all subjects. In some of them, these pixels matched with the chronically infarcted territory [subjects 1–3, 6].

Similarly, abnormal native T1 times corresponded with acutely infarcted pixels in five out of eight subjects [subjects 1, 3, 6–8] in AMI, but were also present remote from the infarcted territory [subjects 4–6, 8]. In CMI, again abnormal native T1 values corresponded with infarcted pixels in most of the subjects [subjects 1–3, 5–8], but native T1 vales were also abnormal remote from the infarcted territory [subjects 3, 4, 6–8]. Pixels with abnormal post-contrast T1-relaxation times matched very well with LGE in all subjects both in AMI and CMI.

Discussion

Several reports described differences of the T1- and T2-relaxation times between infarcted myocardial segments and remote myocardium [10, 11]. It seems easy to reproduce areas of myocardial infarction using T2- or T1-maps if the localization of myocardial infarction is known. However, if the investigator is blinded to any clinical information, the discrimination of normal from abnormal myocardium as well as acutely from chronically injured myocardium solely based on T2- and T1-maps is challenging, as demonstrated in the present case series.

The observed distribution of abnormal and normal relaxation times did not match closely with the extent of the myocardial lesion as defined by LGE, particularly in the T2-maps and the native T1-maps. In CMI, pixels with elevated T2-value that would indicate edema appeared in the myocardium. And both in AMI and CMI, pixels with abnormal T1- and T2-values appeared also in the remote myocardium, which is supposed to have values widely within the normal range.

This mismatch between the results of the thresholding and the expected distribution of T2- and T1-relaxation times within the myocardium may be attributed to several factors:

  1. i.)

    A challenge of this mapping approach is the inter-individual scatter of myocardial T2- and T1-relaxation times that can be large in relation to the small difference between normal and abnormal myocardium [8]: The normal T1-value in healthy controls in the midventricular portion of the LV was reported to range from 1005 ms to 1296 ms at our institution and other sites report mean values of 1169 ± 73 ms mixed standard deviation [8, 13]. On the other hand, some authors reported a mean native T1-value of 1257 ± 97 ms for acutely infarcted segments compared to 1196 ± 56 ms for normal unaffected segments in the same subject [10]. Similarly, the normal T2-values in healthy controls ranged from 38 to 59 ms at 3 T and 46 to 69 ms in a study at 1.5 T [8, 14]. On the other hand, a T2 value of 60 ms has been reported as an adequate cutoff to determine active myocarditis [15]. Therefore, using one simple threshold based on normal values with a large scatter is probably imperfect for the individual subject. For example, in a person with T1-values in the lower range of the reference, the T1-values may still be within the normal range even after an infarct-related increase of 150 ms. This concept certainly needs further analysis in studies with larger samples. The large normal range is presumably attributable to physiological variations as well as to many other influencing factors like a potential heart-rate dependency of some acquisition methods and partial volume effects as outlined below. A detailed description of factors influencing the precision and accuracy of T1-measurements is available elsewhere [16]. In future, new ways of image post-processing may correct for some of these influencing factors, as recently demonstrated by Xanthis et al. [17]. An alternative approach to analyze maps - instead of defining thresholds based on the relaxation time - maybe the analysis based on the signal intensity. Kali et al. recently studied the use of native T1-maps in CMI. CMI was defined as using the mean ±5 standard deviation criterion relative to the respective reference regions of interest. Using this approach, native T1-maps and LGE images showed a close agreement to determine regions with CMI [18].

  2. ii.)

    Another aspect is the influence of partial volume. Pixels that include blood or epicardial fat quickly reach pathologic T2- and T1-values and are misleadingly classified as abnormal. Even though all attempts were made to minimize this error by drawing the contours exactly within the compact myocardium, a significant influence of partial volume effects still has to be assumed. Higher spatial resolution may solve this problem in the future, and single pixels with abnormal values located at the edge of the myocardium have to be interpreted with caution.

  3. iii.)

    In this case series microvascular obstruction was detected by LGE images in only one subject, therefore it does not explain the frequent mismatch between the thresholding and the expected distribution of abnormal T2- and T1-values. But generally, both T2- and T1-maps have been reported to be affected by microvascular obstruction leading to “hypoenhancement” within the “hyperenhanced” acute infarction [19]. Therefore, if large enough, microvascular obstruction may contribute to an inaccurate determination of the infarct area on T2- and T1-maps.

Limitations

The heart rate can influence T1-values by affecting the relaxation between the MOLLI segments. In this study, the heart rate ranged from 50 to 83 bpm. Together with the small sample size (n = 8), these may be the major factors for data overlapping. Using a different mapping sequences with less heart-rate sensitivity, such as the 5(3 s)3 MOLLI variant, could have resulted in an improved performance of T1-mapping [16]. A limitation of the phantom experiments is that SNR has only been estimated, because no correction for multi-element coils has been performed [20, 21].

Conclusions

This pilot study demonstrated that T2- and T1-maps with a simple threshold-based analysis did not facilitate the detection of myocardial infarction and the discrimination of AMI and CMI in the individual patient. Despite all enthusiasm for myocardial mapping, improvements in the technology as well as additional concepts for discriminating normal from abnormal myocardium may be necessary.

Ethics approval and consent to participate

Informed consent was obtained from each patient and the study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki as reflected in a priori approval by the institution’s human research committee (Charité Medical Faculty, EA2/077/10).

Consent for publication

Not applicable.

Availability of data and materials

The datasets supporting the conclusions of this article, including images, contours and databases, are stored on the institutional file server (smb://fs-cmrt.ecrc-berlin.com). The data will not be shared publicly at the current stage, as this study is part of a multi-element project that is still ongoing. Of course, data will be shared on request.

Abbreviations

AMI:

acute myocardial infarction

CMI:

chronic myocardial infarction

LGE:

late Gadolinium enhancement

LV:

left ventricle

References

  1. Eitel I, Friedrich MG. T2-weighted cardiovascular magnetic resonance in acute cardiac disease. J Cardiovasc Magn Reson. 2011;13:13.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Fernandez-Jimenez R, Sanchez-Gonzalez J, Aguero J, Garcia-Prieto J, Lopez-Martin GJ, Garcia-Ruiz JM, et al. Myocardial edema after ischemia/reperfusion is not stable and follows a bimodal pattern: imaging and histological tissue characterization. J Am Coll Cardiol. 2015;65:315–23.

    Article  PubMed  Google Scholar 

  3. Abdel-Aty H, Zagrosek A, Schulz-Menger J, Taylor AJ, Messroghli D, Kumar A, et al. Delayed enhancement and T2-weighted cardiovascular magnetic resonance imaging differentiate acute from chronic myocardial infarction. Circulation. 2004;109:2411–6.

    Article  PubMed  Google Scholar 

  4. Kim HW, Van Assche L, Jennings RB, Wince WB, Jensen CJ, Rehwald WG, et al. Relationship of T2-Weighted MRI Myocardial Hyperintensity and the Ischemic Area-At-Risk. Circ Res. 2015;117:254–65.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Nordlund D, Klug G, Heiberg E, Koul S, Larsen TH, Hoffmann P et al. Multi-vendor, multicentre comparison of contrast-enhanced SSFP and T2-STIR CMR for determining myocardium at risk in ST-elevation myocardial infarction. Eur Heart J Cardiovasc Imaging. 2016. Epub ahead of print.

  6. Giri S, Chung YC, Merchant A, Mihai G, Rajagopalan S, Raman SV, et al. T2 quantification for improved detection of myocardial edema. J Cardiovasc Magn Reson. 2009;11:56.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Messroghli DR, Radjenovic A, Kozerke S, Higgins DM, Sivananthan MU, Ridgway JP. Modified Look-Locker inversion recovery (MOLLI) for high-resolution T1 mapping of the heart. Magn Reson Med. 2004;52:141–6.

    Article  PubMed  Google Scholar 

  8. von Knobelsdorff-Brenkenhoff F, Prothmann M, Dieringer MA, Wassmuth R, Greiser A, Schwenke C, et al. Myocardial T1 and T2 mapping at 3 T: reference values, influencing factors and implications. J Cardiovasc Magn Reson. 2013;15:53.

    Article  Google Scholar 

  9. Messroghli DR, Niendorf T, Schulz-Menger J, Dietz R, Friedrich MG. T1 mapping in patients with acute myocardial infarction. J Cardiovasc Magn Reson. 2003;5:353–9.

    Article  PubMed  Google Scholar 

  10. Dall’Armellina E, Piechnik SK, Ferreira VM, Si QL, Robson MD, Francis JM, et al. Cardiovascular magnetic resonance by non contrast T1-mapping allows assessment of severity of injury in acute myocardial infarction. J Cardiovasc Magn Reson. 2012;14:15.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Verhaert D, Thavendiranathan P, Giri S, Mihai G, Rajagopalan S, Simonetti OP, et al. Direct t2 quantification of myocardial edema in acute ischemic injury. JACC Cardiovasc Imaging. 2011;4:269–78.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Messroghli DR, Walters K, Plein S, Sparrow P, Friedrich MG, Ridgway JP, et al. Myocardial T1 mapping: application to patients with acute and chronic myocardial infarction. Magn Reson Med. 2007;58:34–40.

    Article  PubMed  Google Scholar 

  13. Piechnik SK, Ferreira VM, Dall’Armellina E, Cochlin LE, Greiser A, Neubauer S, et al. Shortened Modified Look-Locker Inversion recovery (ShMOLLI) for clinical myocardial T1-mapping at 1.5 and 3 T within a 9 heartbeat breathhold. J Cardiovasc Magn Reson. 2010;12:69.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Wassmuth R, Prothmann M, Utz W, Dieringer M, von Knobelsdorff-Brenkenhoff F, Greiser A, et al. Variability and homogeneity of cardiovascular magnetic resonance myocardial T2-mapping in volunteers compared to patients with edema. J Cardiovasc Magn Reson. 2013;15:27.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Bohnen S, Radunski UK, Lund GK, Kandolf R, Stehning C, Schnackenburg B, et al. Performance of t1 and t2 mapping cardiovascular magnetic resonance to detect active myocarditis in patients with recent-onset heart failure. Circ Cardiovasc Imaging. 2015;8(6). pii: e003073. doi: 10.1161/CIRCIMAGING.114.003073.

  16. Kellman P, Hansen MS. T1-mapping in the heart: accuracy and precision. J Cardiovasc Magn Reson. 2014;16:2.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Xanthis CG, Bidhult S, Kantasis G, Heiberg E, Arheden H, Aletras AH. Parallel simulations for QUAntifying RElaxation magnetic resonance constants (SQUAREMR): an example towards accurate MOLLI T1 measurements. J Cardiovasc Magn Reson. 2015;17:104.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Kali A, Choi EY, Sharif B, Kim YJ, Bi X, Spottiswoode B, et al. Native T1 Mapping by 3-T CMR Imaging for Characterization of Chronic Myocardial Infarctions. JACC Cardiovasc Imaging. 2015;8:1019–30.

    Article  PubMed  Google Scholar 

  19. Bulluck H, White SK, Rosmini S, Bhuva A, Treibel TA, Fontana M, et al. T1 mapping and T2 mapping at 3 T for quantifying the area-at-risk in reperfused STEMI patients. J Cardiovasc Magn Reson. 2015;17:73.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Constantinides CD, Atalar E, McVeigh ER. Signal-to-noise measurements in magnitude images from NMR phased arrays. Magn Reson Med. 1997;38:852–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Dietrich O, Raya JG, Reeder SB, Reiser MF, Schoenberg SO. Measurement of signal-to-noise ratios in MR images: influence of multichannel coils, parallel imaging, and reconstruction filters. J Magn Reson Imaging. 2007;26:375–85.

    Article  PubMed  Google Scholar 

Download references

Acknowledgement

The authors wish to acknowledge the technicians Kerstin Kretschel, Evelyn Polzin, Denise Kleindienst and Franziska Neumann for acquiring the CMR data, and the study nurses Elke Nickel-Szczech and Antje Els for the organization of the CMR scans.

Funding

This project was supported by a grant of the Else Kröner-Fresenius Stiftung (Bad Homburg, Germany; 2010/A70).

Author information

Authors and Affiliations

  1. Working Group Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max-Delbrueck Center for Molecular Medicine and HELIOS Klinikum Berlin Buch, Department of Cardiology and Nephrology, Lindenberger Weg 80, Berlin, 13125, Germany

    Florian von Knobelsdorff-Brenkenhoff, Marcel Prothmann, Matthias A. Dieringer, Ralf Wassmuth, André Rudolph, Wolfgang Utz, Julius Traber & Jeanette Schulz-Menger

  2. Berlin Ultrahigh Field Facility, Max-Delbrueck Center for Molecular Medicine, Robert-Rössle-Str. 10, Berlin, 13125, Germany

    Florian von Knobelsdorff-Brenkenhoff, Marcel Prothmann, Matthias A. Dieringer, Thoralf Niendorf & Jeanette Schulz-Menger

  3. Siemens Healthcare, Allee am Roethelheimpark 2, Erlangen, 91052, Germany

    Andreas Greiser

  4. Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max-Delbrueck Center for Molecular Medicine, Lindenberger Weg 80, Berlin, 13125, Germany

    Thoralf Niendorf

Authors
  1. Florian von Knobelsdorff-Brenkenhoff
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marcel Prothmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Matthias A. Dieringer
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ralf Wassmuth
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. André Rudolph
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Wolfgang Utz
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Julius Traber
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Andreas Greiser
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Thoralf Niendorf
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Jeanette Schulz-Menger
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Florian von Knobelsdorff-Brenkenhoff.

Additional information

Competing interests

The co-author A. Greiser is employee of Siemens Healthcare. The other authors declare that they have no competing interests.

Authors’ contributions

FvKB made the conception and design of the study, acquired the data, performed analysis and interpretation of data and drafted the manuscript. MP made substantial contributions to conception and design, analysis and interpretation of data and was involved in drafting the manuscript. MAD and JT made substantial contributions to conception and design, acquisition and interpretation of data and revising the manuscript critically for important intellectual content. RW, AR and WU made substantial contributions to acquisition and interpretation of data and revising the manuscript critically for important intellectual content. AG and TN contributed to the conception and design of the study, interpretation of data and revising the manuscript critically for important intellectual content. JSM made the conception and design of the study, acquired the data, performed analysis and interpretation of data revised the manuscript critically for important intellectual content. All authors have given final approval of the version to be published. All authors read and approved the final manuscript.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

von Knobelsdorff-Brenkenhoff, F., Prothmann, M., Dieringer, M.A. et al. Current T1 and T2 mapping techniques applied with simple thresholds cannot discriminate acute from chronic myocadial infarction on an individual patient basis: a pilot study. BMC Med Imaging 16, 35 (2016). https://doi.org/10.1186/s12880-016-0135-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12880-016-0135-y

Keywords

BMC Medical Imaging

ISSN: 1471-2342

Contact us