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. 2020 Aug 13;15(8):e0237358. doi: 10.1371/journal.pone.0237358

Correlations of amide proton transfer-weighted MRI of cerebral infarction with clinico-radiological findings

Daichi Momosaka 1, Osamu Togao 1,*, Kazufumi Kikuchi 1, Yoshitomo Kikuchi 1, Yoshinobu Wakisaka 2, Akio Hiwatashi 3
Editor: Zhongliang Zu4
PMCID: PMC7425944  PMID: 32790705

Abstract

Objective

To clarify the relationship between amide proton transfer-weighted (APTW) signal, which reflects intracellular pH, and clinico-radiological findings in patients with hyperacute to subacute cerebral infarction.

Materials and methods

Twenty-nine patients (median age, 70 years [IQR, 54 to 74]; 15 men) were retrospectively examined. The 10th, 25th, 50th, 75th, and 90th percentiles of APTW signal (APT10, APT25, APT50, APT75 and APT90, respectively) were measured within the infarction region-of-interest (ROI), and compared between poor prognosis and good prognosis groups (modified Rankin Scale [mRS] score ≥2 and mRS score <2, respectively). Correlations between APTW signal and time after onset, lesion size, National Institutes of Health Stroke Scale (NIHSS) score, mRS score, and mean apparent diffusion coefficient (ADC) were evaluated.

Results

The poor prognosis group had lower APT50, APT75, and APT90 than the good prognosis group (–0.66 [–1.19 to –0.27] vs. –0.09 [–0.62 to –0.21]; –0.27 [–0.63 to –0.01] vs. 0.31 [–0.15 to 1.06]; 0.06 [–0.21 to 0.34] vs. 0.93 [0.36 to 1.50] %; p <0.05, respectively). APT50 was positively correlated with time after onset (r = 0.37, p = 0.0471) and negatively with lesion size (r = –0.39, p = 0.0388). APT75 and APT90 were negatively correlated with NIHSS (r = –0.41 and –0.43; p <0.05, respectively). APT50, APT75 and APT90 were negatively correlated with mRS (r = –0.37, –0.52 and –0.57; p <0.05, respectively). APT10 and APT25 were positively correlated with mean ADC (r = 0.37 and 0.38; p <0.05, respectively).

Conclusion

We demonstrated correlations between APTW signals of infarctions and clinico-radiological findings in patients with hyperacute to subacute infarctions. The poor prognosis group had a lower APTW signal than the good prognosis group. APTW signal was reduced in large infarctions, infarctions with low ADC, and in patients with high NIHSS and mRS scores.

Introduction

Ischemic stroke is a leading cause of various neurological sequelae or death throughout the world [1]. A critical reduction of cerebral blood flow leads to a failure in normal cerebral oxygen and glucose metabolism, which causes a shift to anaerobic glycolysis and results in the accumulation of lactic acid and a concomitant decrease in intracellular pH [2]. The intracellular pH of brain tissue varies according to metabolic energy status after stroke [3]. Thus, tissue pH may serve as a potential surrogate biomarker to reflect the metabolic state and tissue damage of ischemic brain tissue [4]. Previous phosphorus-31 MR resonance spectroscopy studies have revealed that early acidosis and subacute alkalosis occurs during ischemic stroke [5, 6]. However, the clinical application of phosphorus-31 MR spectroscopy to brain ischemia is limited by its low spatial and temporal resolution, and the requirement for special coils which are not available in most hospitals [7]. Thus, novel imaging methods to evaluate the changes of tissue pH after ischemic stroke in the clinical setting are required.

Amide proton transfer-weighted (APTW) MRI is a chemical exchange saturation transfer (CEST) imaging method [8]. In the past two decades, APTW MRI has been employed to evaluate the changes of mobile abnormal proteins and peptides in brain tumors [9, 10]. The CEST effect due to amide protons, referred to as the amide proton transfer ratio (APTR), highly depends on tissue pH as shown in the following formula:

APTR=κ[amideproton]2[waterproton](1etsat/T1)T1 (1)
κ=5.57×10pH6.4 (2)

where κ is proton exchange rate, which is the pH-dependent term as shown in Eq (2); T1 is the T1 relaxation time of water; and tsat is the duration of saturation [11]. Zhou et al. were the first to observe the pH-sensitive amide proton transfer effects in an animal model of brain ischemia in 2003 [12]. Since then, there have been increasing number of animal studies in which pH-sensitive APTW imaging has shown promise in detecting ischemic tissue acidosis following impaired aerobic metabolism [13, 14]. Despite these promising results, its translation to clinical use is still limited, and there have been only a few clinical studies using APTW imaging for ischemic stroke [1517].

Clarifying the relationship between APTW signal changes and clinical information should enhance our understanding of the pathophysiology of ischemic stroke, and may benefit its future treatment strategies. Therefore, the purpose of this study was to clarify the relationship between APTW imaging characteristics and the clinico-radiological findings in patients with hyperacute to subacute cerebral infarction.

Materials and methods

Participants

The institutional clinical research ethics committee of Kyushu University approved the study protocol (IRB Clinical Research number 2019–233). The requirement for informed consent was waived due to the retrospective nature of the study. The inclusion criteria were as follows: (a) patients who underwent MRI at our institution with clinical suspicions for acute or subacute infarctions (<3 weeks) from August 2014 to September 2019. The exclusion criteria were as follows: (a) patients who could not undergo APTW imaging because of clinical demand and availability of MRI unit, (b) lesions less than 10 mm in diameter on the transverse diffusion-weighted image (DWI), (c) insufficient image quality, (d) patient’s age <18 years, (e) patients who received endovascular therapy for brain infarction before MRI, (f) hemorrhagic infarction, and (g) other concurrent brain disorders.

Twenty-nine patients (median age, 70 years; interquartile range [IQR], 54 to 74 years) including 15 males (median age, 71 years; IQR, 59 to 75) and 14 females (median age, 63.5 years; IQR, 42.8 to 73.3) met the inclusion and exclusion criteria (Fig 1). In all patients, the clinical subtypes of infarctions were classified according to the TOAST stroke subtype classification system [18]. The time after onset was defined as the duration of symptom onset to MRI. The patients’ pre-stroke functional ability was assessed using the pre-stroke modified Rankin Scale (mRS) score [19]. Clinical severity was assessed with the National Institute of Health Stroke Scale (NIHSS) score when patients were admitted to the hospital [20]. The patients’ functional outcome was assessed using the mRS score [21] at the end of the follow-up period, at least four weeks after symptom onset. Pre-stroke mRS scores, NIHSS scores on admission, and mRS scores at the chronic phase were determined according to the medical records by a board-certified stroke physician (Y.W., 23 years of experience in stroke medicine).

Fig 1. Study population flowchart.

Fig 1

MRI data acquisition

MRI was conducted on a 3.0-T MRI system (Achieva TX, Philips Medical Systems, Best, the Netherlands) with an 8-channel head coil.

First, several routine MR sequences including transverse DWI, T2- and T1-weighted images, fluid attenuated inversion recovery, and 3D time-of-flight MR angiography were collected. DWI was performed using a single-shot echo-planar imaging diffusion sequence, with 2 b-values (0, 1000 sec/mm2) in three orthogonal directions. The other imaging parameters were as follows: repetition time = 2,500 ms, echo time = 70 ms, acquisition matrix = 128 × 126 (zero filled and reconstructed to 256 × 256), field-of-view = 230 × 230 mm2, slice thickness = 5 mm, number of slices = 22, resolution = 0.9 × 0.9 × 5.0 mm3, sensitivity encoding factor = 1.5, scan time = 2 min 7 sec.

Subsequently, APTW MRI was conducted on the transverse slice with the largest ischemic lesions, which was selected with reference to DWI. APTW MRI was conducted using a single-shot, turbo-spin-echo sequence, with the following parameters: saturation power = 1.5 μT, saturation time = 2.0 sec, repetition time = 5000 ms, echo time = 6 ms, acquisition matrix = 128 × 128, field-of-view = 230 × 230 mm2, slice thickness = 5 mm, resolution = 1.8 × 1.8 × 5.0 mm3. A multi-offset, multi-acquisition APTW MRI protocol was used, and 25 offsets spanned –6 to +6 ppm (25 offsets = 0, ± 0.5, ± 1.0, ± 1.5, ± 2.0, ± 2.5, ± 3.0, ± 3.5, ± 4.0, ± 4.5, ± 5.0, ± 5.5, ± 6.0 ppm). An unsaturated image was also acquired with the pre-saturation pulse set to –1560 ppm for signal normalization. The total duration of the APTW MRI protocol was 2 min 20 sec.

To correct the B0 inhomogeneity of the APTW MRI, a B0 map was acquired separately using the same imaging geometry and spatial resolution as the APTW MRI via a 2D gradient-echo sequence with the following parameters: repetition time = 15 ms, echo time = 8.1 ms, flip angle = 30°, dual echo (ΔTE = 1 ms), number of acquisitions = 16, scan time = 33 sec.

Data processing

All image processing was executed using Image J (version 1.48, National Institutes of Health, Bethesda, MD). To assess the APTR, we obtained the magnetization transfer ratio asymmetry (MTRasym) on a pixel-by-pixel basis from a Z-spectrum plot of the water signal attenuation versus offset saturation frequency (offset  =  0 for water resonance). Because the saturation frequency of amide protons is primarily around +3.5 ppm [12], the APTR was assessed by calculating the MTRasym at ±3.5 ppm according to the following formula [12]:

MTRasym(3.5ppm)=Ssat(3.5ppm)/S0Ssat(+3.5ppm)/S0=APTR+MTRasym(3.5ppm) (3)

where Ssat and S0 were the signal intensities obtained with and without selective radiofrequency saturation pulse irradiation, respectively. MTR’asym(3.5 ppm) represents the upfield nuclear Overhauser enhancement (NOE) effect of various non-exchangeable protons [22].

Eq (3) shows that MTRasym(3.5 ppm) contains not only the APTR, but also contributions from the NOE effect. Thus, we refer to MTRasym(3.5 ppm) as the APTW signal (%), and MTRasym(3.5 ppm) maps as APTW images.

Qualitative analysis of APTW images

As a qualitative analysis, the visibility of infarctions on APTW images was independently evaluated by two board-certified neuroradiologists (observer 1, D.M., 5 years of experience; observer 2, O.T., 19 years of experience) using a three-level visual grading scale as follows: clear, the infarction can be clearly identified as a hypointense lesion on an APTW image without reference to DWI; moderate, an infarction can be recognized as a hypointense lesion on APTW images, but it is difficult to identify the lesion without reference to DWI; unclear, a lesion cannot be recognized on an APTW image even with reference to DWI.

The inter-rater agreement for the visibility between the two observers was evaluated using Cohen's kappa coefficient [23].

Quantitative analysis of APTW images

The quantitative analysis was performed by a board-certified neuroradiologist (D.M., 5 years of experience). A region-of-interest (ROI) was manually drawn to include an entire hyperintense lesion on DWI; this ROI was then copied and pasted onto the APTW image. Another ROI was placed on the contralateral normal-appearing white matter (CNAWM).

We obtained the 10th, 25th, 50th, 75th, and 90th percentiles of the histogram for the APTW signal (%) within the ROIs (APT10, APT25, APT50, APT75, and APT90, respectively); the lowest 10% of the signal within an ROI was found below APT10, and the highest 10% was found above APT90. Histogram analysis is a quantitative technique has been used in previous CEST studies, e.g. Liu et al. applied a histogram distribution-based analysis for CEST signals of a mouse model of multiple sclerosis [24].

The mean apparent diffusion coefficient (ADC) (mm2/sec) within the infarction ROI was also obtained. Lesion size was measured as the maximum diameter of the infarction on the transverse DWI.

For the qualitative analyses, the APTW signal percentiles within the infarction ROI were compared to those within the CNAWM ROI using the Wilcoxon signed-rank test. Demographic and baseline clinical characteristics and the APTW signal percentiles within the infarction ROI were compared between cardioembolic infarctions and non-cardioembolic infarctions, and between the poor prognosis group (mRS score ≥2) and the good prognosis group (mRS score <2), using the Chi-squared and Mann–Whitney U tests. The correlations between the APTW signal percentiles within the infarction ROI and the time after onset, lesion size, NIHSS score on admission, mRS score at the chronic phase, and mean ADC within the infarction ROI were evaluated using Spearman’s rank correlation coefficient.

The statistical analyses were performed using JMP Pro 14.2.0 (SAS Institute, Cary, NC) under supervision of a statistician (J.K.). P-values <0.05 was considered statistically significant.

Results

Demographic and baseline clinical characteristics

The infarction etiologies were as follows: cardioembolic infarction, n = 10; non-cardioembolic infarction, n = 19 (large-artery atherosclerosis, n = 6; small vessel occlusion, n = 1; other determined etiology, n = 9; undetermined etiology, n = 3). Twenty-seven patients had infarctions in the cerebral hemispheres and two patients had infarctions in the cerebellar hemispheres. The median time after onset was 52.0 hours [15.3 to 129.0] (median [IQR]) (hyperacute infarction, 1.5–17 hours after onset, n = 9; acute infarction, 31–136 hours after onset, n = 15; subacute infarction, 189–322 hours after onset, n = 5). The pre-stroke mRS score was 1.0 [0 to 2.5], and the median NIHSS score on admission was 4.0 [2.0 to 10.5]. The mRS score at the chronic phase of stroke was 3.0 [1.0 to 4.5] (good prognosis, 0–1, n = 8; poor prognosis, 2–6, n = 21) with the follow-up period of 90.0 [70.5 to 90.0] days.

Qualitative analysis of APTW images

Observer 1 judged seven (24.1%), ten (34.5%), and twelve lesions (41.4%) as clear, moderate, and unclear, respectively. Observer 2 judged seven (24.1%), eleven (37.9%), and eleven lesions (37.9%) as clear, moderate, and unclear, respectively. The inter-rater agreement was moderate (kappa value = 0.84, p <0.001).

Quantitative analysis of APTW images

The APTW signal percentiles within the infarction and CNAWM ROIs are presented in Table 1. The APT10, APT25, and APT50 of the infarctions were significantly lower than those of the CNAWM (median APT10, –1.41 [IQR, –1.96 to –0.73] vs. –0.72 [–1.32 to –0.32] %, p <0.0001; APT25, –0.94 [–1.53 to –0.45] vs. –0.50 [–0.97 to –0.11] %, p = 0.0005; APT50, –0.53 [–1.18 to –0.13] vs. –0.24 [–0.64 to 0.16] %, p = 0.0027). The median lesion size was 46.0 mm [IQR, 32.5 to 71.5] (17–24 mm, n = 6; 25–49 mm, n = 10; 50–74 mm, n = 8; 75–99 mm, n = 2; 100–132 mm, n = 3).

Table 1. Percentiles of APTW signal of infarction and CNAWM (n = 29).

Infarction CNAWM p-value
APT10, % –1.41 (–1.96 to –0.73) –0.72 (–1.32 to –0.32) < 0.0001*
APT25, % –0.94 (–1.53 to –0.45) –0.50 (–0.97 to –0.11) 0.0005*
APT50, % –0.53 (–1.18 to –0.13) –0.24 (–0.64 to 0.16) 0.0027*
APT75, % –0.18 (–0.47 to 0.27) –0.01 (–0.44 to 0.41) 0.1739
APT90, % 0.15 (–0.11 to 0.60) 0.29 (–0.23 to 0.65) 0.8085

Data are expressed as median (interquartile range). APT10, APT25, APT50, APT75, and APT90 are the 10th, 25th, 50th, 75th, and 90th percentiles of the APTW signal within the infarction and CNAWM ROIs, respectively.

* indicates statistically significant (p <0.05). APTW, amide proton transfer-weighted; CNAWM, contralateral normal-appearing white matter; ROI, region-of-interest

The baseline clinical characteristics and the percentiles in the cardioembolic and other subtypes of cerebral infarction are presented in Table 2. There were no significant differences in the clinical characteristics and APTW signals within the infarction ROI between the two groups (p >0.05).

Table 2. Demographic and baseline clinical characteristics and percentiles of APTW signal of cardioembolic (n = 10) and non-cardioembolic (n = 19) infarctions.

Cardioembolic Non-cardioembolic p-value
Gender, male:female 7: 3 8: 11 0.1603
Age, yrs 66 (43.3 to 76.3) 71 (55.0 to 74.0) 0.8363
Time after onset, hrs 33.6 (4.1 to 113.1) 70.3 (31.7 to 129.3) 0.3352
Lesion size, mm 55.5 (20.0 to 83.3) 42 (35.0 to 57.0) 0.4626
Pre-stroke mRS score 0.5 (0 to 2.0) 1.0 (0 to 3.0) 0.3142
NIHSS score 4 (2.5 to 15.5) 3 (2.0 to 7.0) 0.5182
mRS score 1.5 (0 to 3.3) 4 (2.0 to 6.0) 0.0562
APT10, % –1.62 (–2.38 to –0.78) –1.18 (–1.88 to –0.69) 0.3019
APT25, % –1.11 (–1.63 to –0.51) –0.89 (–1.53 to –0.41) 0.5663
APT50, % –0.53 (–1.27 to –0.18) –0.53 (–1.18 to –0.07) 0.6300
APT75, % –0.09 (–0.59 to 0.37) –0.18 (–0.44 to 0.21) 0.9451
APT90, % 0.43 (–0.29 to 1.16) 0.14 (–0.05 to 0.54) 0.6629

Data are expressed as median (interquartile range). APT10, APT25, APT50, APT75, and APT90 are the 10th, 25th, 50th, 75th, and 90th percentiles of APTW signal within the infarction ROI, respectively. APTW, amide proton transfer-weighted; mRS, modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale; ROI, region-of-interest

Table 3 shows the baseline clinical characteristics and percentiles of the two groups divided according to their mRS scores at the chronic period. The baseline clinical characteristics were not significantly different between the poor and good prognosis groups. The APT50, APT75, and APT90 within the infarction ROI were significantly lower in the poor prognosis group than those in the good prognosis group (median APT50, –0.66 [IQR, –1.19 to –0.27] vs. –0.09 [–0.62 to –0.21] %, p = 0.0481; APT75, –0.27 [–0.63 to –0.01] vs. 0.31 [–0.15 to 1.06] %, p = 0.0104; APT90, 0.06 [–0.21 to 0.34] vs. 0.93 [0.36 to 1.50] %, p = 0.0037).

Table 3. Demographic and baseline clinical characteristics and percentiles of APTW signal of the poor prognosis group with mRS score ≥2 (n = 21) and good prognosis group with mRS score <2 (n = 8).

Poor prognosis Good prognosis p-value
Gender, male:female 10: 11 5: 3 0.4812
Age, yrs 72.0 (56.0 to 75.5) 61.0 (47.5 to 70.8) 0.1240
Time after onset, hrs 41.2 (15.3 to 102.5) 100.8 (19.7 to 177.6) 0.3171
Lesion size, mm 48.0 (36.0 to 72.0) 37.0 (22.5 to 67.3) 0.3536
Pre-stroke mRS score 1.0 (0 to 3.0) 0.5 (0 to 1.8) 0.2731
NIHSS score 5.0 (2.5 to 11.0) 3.0 (1.0 to 10.8) 0.2107
Cardioembolic:Non-cardioembolic 5: 16 5: 3 0.0834
APT10, % –1.41 (–2.12 to –0.83) –1.12 (–1.78 to –0.53) 0.2941
APT25, % –1.12 (–1.62 to –0.59) –0.62 (–1.09 to –0.21) 0.1367
APT50, % –0.66 (–1.19 to –0.27) –0.09 (–0.62 to 0.21) 0.0481*
APT75, % –0.27 (–0.63 to –0.01) 0.31 (–0.15 to 1.06) 0.0104*
APT90, % 0.06 (–0.21 to 0.34) 0.93 (0.36 to 1.50) 0.0037*

Data are expressed as median (interquartile range). APT10, APT25, APT50, APT75, and APT90 are the 10th, 25th, 50th, 75th, and 90th percentiles of APTW signal within the infarction ROI, respectively.

* indicates statistically significant (p <0.05). APTW, amide proton transfer-weighted; mRS, modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale

The correlations between APTW signal within the infarction ROI and time after onset, lesion size, NIHSS score, mRS score, and mean ADC are summarized in Table 4. The APT50 was positively correlated with time after onset (r = 0.37, p = 0.0471), and inversely correlated with lesion size (r = –0.39, p = 0.0388). APT75 and APT90 were inversely correlated with the NIHSS score (APT75, r = –0.41, p = 0.0261; APT90, r = –0.43, p = 0.0189). APT50, APT75, and APT90 were inversely correlated with the mRS score at the chronic phase of stroke (APT50, r = –0.37, p = 0.0451; APT75, r = –0.52, p = 0.0035; APT90, r = –0.57, p = 0.0013). APT10 and APT25 were positively correlated with mean ADC (APT10, r = 0.37, p = 0.0457; APT25, r = 0.38, p = 0.0439).

Table 4. Correlations between percentiles of APTW images and clinico-radiological findings in infarctions (n = 29).

Time after onset, hrs Lesion size, mm NIHSS score mRS score Mean ADC, mm2/sec
APT10, % r = 0.16, p = 0.3628 r = –0.27, p = 0.1522 r = –0.14, p = 0.4753 r = –0.16, p = 0.3939 r = 0.37, p = 0.0457*
APT25, % r = 0.24, p = 0.2139 r = –0.36, p = 0.0552 r = –0.23, p = 0.2220 r = –0.25, p = 0.1846 r = 0.38, p = 0.0439*
APT50, % r = 0.37, p = 0.0471* r = –0.39, p = 0.0388* r = –0.33, p = 0.0811 r = –0.37, p = 0.0451* r = 0.33, p = 0.0838
APT75, % r = 0.34, p = 0.0692 r = –0.33, p = 0.0809 r = –0.41, p = 0.0261* r = –0.52, p = 0.0035* r = 0.27, p = 0.1528
APT90, % r = 0.28, p = 0.1375 r = –0.22, p = 0.2427 r = –0.43, p = 0.0189* r = –0.57, p = 0.0013* r = 0.08, p = 0.6826

APT10, APT25, APT50, APT75, and APT90 are the 10th, 25th, 50th, 75th, and 90th percentiles of the APTW signal within the infarction ROI, respectively.

* indicates statistically significant (p <0.05). APTW, amide proton transfer-weighted; ADC, apparent diffusion coefficient; NIHSS, National Institutes of Health Stroke Scale; mRS, modified Rankin Scale; ROI, region-of-interest

Sensitivity analysis of study participants without pre-stroke dependency

The sensitivity analysis of a subpopulation of patients without pre-stroke dependency (n = 18, pre-stroke mRS≦1) showed the same trend for an association between the APTW signal within the infarction ROI and the stroke outcome (see details in S1 Appendix): the APT50, APT75, and APT90 were significantly lower in the poor prognosis group than those in the good prognosis group (median APT50, –0.74 [IQR, –1.42 to –0.35] vs. 0 [–0.44 to 0.42] %, p = 0.0169; median APT75, –0.36 [–0.82 to –0.07] vs. 0.45 [–0.06 to 1.44] %, p = 0.0131; median APT90, 0.03 [–0.44 to 0.49] vs. 0.94 [0.21 to 2.21] %, p = 0.0169). Moreover, APT50, APT75, and APT90 were inversely correlated with the mRS score at the chronic phase of stroke (APT50, r = –0.54, p = 0.0211; APT75, r = –0.59, p = 0.0099; APT90, r = –0.57, p = 0.0130).

Figs 24 show representative cases of cerebral infarctions.

Fig 2. A 60-year-old male with a hyperacute cardioembolic infarction fifteen hours after the onset.

Fig 2

The pre-stroke mRS score was one. The NIHSS score at the time of admission was 17. The mRS score at 90 days after the onset was one. No signal abnormality is seen on A: T1-weighted image, B: T2-weighted image, and C: FLAIR image. D: DWI shows the hyperintense infarct area in the left frontal lobe. The ROI of the infarct area (red line) and the CNAWM (green line) is indicated. E: The infarct area shows restricted diffusivity (mean ADC = 0.41 × 10−3 mm2/sec). F: MR angiography shows the occlusion of the frontal branch of the left middle cerebral artery (arrow). G: The infarct area was hypointense on the APTW image (APT10 = –3.52%, APT25 = –2.90%, APT50 = –2.13%, APT75 = –0.22%, APT90 = 1.50%) (arrowheads). On the visual grading scale, this case was graded as clear by both raters. H: Z-spectra show a lower CEST effect in the entire offset range (–6 to +6 ppm) in the infarct area compared to the CNAWM. G: MTRasym spectra show decreased MTRasym (3.5ppm) or APTW signal (%) in the infarct area compared to the CNAWM. mRS, modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale; FLAIR, fluid attenuated inversion recovery; DWI, diffusion-weighted imaging; ROI, region-of-interest; ADC, apparent diffusion coefficient; APTW, amide proton transfer-weighted; CEST, chemical exchange saturation transfer; CNAWM, contralateral normal-appearing white matter; Ssat(ppm) and S0, the signal intensities obtained with and without selective radiofrequency saturation pulse irradiation, respectively; APT10, APT25, APT50, APT75, and APT90 correspond to the 10th, 25th, 50th, 75th, and 90th percentiles of the APTW signal value within the ROI, respectively.

Fig 4. A 59-year-old male with a subacute atherosclerotic infarction nine days after the onset.

Fig 4

The pre-stroke mRS score was zero. The NIHSS score at the time of admission was 10. The mRS score at 90 days after the onset was four. The infarct area in the right cerebellar hemisphere is hypointense on A: T1-weighted image; and hyperintense on B: T2-weighted image, C: FLAIR, and D: DWI. The ROI of the infarct area (red line) and the CNAWM (green line) are indicated. E: The infarct area shows restricted diffusivity (mean ADC = 0.51 × 10−3 mm2/sec). F: MR angiography shows the terminus stenosis of the right internal carotid artery (arrow). G: The infarct area was relatively hypointense on the APTW image (APT10 = –0.68%, APT25 = –0.41%, APT50 = –0.07%, APT75 = 0.30%, APT90 = 0.64%) (arrowheads). This case was graded as moderate by both raters on the visual grading scale. H: Z-spectra show a lower CEST effect in the entire offset range (–6 to +6 ppm) in the infarct area compared to the CNAWM. G: MTRasym spectra show decreased MTRasym(3.5ppm) or APTW signal (%) in the infarct area compared to the CNAWM. mRS, modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale; FLAIR, fluid attenuated inversion recovery; DWI, diffusion-weighted imaging; ROI, region-of-interest; ADC, apparent diffusion coefficient; APTW, amide proton transfer-weighted; CEST, chemical exchange saturation transfer; CNAWM, contralateral normal-appearing white matter; Ssat (ppm) and S0, the signal intensities obtained with and without selective radiofrequency saturation pulse irradiation, respectively; APT10, APT25, APT50, APT75, and APT90, correspond to the 10th, 25th, 50th, 75th, and 90th percentiles of APTW signal value, respectively.

Fig 3. A 27-year-old female with an acute cardioembolic infarction fifteen hours after the onset.

Fig 3

The pre-stroke mRS score was zero. The NIHSS score at the time of admission was 15. The mRS score at 90 days after the onset was four. The infarct area in the left cerebral hemisphere is hypointense on A: T1-weighted image; and hyperintense on B: T2-weighted image, C: FLAIR, and D: DWI. The ROI of the infarct area (red line) and the CNAWM (green line) is indicated. E: The infarct area shows restricted diffusivity (mean ADC = 0.36 × 10−3 mm2/sec). F: MR angiography shows the occlusion of the left middle cerebral artery (arrow). G: The infarct area was hypointense on the APTW image (APT10 = –2.29%, APT25 = –1.93%, APT50 = –1.51%, APT75 = –1.10%, APT90 = –0.69%) (arrowheads). This case was graded as clear by both raters according to the visual grading scale. H: Z-spectra show a lower CEST effect in entire offset range (–6 to +6 ppm) in the infarct area compared to the CNAWM. G: MTRasym spectra show decreased MTRasym(3.5ppm) or APTW signal (%) in the infarct area compared to the CNAWM. mRS, modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale; FLAIR, fluid attenuated inversion recovery; DWI, diffusion-weighted imaging; ROI, region-of-interest; ADC, apparent diffusion coefficient; APTW, amide proton transfer-weighted; CEST, chemical exchange saturation transfer; CNAWM, contralateral normal-appearing white matter; Ssat(ppm) and S0, the signal intensities obtained with and without selective radiofrequency saturation pulse irradiation, respectively; APT10, APT25, APT50, APT75, and APT90, correspond to the 10th, 25th, 50th, 75th, and 90th percentiles of APTW signal value, respectively.

Discussion

In this study, we observed a significantly reduced APTW signal in the infarct area compared to that in the CNAWM, in agreement with previous studies [12, 13, 17].

As shown in Eqs (1) and (2), the APTR depends on not only tissue pH, but also T1 relaxation time, water content, and amide proton content. However, it has been previously reported that APTR changes are primarily determined by pH changes [12]. In addition, a previous study using phosphorus-31 MR spectroscopy has demonstrated that pH abnormalities of the infarct area remain, even in the subacute phase [6]. T1 relaxation time and water content of the infarct area have been shown to both increase over time during the acute to subacute phase due to cytotoxic edema [25]; as the T1 relaxation time has a strong positive correlation with the water content in the infarct area [26], the two changes may cancel each other out to some extent. There has been no previous study focusing on dynamic changes of the amide proton content within the infarction. However, based on a study investigating amide proton content in peritumoral brain edema [27], we speculate that amide proton content might decline in infarctions with cytotoxic edema, which would affect the APTR.

As shown in Eq (3), the APTW signal includes not only the APTR but also MTR’asym(3.5 ppm), which is attributed to the upfield NOE effect [22]. However, a recent quantitative CEST study using animal models confirmed that the APTR accounts for a greater part of the MTRasym(3.5 ppm) changes than the NOE effect [28]. Collectively, this suggests that the APTW signal would primarily depend on tissue pH of the infarction, even in the subacute phase. Therefore, the reduction in APTW signal in the infarction observed in the present study likely reflects the reduced CEST effect of amide protons due to pH reduction.

The APTW signal within the infarction ROI was significantly lower in the poor prognosis group than in the good prognosis group, which was similar to the findings of Lin et al. [29]. Although infarct volume could be a prognostic factor for patients with cerebral infarction [30], there were no significant differences in the lesion size between the two groups. Thus, the APTW signal of the infarct area might be a new prognostic factor, independent from a lesion size.

Our analyses showed that the APTW signal within the infarction was positively correlated with the time after onset. This might reflect the alleviation of tissue acidification that occurs over time after the onset, as previously demonstrated in both animal [13] and clinical [17] studies. This result is consistent with previous studies using phosphorus-31 MR spectroscopy [5, 6]. The increase in pH after stroke could be explained by active compensatory mechanisms within the ischemic tissue, such as microglial invasion and alternate buffering mechanisms [6].

The APTW signal within the infarction was inversely correlated with the lesion size. We assume that larger infarctions could have a smaller surface area to volume ratio, which would reduce gas-diffusion from surrounding area and result in severe metabolic dysfunction.

The APTW signal within the infarction was significantly inversely correlated with both the NIHSS score on admission and the mRS score at the chronic phase. Lin et al. [29] have previously shown that the difference of the APTW signal between the acute ischemic region and the contralateral side is linearly correlated with both the NHISS score and mRS score. Thus, these results indicate that the APTW signal may be a useful tool to assess stroke severity and predict outcome.

A previous study has demonstrated that a high pre-stroke mRS score is significantly associated with poor functional outcomes at the chronic phase [19]. Thus, we were concerned that the pre-stroke mRS score could be a confounding factor when evaluating the relationship between the APTW signal and mRS score at the chronic phase. Therefore, we conducted an additional sensitivity analysis of a patient subpopulation comprising only those with low pre-stroke mRS scores (pre-stroke mRS ≤1), to exclude the influence of a high pre-stroke mRS score. This sensitivity analysis showed that APTW signal within the infarction in the poor prognosis group was significantly lower than that in the good prognosis group, and was inversely correlated with the mRS score at the chronic phase, which agreed with the main results. These findings suggest that a low APTW signal within the infarction could predict poor outcome, regardless of pre-stroke mRS score.

We found that the APTW signal was positively correlated with ADC in infarctions, indicating that the pH reduction may correlate with the severity of cytotoxic edema. One explanation for this is that acid-sensing ion channels, which are hydrogen ion-gated cation channels that are permeable to Na+, are activated as pH falls but are inactive at physiological pH [31]. Thus, pH reduction would promote intracellular Na+ accumulation via the activation of those channels, worsening the cytotoxic edema.

The two observers judged 11 and 12 out of the 29 infarctions as unclear on the visual grading scale. This may reflect an insufficient sensitivity to pH changes in the protocol used in this study. Concomitantly, undetected lesions might have less tissue acidosis compared to the detected lesions. Optimization of the acquisition parameters, application of a fitting method [32], correction with T1-relaxation time [33, 34] and reduction of motion effect [35] would be helpful to improve the sensitivity of APTW images to tissue pH.

There were no significant differences in the APTW signals within the infarctions between cardioembolic infarctions and the other subtypes. The pH reduction might be less influenced by clinical subtypes compared to other factors such as lesion size or time after onset. Since the number of patients in each group was small, the effect of clinical subtype should be evaluated in a larger patient population.

Our study had several limitations. First, only a limited number of the records of patients with suspected acute infarctions included APTW MRI. When patients are treated for infarctions, the opportunity to perform new treatment and assessment protocols is limited. Therefore, the sample size was small (n = 29) in this study period. Second, although we excluded cases with intense participant motion, it remains possible that participant motion negatively affected the image quality. Third, we determined pre-stroke mRS scores, NIHSS scores on admission, and mRS scores at the chronic phase retrospectively with a stroke physician supervising to avoid inaccurate scoring. Fourth, to date, the optimal saturation pulse strength for APTW imaging has not been established, and saturation pulse strengths of 0.5–3 μT have been used in previous studies [1416, 36, 37]. We selected a saturation power of 1.5 μT based on a previous animal study that reported the relationship between APTW signal and tissue lactic acidosis [14]. However, a human study has demonstrated that a saturation power of either 2 or 3 μT can result in a better APTW image contrast between the infarction and the CNAWM than that of 1 μT [15]. Considering these facts, we feel that the saturation pulse of 1.5 μT used in the present study was acceptable; however, slightly stronger saturation powers might have improved the APTW image contrast.

In conclusion, we demonstrated correlations between the APTW signal of infarctions and the clinico-radiological findings in patients with hyperacute to subacute infarctions. The poor prognosis group had a lower APTW signal than good prognosis group. APTW signal was reduced in large infarctions, infarctions with low ADC, and in patients with high NIHSS and mRS scores.

Supporting information

S1 Appendix. Supporting methods and results.

(DOCX)

Acknowledgments

The authors thank Junji Kishimoto, PhD, from the Center for Clinical and Translational Research, Kyushu University Hospital, for his contribution to the statistical analysis.

Abbreviations

APTW

amide proton transfer-weighted

ADC

apparent diffusion coefficient

CEST

chemical exchange saturation transfer

CNAWM

contralateral normal-appearing white matter

DWI

diffusion-weighted imaging

IQR

interquartile range

mRS

modified Rankin Scale

MTRasym

magnetization transfer ratio asymmetry

NIHSS

National Institutes of Health Stroke Scale

NOE

nuclear Overhauser enhancement

ROI

region-of-interest

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

This work was supported by JSPS KAKENHI grants no. JP17K10410 and no. JP20K08111 (https://www.jsps.go.jp). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Zhongliang Zu

21 May 2020

PONE-D-20-12833

Correlations of Amide Proton Transfer-Weighted MRI of Cerebral Infarction with Clinico-radiological Findings

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Reviewer #1: This study investigated the relationship between amide proton transfer-weighted (APTw) imaging signals with clinic-radiological findings in patients with cerebral infarction. Results on 29 patients showed the association of APTw imaging with clinical and prognostic features, including time after onset, lesion size, NIHSS, mRS and so on. The findings may facilitate better understanding of pathophysiology of ischemic stroke and thus benefit treatment strategies.

There are several issues that need to be addressed.

(1) As shown in Equation 1, the APTw effect is not only dependent on amide proton exchange rate of k, but also dependent on [amide proton]/[water proton] and T1. The studied 29 patients were at different stroke stages with varied time after onset (1.5-322 hours). I am not sure if [amide proton]/[water proton] and T1 still remain constant after hundred hours after stroke onset. If not, the APTw change may not be specific to pH alteration. It may be useful to provide images of T1w and T2w, as well as Z-spectra of infarct lesion and CNAWM for patients at different stroke stages.

(2) It is not clear why only 10th percentile of ADC was measured from DWI data. How about mean ADC? Is it correlated with APT?

(3) Please explain why a saturation power of 1.5 μT was employed. Was the CEST data corrected for B0 inhomogeneity? Please provide the details.

(4) Calculation of magnetization transfer ratio was described in the ‘Data processing’ section, but I did not see any results about it.

(5) How many slices for DWI? Why the acquisition matrix was 128x126 (rather than 128x128) and reconstructed to 256x256? Should DWI performed before APT imaging so that the slice with the largest ischemic lesions could be identified from DWI? Please re-order the imaging protocols.

(6) Please illustrate ROIs of CNAWM in Fig.2 and 3.

(7) In the discussion section, the authors stated that “we concerned mRS scores at the chronic phase were biased by pre-stroke mRS in this study”. What does this mean? Please clarify.

(8) Please keep consistent for MRA image illustration for Fig.2 and 3.

Reviewer #2: This manuscript retrospectively examined 29 stroke patients for association among their MRI markers and other clinical findings. In methodology, the histogram parameters including 10th, 25th, 50th, 75th, and 90th percentiles of APTW signal were calculated, and compared with other clinical factors including time after onset, lesion size, NIHSS and mRS. Furthermore, patients were subgrouped according to their prognosis and origins (cardioembolic v.s. no cardioembolic). Overall, the histogram analysis of APTw MRI is new for stroke patients. And the correlation with clinical factors were performed in detail and the results are sound. Therefore, I recommend for publication, after minor correction of following points.

1.The APT10, APT25 ... parameters are new to readers. Therefore, in writing, authors should emphasize and clarify the meaning of these parameters. For example, in method authors need to clarify APT10 is the “top” 10% since people can also measure the lowest 10%. In note of Table1 as well as in discussion,authors should clarify that APT 10 , APT 25 , ... are the 10th, 25th,... percentiles of APTW signal “within the ROIs”. Furthermore, authors may want to cite another paper on histogram analysis of CEST data (Liu T. et al “CEST MRI With Distribution-Based Analysis for Assessment of Early Stage Disease Activity in a Mouse Model of Multiple Sclerosis:An initial study”NMR Biomed 2019 Nov;32(11):e4139)

2.In figure caption(text) for Fig. 2 and Fig. 3, authors say both APTw signals in infarct area as indicated by DWI are lower compared with those for contralateral tissue. However, visually the lower signal lesions is not clear in Fig.3 APTw image. The authors should add more explanation on the comparison of Fig2 and Fig.3.

3.Line 42-43, in conclusion of the abstract, Authors claimed that "APTW imaging associates with clinico-radiological findings including the prognosis of patients with cerebral infarction."This is a bit over-interpreted, and the writing should be more accurate and specific.

4.APT25 (%), APT50 (%), APT75 (%) and APT90 (%) should be also reported both in Fig. 2 and Fig. 3.

5.MTRasym should be uniform throughout the paper. And the English writing should be more clear and accurate.

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2020 Aug 13;15(8):e0237358. doi: 10.1371/journal.pone.0237358.r002

Author response to Decision Letter 0


7 Jul 2020

Reviewer #1:

There are several issues that need to be addressed.

(1) As shown in Equation 1, the APTw effect is not only dependent on amide proton exchange rate of k, but also dependent on [amide proton]/[water proton] and T1. The studied 29 patients were at different stroke stages with varied time after onset (1.5-322 hours). I am not sure if [amide proton]/[water proton] and T1 still remain constant after hundred hours after stroke onset. If not, the APTw change may not be specific to pH alteration. It may be useful to provide images of T1w and T2w, as well as Z-spectra of infarct lesion and CNAWM for patients at different stroke stages.

RESPONSE: Thank you for this comment. As you pointed out, the APT effect (referred to as the APT ratio or APTR in the present study) depends on not only tissue pH, but also T1 relaxation time, water content, and amide proton content as shown in equations (1) and (2).

However, it has been shown that APTR changes are largely determined by changes in pH (Zhou J, et al. Nature medicine. 2003;9). A previous study using phosphorus-31 MR spectroscopy has demonstrated that pH abnormalities of the infarct area remain, even in the subacute phase (Zollner JP, et al. Stroke. 2015;46).

T1 relaxation time and water content of the infarct area both increase over time during the acute to subacute phase, due to cytotoxic and vasogenic edema (Allen LM, et al. RadioGraphics. 2012;32). As the T1 relaxation time has a strong positive correlation with the water content in the infarct area (Lin et al. Journal of Cerebral Blood Flow and Metabolism 20;37), it seems likely that the two changes would cancel each other out, and thus contributions from both T1 and water content would be small.

There has been no previous study focusing on dynamic changes of the amide proton content within the infarction. However, based on a study investigating amide proton content in peritumoral brain edema (Zhou J, et al. Magnetic resonance in medicine. 2003;50), it might decline in infarctions with cytotoxic edema, which might have affected the APTR to some extent.

As shown in equation (3), the APTW signal includes not only the APTR but also MTR’asym(3.5 ppm), which is attributed to the upfield NOE effect and does not reflect pH changes. However, a recent quantitative CEST study using animal models confirmed that the APTR accounts for a greater part of the MTRasym(3.5 ppm) changes than the NOE effect (Wu Y, et al. Magnetic resonance in medicine. 2018;79). Considering these facts, the APTW signal should primarily depend on tissue pH of the infarction, even in the subacute phase. We have added these points to the discussion (p.19–20, lines 370–388).

As requested, we have shown three cases with different stroke stages (hyperacute, acute, and subacute) in Fig 2–4 including T1WI, T2WI, Z-spectra, and MTRasym spectra of the infarction and CNAWM.

(2) It is not clear why only 10th percentile of ADC was measured from DWI data. How about mean ADC? Is it correlated with APT?

RESPONSE: Thank you for these questions. We used the ADC10 percentile because we initially thought it would better reflect the degree of cellular edema in infarctions.

We have calculated the correlation between the mean ADC values and APTW signals, and found that the mean ADC values were also positively correlated to the APTW signals (Table 4). Because the mean ADC value has been broadly used to measure the degree of diffusion restriction in infarctions, we have replaced the APT10 values with mean ADC values throughout the manuscript.

(3) Please explain why a saturation power of 1.5 μT was employed. Was the CEST data corrected for B0 inhomogeneity? Please provide the details.

RESPONSE: Thank you for these questions. The optimal saturation pulse strength for APTW imaging has not been established yet. Saturation pulse strengths of 0.5–3 μT have been used in previous studies. We selected a saturation power of 1.5 μT based on a previous animal study that reported the relationship between APTW signal and tissue lactic acidosis (Sun PZ, et al. Journal of cerebral blood flow and metabolism. 2007;27). However, a human study demonstrated that a saturation power of either 2 or 3 μT resulted in the better APTW image contrast between the infarction and the CNAWM than that of 1 μT (Zhao X, et al. Magnetic resonance in medicine. 2011;66). Considering these facts, we feel that the saturation pulse of 1.5 μT used in the present study was acceptable; however, slightly stronger saturation powers might have improved the APTW image contrast. We have added this point to the limitation section of the discussion (p.23, lines 450–459).

To correct the B0 susceptibility and inhomogeneity of the APTW MRI, we acquired a B0 map for off-resonance correction separately, with an identical spatial resolution to that of the APTW MRI. We have described this point in detail in the revised manuscript (p.7–8, lines 142–146).

(4) Calculation of magnetization transfer ratio was described in the ‘Data processing’ section, but I did not see any results about it.

RESPONSE: We apologize for the confusion. This study did not evaluate the MTR alone. Instead, we evaluated the MTR asymmetry (MTRasym) at ± 3.5 ppm as the APTW signal. We have rewritten the data processing section to clarify this (p.8, lines 147–164).

(5) How many slices for DWI? Why the acquisition matrix was 128x126 (rather than 128x128) and reconstructed to 256x256? Should DWI performed before APT imaging so that the slice with the largest ischemic lesions could be identified from DWI? Please re-order the imaging protocols.

RESPONSE: Thank you for these questions. The number of slices for DWI was 22.

With the 3.0-T MRI system (Achieva TX, Philips Medical Systems, Best, the Netherlands) we used, we were not able to directly set the acquisition matrix in k-space. Instead, the acquisition matrix was calculated backwards from the FOV, in-plane resolution, and sensitivity encoding factor; therefore, the number of phase-encoding steps did not result in just 128, but also 126. This is simply a matter of equipment operation and did not affect the ultimate images.

We generated a 256 x 256 matrix in DWI by filling the periphery of the 128 x 126 acquisition matrix in k-space with zeroes (zero filling interpolation: ZIP), which is a routinely-used interpolation technique (Bernstein MA, et al. Journal of Magnetic Resonance Imaging. 2001;14). We have described the number of slices and the zero-filling interpolation in the MRI data acquisition section of the materials and methods (p.7, lines 129–130).

In the present study, several MR sequences including transverse DWI, T2- and T1-weighted images, fluid attenuated inversion recovery, and 3D time-of-flight MR angiography were collected first. Subsequently, APTW MRI was conducted on the transverse slice with the largest ischemic lesions, which was selected with reference to DWI. We have clarified this point in the MRI data acquisition section and re-ordered the imaging protocols (p.6–8, lines 121–146).

(6) Please illustrate ROIs of CNAWM in Fig.2 and 3.

RESPONSE: Thank you for this suggestion. We have added the ROIs of the CNAWM to all the case presentations (Fig 2–4).

(7) In the discussion section, the authors stated that “we concerned mRS scores at the chronic phase were biased by pre-stroke mRS in this study”. What does this mean? Please clarify.

RESPONSE: We apologize for the confusion. A previous study demonstrated that a high pre-stroke mRS score was significantly associated with poor functional outcomes at the chronic phase (Quinn TJ, et al. Frontiers in neurology. 2017;8). Thus, we were concerned that the pre-stroke mRS score could be a confounding factor when evaluating the relationship between the APTW signal and the mRS score at the chronic phase. Therefore, we conducted an additional sensitivity analysis of a patient subpopulation comprising only those with low pre-stroke mRS scores (pre-stroke mRS ≤1), to exclude the influence of a high pre-stroke mRS score.

We have rewritten the corresponding part of the discussion to clarify this (p.21–22, lines 414–420).

(8) Please keep consistent for MRA image illustration for Fig.2 and 3.

RESPONSE: Thank you for this suggestion. We have presented all the MRA images as maximum intensity projections in Fig 2–4.

Reviewer #2


1.The APT10, APT25 ... parameters are new to readers. Therefore, in writing, authors should emphasize and clarify the meaning of these parameters. For example, in method authors need to clarify APT10 is the “top” 10% since people can also measure the lowest 10%. In note of Table1 as well as in discussion,authors should clarify that APT 10 , APT 25 , ... are the 10th, 25th,... percentiles of APTW signal “within the ROIs”. Furthermore, authors may want to cite another paper on histogram analysis of CEST data (Liu T. et al “CEST MRI With Distribution-Based Analysis for Assessment of Early Stage Disease Activity in a Mouse Model of Multiple Sclerosis:An initial study”NMR Biomed 2019 Nov;32(11):e4139)

RESPONSE: Thank you for pointing this out. We obtained the 10th, 25th, 50th, 75th, and 90th percentiles of the APTW signals (%) within the ROI (APT10, APT25, APT50, APT75, APT90, respectively). The lowest 10% of the signal within an ROI was found below APT10, and the highest 10% was found above APT90. We have clarified this in the quantitative analysis of APTW images section (p. 9, lines 181–184). We have also emphasized that APTW signals were calculated within the infarction or CNAWM ROIs, throughout the paper.

We have cited the article by Liu et al. as an example of the application of APTW MRI in the introduction (p. 4, lines 71–73).

2.In figure caption(text) for Fig. 2 and Fig. 3, authors say both APTw signals in infarct area as indicated by DWI are lower compared with those for contralateral tissue. However, visually the lower signal lesions is not clear in Fig.3 APTw image. The authors should add more explanation on the comparison of Fig2 and Fig.3.

RESPONSE: Thank you for this suggestion. First, we have replaced Fig 3 with another case of subacute infarction, and added a case of hyperacute infarction in accordance with the suggestion by Reviewer #1. In addition, to make the figures easier to understand, we have added arrowheads indicating the infarct area to the APTW images (Fig 2–4).

3.Line 42-43, in conclusion of the abstract, Authors claimed that "APTW imaging associates with clinico-radiological findings including the prognosis of patients with cerebral infarction."This is a bit over-interpreted, and the writing should be more accurate and specific.

RESPONSE: Thank you for pointing this out. We have removed the description, and replaced it with the following conclusion: The poor prognosis group had a lower APTW signal than the good prognosis group. APTW signal was reduced in large infarctions, infarctions with low ADC, and in patients with high NIHSS and mRS scores. (p. 3, lines 43–46).

4.APT25 (%), APT50 (%), APT75 (%) and APT90 (%) should be also reported both in Fig. 2 and Fig. 3.

RESPONSE: Thank you for pointing this out. We have added APT25, APT50, APT75 and APT90 to the figure legends (Fig 2–4).

5.MTRasym should be uniform throughout the paper. And the English writing should be more clear and accurate.

RESPONSE: Thank you for pointing this out. We have standardized MTRasym throughout the manuscript. A professional English language editing company has checked and edited the manuscript. We have attached the separate file labeled 'Certificate of English Editing’ as proof that we have used the service.

Attachment

Submitted filename: Response to Reviewers.docx

Decision Letter 1

Zhongliang Zu

15 Jul 2020

PONE-D-20-12833R1

Correlations of amide proton transfer-weighted MRI of cerebral infarction with clinico-radiological findings

PLOS ONE

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Please correct the reference 11.

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Reviewer #2: Reference 11 was cited at the wrong place. Currently it is cited in the introduction " or to detect subtle inflammatory changes at an early stage of multiple sclerosis [11]." This is not proper. Reference 11 not only examined APT signal, but also CEST signals at other offsets. Importantly, it applied a distribution-based analysis for CEST analysis. And in this paper the parameters APT10,APT15, ... in fact is also a quantitative desciption of APTw images. Therefore, the old reference 11 should be cited in the method within the "Quantitative analysis of APTW images" part

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PLoS One. 2020 Aug 13;15(8):e0237358. doi: 10.1371/journal.pone.0237358.r004

Author response to Decision Letter 1


17 Jul 2020

Reviewer #2:

Reference 11 was cited at the wrong place. Currently it is cited in the introduction " or to detect subtle inflammatory changes at an early stage of multiple sclerosis [11]." This is not proper. Reference 11 not only examined APT signal, but also CEST signals at other offsets. Importantly, it applied a distribution-based analysis for CEST analysis. And in this paper the parameters APT10,APT15, ... in fact is also a quantitative desciption of APTw images. Therefore, the old reference 11 should be cited in the method within the "Quantitative analysis of APTW images" part

RESPONSE: Thank you for pointing this out. We have removed the reference from the introduction and have cited it in the “Quantitative analysis of APTW images” part, as a previous instance applying a histogram-based analysis on CEST data (p. 9–10, lines 181–186).

Attachment

Submitted filename: Response to Reviewers.docx

Decision Letter 2

Zhongliang Zu

24 Jul 2020

Correlations of amide proton transfer-weighted MRI of cerebral infarction with clinico-radiological findings

PONE-D-20-12833R2

Dear Dr. Togao,

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