Natural course of apparent diffusion coefficient (ADC) change after brain ischemic stroke: an alternative explanation by the triphasic relationship between T2 and ADC

Recently, we proposed that in vivo apparent diffusion coefficient (ADC) measure is strongly associated with T2 relaxation time (T2) (1-5). In this context, T2 can be divided into short T2 band (<60 ms), intermediate T2 band (60–80 ms), and long T2 band (>80 ms, all 3T values). For the short T2 time band, there is a negative correlation between T2 and ADC. For the long T2 time band, there is a positive correlation between T2 and ADC (Figure 1, Figure S1). A tissue likely measures a low ADC if its T2 is close to 70 ms. On the other hand, a tissue is likely to measure a high ADC if its T2 is far away from 70 ms.

Figure 1 Relationship between T2 time and ADC for various non-brain tissues, 3T data. With parotid gland tumors, ADC from lower to higher ranking: Warthin’s tumor, malignant tumor, benign tumor, PA. Dotted arrow denotes susceptibility T2* black-out, which is observed with structures having a very short intrinsic T2 signal due to very short T2*. In this graph, dotted arrow is for illustration only, and does not reflect true quantitative values for susceptibility T2* black-out. This graph is adapted with permission from (5). ADC, apparent diffusion coefficient; PA, pleomorphic adenoma.

This ‘T2-ADC curve’ shown in Figure 1 can help explain the counterintuitive ADC values commonly seen in several tissues. The liver and the spleen are almost equally perfused. However, the spleen has a much lower ADC value than the liver (spleen: 0.8×10⁻³ mm², liver: 1.1×10⁻³ mm²), we consider this is due to that the spleen has a longer T2 than the liver (spleen: 60 ms, liver 42: ms, 3T values). Experimental studies have shown that the hepatic blood volume including that of the large vessels is about 25 mL/100 g, whereas this value is 3 mL/100 g in skeletal muscle (6). Thus, it could be thought that the ADC of muscles is not higher than that of liver with the liver more richly perfused by hepatic artery and portal vein and with lots of sinusoids and space of Disse. However, muscle has a shorter T2 time than the liver. In the study of Wall et al. (7), muscle measured a T2 of 29 ms whereas liver measured a T2 of 45 ms at 0.35T. In the study of de Bazelaire et al. (8), muscle measured a T2 of 29 ms whereas liver measured a T2 of 46 ms at 1.5T. Figure 1 shows, with liver data as the reference, the shorter T2 of muscle is associated with an increased ADC value for the muscle (relative to the liver). Figure 1 also helps to explain why cartilage and intervertebral disc nucleus pulposus and inner annulus fibrosus measure very high ADC. This is not because these tissues have true high tissue diffusivity, but instead because of their T2 being both away from the intermediate T2 of 60–80 ms (at 3T). Moreover, cartilage and intervertebral disc nucleus pulposus and inner annulus fibrosus demonstrate high ADC due to the opposite reasons, with cartilage having a relatively short T2 and non-degenerated disc having a long T2. Pyogenic abscess fluid (i.e., pus) tends to demonstrate a very low ADC (e.g., 0.63×10⁻³ mm²/s) regardless of the location of the abscess (9-12). We noted that (4), abscess pus having a T2 of around 80 ms contributes to its very low ADC measured by MRI. Lymphoma has a T2 close to 60–70 ms at 3T. For example, Dooms et al. (13) reported a lymphoma mean T2 of 58 ms at 0.35T; Weissleder et al. (14) reported a lymphoma mean T2 of 84 ms and a liver mean T2 of 51 ms at 0.6T (thus, lymphoma will have a mean T2 of around 74 ms at 3T). Consistent with the ‘T2-ADC curve’, lymphoma shows low ADC (15-17). Wu et al. (17) further reported that there was no correlation between the ADC value and cellularity of the tumor in patients with diffuse large B-cell lymphoma and follicular lymphoma. Note that a lack of correlation between ADC and cell density is a common finding in various pathologies (16-21). Morán et al. (22) and Einarsdóttir et al. (23) reported myxoma ADC values of 2.38×10⁻³ and 2.80×10⁻³ mm²/s respectively, which are quite high. Myxoid substance has a long T2, and myxoma has a high ADC likely due to myxoid substance’s long T2. Another disease is chondrosarcoma. Chondrosarcoma has a long T2 (e.g., 120 ms) and high ADC measure [e.g., 2.3×10⁻³ mm² (24)]. It is unlikely that chondrosarcoma has a true high tissue diffusivity. For parotid gland tumors, Warthin’s tumor [T2: 83.3 ms, 3T data of Baohong et al. (25)] is associated with low ADC and pleomorphic adenoma is associated with high ADC [T2: 142.9 ms, 3T data of Baohong et al. (25)]. For pleomorphic adenoma, long T2 (and thus high ADC measure) can be attributed to its myxomatous and chondroid contents (26). For Warthin’s tumor, low ADC can be attributed to its mature lymphocytic components (27,28). Spleen, which also has T2 of around 60 ms at 3T and is associated with low ADC, is also part of the lymphatic system.

For prostate cancer, an injection of gadolinium contrast agent, which shortens T2 of the cancerous tissues and shifts the T2 time of cancerous tissues toward 70 ms, has been noted to be associated with a lower ADC measure without the gadolinium agent actually changing the diffusivity of the tissues (29). For the purpose of evaluating in vivo perfusion, we have been using the subtraction of signal intensity on non-zero low b value images from signal intensity on b=0 image (30-35). Diffusion-derived ‘vessel density’ (DDVD), initially proposed as an imaging biomarker to evaluate liver perfusion (30), is calculated from a simple diffusion MRI protocol as

DDVD(b0b2)=Sb0ROIarea0−Sb2ROIarea2[unit:arbitrary unit(au)/pixel][1]

where Sb0 refers to the measured liver sum signal intensity when b=0 s/mm², and Sb2 refers to the measured liver sum signal intensity when b=2 s/mm². ROI_area0 and ROI_area2 refer to the number of pixels in the selected region-of-interest (ROI) on b=0 and 2 s/mm² images, respectively. Sb2 and ROI_area2 can also be approximated by other low b value diffusion image data (33-35). In a recent study (36), when DDVD was calculated from b=0 and 1 (or 2) s/mm² images, then following the principle that liver and spleen have similar amounts of perfusion, there is little difference between liver DDVD and spleen DDVD. Simple liver cyst shows very low DDVD reflecting there is no perfusion inside the cyst. However, when DDVD was calculated from b=0 and 20 s/mm² images, then, with liver value as the reference, spleen DDVD was ‘suppressed’ due to the spleen T2 being around 60 ms. Since cyst has a long T2 (maybe similar to gallbladder being around 160 ms), liver cyst DDVD calculated from b=0 and 20 s/mm² became higher than liver DDVD (Figure 2). These results further support that T2 of the tissues/fluid always heavily contributes to diffusion metrics computed with ≥ two b values and when these b values are not very close to each other (3,4).

Figure 2 Relationship between the second b value to calculate the DDVD and the absolute DDVD values. Red dots: values of liver parenchyma; orange dots: values of spleen parenchyma; green dots: values of liver simple cyst. DDVD, diffusion-derived ‘vessel density’.

Note that, in addition to T2 (which is often dominant), we consider diffusion indeed contributes to ADC (3). This is also evidenced by the success of the diffusion tensor imaging technique. When a cluster of voxels has a homogeneous T2 value, then their dominant diffusion direction can still be measured.

Brain acute ischemic stroke is a major cause of death and a leading cause of disability globally. Neuroimaging is a cornerstone in the diagnosis and treatment decision-making. It has been well documented that, once a stroke occurs, stroke lesion’s ADC starts to decrease and T2 starts to increase (37-46). In human studies, T2 typically follows a pattern of stepwise gradual increase till plateau (39,44). On the other hand, ADC follows a course of (I) decrease, (II) pseudo-normalization, (III) elevation [note that experimental results based on rodents are different from those of humans, the current analyses are based only on human data (45)]. The initial ADC decrease has been proposed to be due to cytotoxic oedema, which results in cellular swelling and a reduction in the extracellular volume and increased restricted diffusion on MRI. However, the evidence to support this theory of restricted diffusion remains limited.

Using our ‘T2-ADC curve’ (3), we attempt to offer an alternative explanation for the ADC evolution course of stroke lesions. Normal brain tissues are generally noted to have a short T2 with grey/dark signal on T2 weighted image. Wansapura et al. described that, at 3T the average T2 values for occipital and frontal gray matter are 41.6 and 51.8 ms, respectively, and average T2 values for occipital and frontal white matter are 48.4 and 44.7 ms, respectively (47-50). When an abscess develops inside the brain and abscess pus is roughly estimated to have a T2 of around 80 ms (4), according to Figures 1,3 (4,50), an increase of T2 time from grey/white matter values toward 80 ms (at 3T) would be associated with a lower ADC. The same is true for the development of brain lymphoma (13,14,16). Following the examples of brain abscess and lymphoma, an initial increase of T2 of a stroke lesion will lead to a decrease of ADC measure. With the further increase of the lesion’s T2 and when the T2 reaches the value of around 90 ms at 3T or 110 ms at 1.5T (approximately estimated from Figures 1,3), the lesion’s ADC will pseudo-normalize. After that, the stroke lesion’s T2 becomes even longer, and lesion’s ADC will start to show elevated compared to the contra-lateral brain tissue.

Figure 3 Relationship between T2 time and ADC. Normal brain tissue is based on 3T data. Brain lymphoma is based on 3T data (16). Brain glioma is based on 1.5T data (50). Abscess is only based on an estimation. The dotted blue arrow shows, as brain tissue turns into abscess or lymphoma, T2 increases and ADC decreases. The dotted red arrow shows as glioma T2 increases, glioma ADC increases. ADC, apparent diffusion coefficient.

We try to tentatively answer the questions: do we have evidence to show the timepoint of ADC lesion pseudo-normalization is the timepoint when T2 reaches around 90 ms at 3T or around 110 ms at 1.5T? Since it has been shown that pseudo-normalization of stroke lesion’s ADC occurs ‘somewhat’ 10 days after the stroke incident (37-39,42), is stroke lesion’s T2 around 90 ms at 3T or 110 ms at 1.5T 10 days after the stroke incident? According to the report of Lutsep et al. (1.5T data) (39,40), about 5 months after infarction incidence, lesion’s T2-weighted image signal intensity is about ×2 of contra-lateral brain tissue (and appears to be plateaued). Figure 4 shows, if normal brain tissue signal intensity is increased ×2, then the signal intensity will be overall close to the signal intensity of most of the gliomas. Noted that, according to the report of Oh et al. (50), at 1.5T, brain white matter had a median T2 value of 77 ms, and glioma had a median T2 value of 160 ms. According to Lutsep et al. (39) and Lansberg et al. (44), about 10 days after an infarction incidence, lesion’s T2-weighted image signal intensity is about ×1.7 of contra-lateral brain tissue. If normal brain tissue signal intensity is increased ×1.7, then the signal intensity will be lower than the signal intensity of most of glioma tissues shown in Figure 5. It is difficult to estimate how the normal brain tissue corresponds to a ‘new T2 value’ if normal brain tissue signal intensity is elevated by ×1.7, but it is possible that the ‘new T2’ might be around 90–100 ms at 3T and 110–120 ms at 1.5T (roughly approximated based on Figures 3,5).

Figure 4 T2-weighted magnetic resonance images of a random selection of five cases of brain glioma (A and B are the same case). The signal intensity of the contra-lateral brain (A-E) and the lower part of the brain (F) are magnified by ×2 (labeled ×2). For visual comparison a portion of the glioma lesion or edema is cropped (rectangles) and placed on the part of brain with signal intensity magnification (arrows). Overall, the lesion image intensities are comparable to normal brain with signal intensity magnified by ×2.

Figure 5 T2-weighted magnetic resonance images of five cases of brain gliomas (the same as in Figure 4). The signal intensities of the contra-lateral brain (A-E) and the lower part of the brain (F) are magnified by ×1.7 (labeled ×1.7), and for visual comparison a portion of the glioma lesion or edema was cropped (rectangles) and placed on the part of brain with signal intensity magnification (arrows). Overall, the lesion image intensities are higher than normal brain with signal intensity magnified by ×1.7.

In conclusion, for the brain ischemic stroke lesion ADC triphasic evolution course of decrease, pseudo-normalization, and elevation, we propose that this can be explained by the triphasic relationship between T2 and ADC. This model may support the differential diagnosis of various brain abnormalities.

Acknowledgments

The author would like to thank Mr. Ben-Heng Xiao, Research student at the Chinese University of Hong Kong, for the processing of Figures 4,5, and Dr. Ming-Hua Sun, Visting radiologist at the Chinese University of Hong Kong, for providing the raw images used in Figures 4,5.

Funding: This work was supported by Hong Kong GRF Project (No. 14112521).

Footnote

Conflicts of Interest: The author has completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-2383/coif). Y.X.J.W. serves as the Editor-in-Chief of Quantitative Imaging in Medicine and Surgery. The author has no other conflicts of interest to declare.

Ethical Statement: The author is accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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