An explanation for why tissues with T2 of around 70 milliseconds always measure low MRI apparent diffusion coefficient (ADC)

In literature reporting in vivo apparent diffusion coefficient (ADC) results, there exists a ‘T2-ADC curve’, with ADC measure strongly correlated with T2 relaxation time (T2) (1-6). T2 can be divided into short T2 band [<60 milliseconds (ms)], intermediate T2 band (60–80 ms), and long T2 band (>80 ms, all 3.0 T 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. A tissue likely measures a low ADC if its T2 is close to 70 ms (such as the cases of lymphoma and the acute phase of brain ischemic stroke). A tissue is likely to measure a high ADC if its T2 is far away from 70 ms, such as the cases of cartilage (with very short T2 and high ADC), myxoma and chondrosarcoma (both with very long T2 and very high ADC) (4). The spleen (with T2 of around 60 ms, 3.0 T) and parotid gland Warthin’ tumors (with T2 of around 80 ms, 3.0 T) have a low ADC despite having rich blood perfusion. It appears to be unreasonable that the spleen has an ADC of only around 0.8×10⁻³ mm²/s while chondrosarcoma has an ADC of around 2.3×10⁻³ mm²/s (4). It is also puzzling that pyogenic abscess fluid (i.e., pus) tends to demonstrate a very low ADC regardless of the location of the abscess (7-10). It has been suggested that the low ADC of abscess fluid might be related to the high viscosity of the liquid; however, myxoma is known to have a very high ADC value (11,12). We reviewed that the abscess pus is likely to have a T2 of about 70–80 ms, and the specific T2 of pyogenic abscess fluid likely contributes to its very low ADC measured by magnetic resonance imaging (MRI) (3).

We have recently proposed a metric ’slow diffusion coefficient (SDC)’ [unit: arbitrary unit (au)/s]:

SDC=S(b1)−S(b2)b2−b1[1]

where b₁ and b₂ refer to a high b-value (e.g., 500 mm²/s) and a higher b-value (e.g., 800 mm²/s), respectively, S(b₁) and S(b₂) denote the image signal intensity acquired at the high b-value and the higher b-value, respectively (13). A higher SDC value indicates a more rapid signal decay between the two b-values, suggesting faster diffusion within the observed tissue. SDC measure suggests that liver abscess liquid may have a faster diffusion than liver parenchyma (14). SDC measure also suggests that spleen has a faster diffusion than liver and hepatocellular carcinoma (HCC) tends to have a faster diffusion than liver parenchyma (13).

In addition to our earlier discussion on the relationship between T2 and ADC (6), in this letter we propose an explanation why tissues with T2 between 60 and 80 ms always measure a low ADC, and why this low ADC does not necessarily suggest ‘diffusion restriction’.

For in vivo diffusion-weighted (DW) imaging, ADC is typically calculated according to:

ADC=ln(S(b1)/S(b2))b2−b1[2]

where b₂ and b₁ refer to high b-value and low b-value, respectively, S(b₂) and S(b₁) denote the image signal intensity acquired at the high b-value and low b-value, respectively. Although the low b-value can be nominally 0, in reality, the gradient switching for spatial encoding in the slice selection and readout directions always generates b-values greater than 0. This makes it impossible to acquire images with exactly b=0 s/mm². Eq. [2] shows, the greater the signal loss between S(b₁) and S(b₂), the higher the ADC value. As we noted earlier, the DW imaging signal decay between S(b₁) and S(b₂) can be separated into two parts: (I) the ‘slow compartment portion’; and (II) the ‘fast compartment portion’ (6). For the slow compartment portion, as shown in Figure 1 (15-17), the relationship between T2 and the measured ADC appeared to be almost positively linear. For simplicity, we can assume that longer tissue T2 values are highly correlated with higher wateriness, and higher wateriness is, in turn, highly correlated with higher ADC value. In practice, bounded water will have longer T2 yet slower diffusion than free water. The fast compartment portion is, on the other hand, majorly caused by T2-related signal decay between S(b₁) and S(b₂).

Figure 1 Empirical data show positive almost linear relationship between T2 and ADC of brain tumors (A), parotid gland tumors (B), and prostate and its lesions (C). (A) Data are extracted from the study of Oh et al. (15), using a 1.5 T scanner and with ADC based on b-value of 0 and 1,000 s/mm². (B) Data from Baohong et al. (16), ADCs were from two b-values (0 and 1,000 s/mm²) using a 3.0 T scanner. Mean ADC values from lower to higher ranking: Warthin’s tumor, malignant tumor, benign tumor, and pleomorphic adenoma. (C) Data from Hepp et al. (17), ADC was based on b-values =50, 500, 1,000, and 2,000 s/mm² using a 3.0 T scanner. Mean ADC values from lower to higher ranking: prostate cancer, chronic prostatitis, prostate peripheral zone. ADC, apparent diffusion coefficient; ms, millisecond.

The application of diffusion gradients lead to the tissue demonstrating shorter ‘apparent’ (or ‘measured’) T2 (relative to the T2 measured when b=0 s/mm²) (6), thus ‘apparent T2’ = (‘actual T2’ − ΔT2). In a study of breast cancer tissues (3.0 T), Egnell et al. (18) reported that apparent T2 value at b=50 s/mm² was around 8% lower than at b=0 s/mm² (68.7 vs. 74.5 ms). For moving spins, the application of the pair of diffusion gradients will contribute to residual dispersion of ‘spin focusing’ in the transverse plane (even after the application of the second ‘re-focusing’ diffusion gradient), leading to shorting of the measured T2 [or the addition of diffusion gradients will be equivalent to the addition of delta echo time (ΔTE) in terms of the relative measured signal strength]. It is reasonable to assume that, at voxel level, there will be ‘ever-existing’ moving spins, which are also contributed by irregular macroscopic body motion. When the motion probing gradient b-value is increasingly high, even for assumed static voxels, the ‘re-focusing’ by the second diffusion gradient is increasingly less coherent. This phenomenon will be more apparent when the actual T2 of a tissue is very short. For instance, for a tissue where the actual T2 is very short, such as muscle (T2 =32 ms at 3.0 T), the application of diffusion gradients induces major ‘T2-related signal loss between S(b₁) and S(b₂)’, leading to a high ‘fast compartment’ value. That is, for a tissue with actual short T2, the contribution of ΔT2 will be relatively greater than a tissue with actual long T2. As the tissue T2 becomes longer, such as in the spleen (T2 =60 ms), the ‘T2-related signal loss between S(b₁) and S(b₂)’ becomes smaller. When the tissue T2 is longer than 80 ms, this ‘T2-related signal loss between S(b₁) and S(b₂)’ becomes even smaller. Thus, for tissues with a T2 of approximately 70 ms, the ADC contribution from wateriness is small (relative to the tissues with even longer T2), and the ADC contribution from ‘T2-related signal loss between S(b₁) and S(b₂)’ is also small, and the summation of ‘slow compartment portion’ and the ‘fast compartment portion’ remains small, resulting in a low ADC. This is illustrated with Figure 2.

Figure 2 Relationship between T2 and ADC for various tissues using 3.0 T data. The brown line indicates the ‘slow compartment portion’, showing a positive correlation between T2 and its contribution. The blue line indicates the ‘T2 decay associated fast compartment portion’, showing exponential growth in its contribution when T2 is shorter. The yellow line indicates DDVD effect, which is mainly associated with the proportional blood vessel volume of the tissue. The dotted red line indicates the sum of the blue, brown, and red lines, corresponding to the measured ADC. Blue, brown, and red lines are for illustration only, and may not represent exact values. Commonly, tissues with long T2 are less vascularized; however, there should be no intrinsic relationship between T2 and true DDVD measure. The liver has a short T2, contains high proportion of water (about 70%), and it is heavily vascularized. However, liver measures a lower ADC than that of prostate peripheral zone. This could be because liver has higher iron concentration and the high T2* susceptibility effect, and this lowers its ADC value. T2* susceptibility effect, even at low level, may have a very notable contribution to ADC measure. The background graph, excluding the blue, brown, and red lines, is adapted with permission from (4). For parotid gland tumors, the ADC values, ranked from lowest to highest, are as follows: Warthin’s tumor, malignant tumor, benign tumor, and PA. The dotted arrow denotes susceptibility-related T2* black-out. ADC, apparent diffusion coefficient; DDVD, diffusion-derived ‘vessel density’; ms, millisecond; PA, pleomorphic adenoma.

The application of diffusion gradients induces the shorter ‘measured’ T2 than the ‘actual’ T2 (18). If we want to assume T2 to be unchanged following the application of diffusion gradients, from the viewpoint of measuring magnetic resonance (MR) signal, it can also be conceptually seen as the application of diffusion gradients is associated with an additional TE (ΔTE), leading to an ‘apparent TE’ = (‘actual TE’ + ΔTE). This conceptual equivalence has also been empirically shown by a number of IVM studies. It is shown that, if the TE is increased during DW imaging data acquisition, there is an associated increase in the ‘perfusion fraction’ (‘PF’) (Figure 3) (19-21). IVIM-‘PF’ can be understood as the proportional signal loss for the fast compartment, due to T2-related signal loss as well as perfusion. This observation is equivalent to that, when liver parenchyma develops HCC and there is an increase of T2 from around 40 ms in normal liver tissue to around 60 ms (3.0 T) in HCC, the measured ‘PF’ decreases, even though HCC is commonly associated with higher perfusion (22). Though in reality, spleen and liver have very similar amounts of perfusion, due to the longer T2 of the spleen than the T2 of the liver, the IVIM-‘PF’ of the spleen is measured at only half of that of the liver (23). These observations suggest the dominant role of ‘T2-related signal loss between different diffusion gradients’ in determining the IVIM-‘PF’, over the actual contribution from perfusion.

Figure 3 IVIM studies show if the TE is increased for DW imaging data acquisition, measured ‘PF’ increases. ‘PF’ is understood as the proportional signal loss for the fast compartment due to T2-related signal decay as well as perfusion. (A) Following the increase of TE, ‘PF’ increases. (B) The equivalent of (A) with X-axis showing T2 increases (precise T2 values could not be obtained). From MRI signal viewpoint, an increase of TE is equivalent to a relative decrease of T2 (with T2 at b=0 s/mm² as the reference). Data are from Lemke et al. (19), Jerome et al. (20), and Führes et al. (21). DW, diffusion-weighted; IVIM, intravoxel incoherent motion; MRI, magnetic resonance imaging; ms, millisecond; PF, perfusion fraction; TE, echo time.

In the case of HCC, these lesions are mostly associated with increased blood supply and increased proportion of arterial blood supply and higher water content (i.e., edema, as shown with higher signal on T2-weighted image and with lower density on X-ray CT). Perfusion CT also shows HCCs have a shorter mean transit time (MTT) than adjacent liver parenchyma [8.1±3.1 s for HCC and 14.9±2.3 s for liver parenchyma, according to the report by Sahani et al. (24)]. However, the longer T2 time of HCC (approximately, HCC: 60 ms, liver: 40 ms, 3.0 T) lead to its lower ADC value than that of liver parenchyma. In the case of liver fibrosis, it has been well reported that liver fibrosis is commonly associated with higher liver water content and longer T2 value (25-30); particularly, extracellular fluid excess is a common condition in advanced liver cirrhosis patients with ascites. Liver fibrosis has been measured to be with lower ADC (31-34). It is likely that the longer T2 of the fibrotic livers majorly contributes to the lower ADC of these livers. Our preliminary data show that, due to the higher water content in cirrhotic livers, cirrhotic livers have a faster diffusion as measured by the metric SDC (unpublished results). Liver cirrhosis also induced pathophysiological changes in the spleen (35-41). With a 1.5 T scanner, Mesropyan et al. (36) reported that, compared with those of healthy controls, cirrhotic livers with portal hypertension had longer T2 (53.72±7.56 vs. 48.58±8.41 ms) and higher extracellular volume fraction (ECV) values (45%±18.55% vs. 26.14%±2.31%). Compared with healthy controls, spleen in liver cirrhosis patients also had longer T2 (113.17±18.72 vs. 98.83±11.69 ms) and ECV values (42.53%±6.29% vs. 25.82%±2.40%). Similar trends have been described by Özyurt et al. (37) though with livers with milder fibrosis severity. It is interesting to note that, while a cirrhosis-related liver T2 increase (an increase started from a normal value of around 40 ms, 3.0 T) always leads to a reduction of liver ADC, cirrhosis-related spleen T2 increase (an increase started from a normal value of around 60 ms, 3.0 T) often leads to an elevation of spleen ADC (38-41). In a patient study, Subbiah et al. (40) reported that the Model for End-Stage Liver Disease (MELD) score was negatively correlated with liver ADC but positively correlated with spleen ADC. In a miniature pig liver fibrosis model induced by injection of carbon tetrachloride, Chen et al. (41) described that the spleen ADC values (1.5 T) corresponded to normal physiology and four stages of liver fibrosis (stage 4 is cirrhosis). The data showed a decrease of spleen ADC from ‘normal liver’ to ‘stage 2 liver fibrosis’, and an increase of spleen ADC from ‘stage 2 liver fibrosis’ to ‘stage 4 liver fibrosis’, with stage 2 liver fibrosis associated with the lowest spleen ADC (Figure 4). Therefore, with the elongation of spleen T2 caused by progressive liver fibrosis/cirrhosis, spleen ADC can pass the ‘ADC valley bottom’ and reach the phase of positive correlation between T2 and ADC (>70 ms, 3.0 T).

Figure 4 Spleen ADC tri-phasic changes following the progress of liver fibrosis severity and the associated elongation of spleen T2, based on a study of a miniature pig liver fibrosis model induced by injection of carbon tetrachloride. Other factors might also have contributed to the spleen ADC changes, but cannot fully explain the tri-phasic change pattern. F0: normal spleen; F1, F2, F3, F4: stage 1, stage 2, stage 3, stage 4 liver fibrosis; ADC_b0b300 and ADC_b0b500: ADC values calculated from b=0 and b=300 s/mm², or b=0 and b=500 s/mm², respectively. This graph is plotted according to the data reported by Chen et al. (41). ADC, apparent diffusion coefficient.

We have proposed the metric diffusion-derived ‘vessel density’ (DDVD) (unit: au/pixel) (42-44), which is derived from the equation:

DDVDb0b1=S(b0)ROIarea0−S(b1)ROIarea1[3]

where ROIarea0 and ROIarea1 refer to the number of pixels in the selected region-of-interest (ROI) on b=0 and b=1 s/mm² DW image, respectively. S(b₀) refers to the measured sum signal intensity within the ROI when b=0, and S(b₁) refers to the measured sum signal intensity within the ROI when b=1 s/mm², thus Sb/ROIarea equates to the mean signal intensity within the ROI. S(b₁) and ROIarea1 can also be approximated by other low b-values (such as b=10 s/mm²) DW images. DDVD can be practically useful for the evaluation of a variety of diseases such as liver hemangioma (45), liver focal nodular hyperplasia (46), placentas of preeclampsia pregnancy (47), placenta accreta spectrum (48), etc. It is noted that, based on DDVD measure, HCC tends to have a higher perfusion than liver parenchyma and the spleen, and the liver have similar amounts of perfusion (49,50).

Empirical observations also showed relative T2-dependent change of DDVD value following the increase of the 2^ndb-value (the 1^stb-value being 0 s/mm²). Figure 5 (46,50) shows the phenomenon that, for tissues with T2 shorter than 70 ms, a stronger pair of diffusion gradients (i.e., higher b-value) leads to a greater DDVD increase for tissues with an even shorter T2, with a greater DDVD meaning a greater signal loss between the b=0 image and the 2^ndb-value image. The liver has a shorter T2 than that of the spleen (46 vs. 80 ms, 1.5 T; 40 vs. 60 ms, 3.0 T). When the 2^ndb-value is 1 or 2 s/mm², DDVD_liver and DDVD_spleen are very similar; when 2^ndb-value is ≥7 s/mm², DDVD_liver is measured higher than DDVD_spleen (Figure 5A) (50). On average HCCs have a shorter T2 than liver metastasis tumors. Figure 5B shows, as 2^ndb-value changes from 10 to 80 s/mm², DDVD_HCC changes from being measured lower than DDVD_mets to being measured higher than DDVD_mets. These data suggest that a stronger pair of diffusion gradients is associated with a shorter measured ‘ΔT2’ (or a longer ‘conceptual ΔTE’). On the other hand, Figure 5C shows, for liver cyst which has a very long T2, when the 2^ndb-value is 20 s/mm², the contribution from slow diffusion (i.e., the wateriness) is so much that, the measured DDVD_cyst is higher than the DDVD values of the liver and spleen. According to the DDVD principle, cyst liquid has no perfusion, so when 2^ndb-value is 1 or 2 s/mm², liver cyst measures very low DDVD values (Figure 5C).

Figure 5 Relative T2-dependent change of DDVD values following the increase of the 2^ndb-value. Generally, following the increase of the 2^ndb-value (the 1^stb-value =0), DDVD for all tissues increases. (A) Due to the shorter T2 of the liver relative to the spleen, following the increase of the 2^ndb-value, DDVD_liver increases greater than DDVD_spleen. (B) Due to the shorter T2 of HCC relative to Mets (statistically, HCC has a shorter T2 than Mets), following the increase of the 2^ndb-value, DDVD_HCC increases greater than DDVD_mets. (C) Due to the very long T2 of liver cyst (estimated 170 ms, 3.0 T), following the increase of the 2^ndb-value, DDVD_cyst increases greater than DDVD_liver and DDVD_spleen. (A,C) Reused with permission from (50), and (B) reused with permission from (46). Au, arbitrary unit; DDVD, diffusion-derived ‘vessel density’; HCC, hepatocellular carcinoma; Mets, metastasis.

In conclusion, in this letter, we describe an explanation why tissues with T2 between 60 and 80 ms always measure a low ADC. While the relative T2-dependent change of DDVD following the increase of the 2^ndb-value will require more empirical data to elaborate, a low 2^ndb-value of ≤10 s/mm² is recommended to minimize the T2 effect.

Acknowledgments

None.

Footnote

Funding: None.

Conflicts of Interest: The author has completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-aw-2199/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/.

References

1. Wáng YXJ, Zhao KX, Ma FZ, Xiao BH. The contribution of T2 relaxation time to MRI-derived apparent diffusion coefficient (ADC) quantification and its potential clinical implications. Quant Imaging Med Surg 2023;13:7410-6. [Crossref] [PubMed]
2. Wáng YXJ, Ma FZ. A tri-phasic relationship between T2 relaxation time and magnetic resonance imaging (MRI)-derived apparent diffusion coefficient (ADC). Quant Imaging Med Surg 2023;13:8873-80. [Crossref] [PubMed]
3. Wáng YXJ. The very low magnetic resonance imaging apparent diffusion coefficient (ADC) measure of abscess is likely due to pus's specific T2 relaxation time. Quant Imaging Med Surg 2023;13:8881-5. [Crossref] [PubMed]
4. Wáng YXJ, Aparisi Gómez MP, Ruiz Santiago F, Bazzocchi A. The relevance of T2 relaxation time in interpreting MRI apparent diffusion coefficient (ADC) map for musculoskeletal structures. Quant Imaging Med Surg 2023;13:7657-66. [Crossref] [PubMed]
5. Wáng YXJ. Natural course of apparent diffusion coefficient (ADC) change after brain ischemic stroke: an alternative explanation by the triphasic relationship between T2 and ADC. Quant Imaging Med Surg 2024;14:9848-55. [Crossref] [PubMed]
6. Wáng YXJ. An explanation for the triphasic dependency of apparent diffusion coefficient (ADC) on T2 relaxation time: the multiple T2 compartments model. Quant Imaging Med Surg 2025;15:3779-91. [Crossref] [PubMed]
7. Feraco P, Donner D, Gagliardo C, Leonardi I, Piccinini S, Del Poggio A, Franciosi R, Petralia B, van den Hauwe L. Cerebral abscesses imaging: A practical approach. J Popul Ther Clin Pharmacol 2020;27:e11-24. [Crossref] [PubMed]
8. Erdogan C, Hakyemez B, Yildirim N, Parlak M. Brain abscess and cystic brain tumor: discrimination with dynamic susceptibility contrast perfusion-weighted MRI. J Comput Assist Tomogr 2005;29:663-7. [Crossref] [PubMed]
9. Harish S, Chiavaras MM, Kotnis N, Rebello R. MR imaging of skeletal soft tissue infection: utility of diffusion-weighted imaging in detecting abscess formation. Skeletal Radiol 2011;40:285-94. [Crossref] [PubMed]
10. Castillo S, Manterola C. Morphological characteristics of liver abscesses according its etiology. Int J Morphol 2020;38:406-14.
11. Morán LM, Vega J, Gómez-León N, Royuela A. Myxomas and myxoid liposarcomas of the extremities: Our preliminary findings in conventional, perfusion, and diffusion magnetic resonance. Acta Radiol Open 2022;11:20584601221131481. [Crossref] [PubMed]
12. Einarsdóttir H, Karlsson M, Wejde J, Bauer HC. Diffusion-weighted MRI of soft tissue tumours. Eur Radiol 2004;14:959-63. [Crossref] [PubMed]
13. Xu FY, Xiao BH, Wáng YXJ. The rationale for proposing a magnetic resonance slow diffusion metric and its proof-of-concept testing showing spleen parenchyma and hepatocellular carcinoma have faster diffusion than liver parenchyma. Quant Imaging Med Surg 2025;15:3792-806. [Crossref] [PubMed]
14. Ling GH, Wáng YXJ. MRI slow diffusion coefficient (SDC) shows liver pyogenic abscess has faster diffusion than adjacent liver parenchyma. Quant Imaging Med Surg 2025;15:6547-51. [Crossref] [PubMed]
15. Oh J, Cha S, Aiken AH, Han ET, Crane JC, Stainsby JA, Wright GA, Dillon WP, Nelson SJ. Quantitative apparent diffusion coefficients and T2 relaxation times in characterizing contrast enhancing brain tumors and regions of peritumoral edema. J Magn Reson Imaging 2005;21:701-8. [Crossref] [PubMed]
16. Baohong W, Jing Z, Zanxia Z, Kun F, Liang L, Eryuan G, Yong Z, Fei H, Jingliang C, Jinxia Z. T2 mapping and readout segmentation of long variable echo-train diffusion-weighted imaging for the differentiation of parotid gland tumors. Eur J Radiol 2022;151:110265. [Crossref] [PubMed]
17. Hepp T, Kalmbach L, Kolb M, Martirosian P, Hilbert T, Thaiss WM, Notohamiprodjo M, Bedke J, Nikolaou K, Stenzl A, Kruck S, Kaufmann S. T2 mapping for the characterization of prostate lesions. World J Urol 2022;40:1455-61. [Crossref] [PubMed]
18. Egnell L, Jerome NP, Andreassen MMS, Bathen TF, Goa PE. Effects of echo time on IVIM quantifications of locally advanced breast cancer in clinical diffusion-weighted MRI at 3 T. NMR Biomed 2022;35:e4654. [Crossref] [PubMed]
19. Lemke A, Laun FB, Simon D, Stieltjes B, Schad LR. An in vivo verification of the intravoxel incoherent motion effect in diffusion-weighted imaging of the abdomen. Magn Reson Med 2010;64:1580-5. [Crossref] [PubMed]
20. Jerome NP, d'Arcy JA, Feiweier T, Koh DM, Leach MO, Collins DJ, Orton MR. Extended T2-IVIM model for correction of TE dependence of pseudo-diffusion volume fraction in clinical diffusion-weighted magnetic resonance imaging. Phys Med Biol 2016;61:N667-80.
21. Führes T, Riexinger AJ, Loh M, Martin J, Wetscherek A, Kuder TA, Uder M, Hensel B, Laun FB. Echo time dependence of biexponential and triexponential intravoxel incoherent motion parameters in the liver. Magn Reson Med 2022;87:859-71. [Crossref] [PubMed]
22. Ma FZ, Wáng YXJ T. (2) relaxation time elongation of hepatocellular carcinoma relative to native liver tissue leads to an underestimation of perfusion fraction measured by standard intravoxel incoherent motion magnetic resonance imaging. Quant Imaging Med Surg 2024;14:1316-22. [Crossref] [PubMed]
23. Yu WL, Xiao BH, Ma FZ, Zheng CJ, Tang SN, Wáng YXJ. Underestimation of the spleen perfusion fraction by intravoxel incoherent motion MRI. NMR Biomed 2023;36:e4987. [Crossref] [PubMed]
24. Sahani DV, Holalkere NS, Mueller PR, Zhu AX. Advanced hepatocellular carcinoma: CT perfusion of liver and tumor tissue--initial experience. Radiology 2007;243:736-43. [Crossref] [PubMed]
25. Schober O, Mariss P, Schmidt FW, Hundeshagen H. Total body water, extracellular water, plasma volume, and total body potassium in cirrhosis of the liver. Klin Wochenschr 1979;57:757-61. [Crossref] [PubMed]
26. Nishikawa H, Yoh K, Enomoto H, Ishii N, Iwata Y, Nakano C, Takata R, Nishimura T, Aizawa N, Sakai Y, Ikeda N, Hasegawa K, Takashima T, Iijima H, Nishiguchi S. Extracellular Water to Total Body Water Ratio in Viral Liver Diseases: A Study Using Bioimpedance Analysis. Nutrients 2018;10:1072. [Crossref] [PubMed]
27. Kishino K, Enomoto H, Shimono Y, Moriwaki EI, Nishikawa H, Nishimura T, Iwata Y, Iijima H, Nishiguchi S. Association of an Overhydrated State With the Liver Fibrosis and Prognosis of Cirrhotic Patients. In Vivo 2020;34:1347-53. [Crossref] [PubMed]
28. Guimaraes AR, Siqueira L, Uppal R, Alford J, Fuchs BC, Yamada S, Tanabe K, Chung RT, Lauwers G, Chew ML, Boland GW, Sahani DV, Vangel M, Hahn PF, Caravan P. T2 relaxation time is related to liver fibrosis severity. Quant Imaging Med Surg 2016;6:103-14. [Crossref] [PubMed]
29. Zhang H, Yang Q, Yu T, Chen X, Huang J, Tan C, Liang B, Guo H. Comparison of T2, T1rho, and diffusion metrics in assessment of liver fibrosis in rats. J Magn Reson Imaging 2017;45:741-50. [Crossref] [PubMed]
30. Hoffman DH, Ayoola A, Nickel D, Han F, Chandarana H, Shanbhogue KP. T1 mapping, T2 mapping and MR elastography of the liver for detection and staging of liver fibrosis. Abdom Radiol (NY) 2020;45:692-700. [Crossref] [PubMed]
31. Wáng YXJ, Wang X, Wu P, Wang Y, Chen W, Chen H, Li J. Topics on quantitative liver magnetic resonance imaging. Quant Imaging Med Surg 2019;9:1840-90. [Crossref] [PubMed]
32. Taouli B, Chouli M, Martin AJ, Qayyum A, Coakley FV, Vilgrain V. Chronic hepatitis: role of diffusion-weighted imaging and diffusion tensor imaging for the diagnosis of liver fibrosis and inflammation. J Magn Reson Imaging 2008;28:89-95. [Crossref] [PubMed]
33. Kocakoc E, Bakan AA, Poyrazoglu OK, Dagli AF, Gul Y, Cicekci M, Bahcecioglu IH. Assessment of Liver Fibrosis with Diffusion-Weighted Magnetic Resonance Imaging Using Different b-values in Chronic Viral Hepatitis. Med Princ Pract 2015;24:522-6. [Crossref] [PubMed]
34. Kahraman AS, Kahraman B, Ozdemir ZM, Gormeli CA, Ozdemir F, Dogan M. Diffusion-weighted imaging (DWI) of the liver in assessing chronic liver disease: effects of the presence and the degree of ascites on ADC values. Abdom Radiol (NY) 2016;41:56-62. [Crossref] [PubMed]
35. Zheng CJ, Huang H, Xiao BH, Li T, Wang W, Wáng YXJ. Spleen in viral Hepatitis-B liver fibrosis patients may have a reduced level of per unit micro-circulation: non-invasive diffusion MRI evidence with a surrogate marker. SLAS Technol 2022;27:187-94. [Crossref] [PubMed]
36. Mesropyan N, Isaak A, Faron A, Praktiknjo M, Jansen C, Kuetting D, Meyer C, Pieper CC, Sprinkart AM, Chang J, Maedler B, Thomas D, Kupczyk P, Attenberger U, Luetkens JA. Magnetic resonance parametric mapping of the spleen for non-invasive assessment of portal hypertension. Eur Radiol 2021;31:85-93. [Crossref] [PubMed]
37. Özyurt GM, Esen K, Üçbilek E, Apaydın FD. Liver/spleen magnetic resonance elastography and T1/T2 mapping in chronic liver disease: a prospective study. Rev Assoc Med Bras (1992) 2024;70:e20241008.
38. Klasen J, Lanzman RS, Wittsack HJ, Kircheis G, Schek J, Quentin M, Antoch G, Häussinger D, Blondin D. Diffusion-weighted imaging (DWI) of the spleen in patients with liver cirrhosis and portal hypertension. Magn Reson Imaging 2013;31:1092-6. [Crossref] [PubMed]
39. Razek AA, Massoud SM, Azziz MR, El-Bendary MM, Zalata K, Motawea EM. Prediction of esophageal varices in cirrhotic patients with apparent diffusion coefficient of the spleen. Abdom Imaging 2015;40:1465-9. [Crossref] [PubMed]
40. Subbiah K, Ayyamperumal B, Chellathurai A, Gnanasigamani S, Balasubramaniam S, Kannappan S. Diagnostic utility of ADC value of the spleen in assessing severity of portal hypertension in cirrhosis. J Evolution Med Dent Sci 2018;7:2814-8.
41. Chen XL, Chen TW, Zhang XM, Li ZL, Li H, Zeng NL, Tang HJ, Pu Y, Chen N, Yang Q, Li L, Xie XY, Hu J. Spleen magnetic resonance diffusion-weighted imaging for quantitative staging hepatic fibrosis in miniature pigs: An initial study. Hepatol Res 2013;43:1231-40. [Crossref] [PubMed]
42. Wáng YXJ. Living tissue intravoxel incoherent motion (IVIM) diffusion MR analysis without b=0 image: an example for liver fibrosis evaluation. Quant Imaging Med Surg 2019;9:127-33. [Crossref] [PubMed]
43. Ma FZ, Xiao BH, Wáng YXJ. MRI signal simulation of liver DDVD (diffusion derived 'vessel density') with multiple compartments diffusion model. Quant Imaging Med Surg 2025;15:1710-8. [Crossref] [PubMed]
44. Xiao BH, Huang H, Wang LF, Qiu SW, Guo SW, Wáng YXJ. Diffusion MRI Derived per Area Vessel Density as a Surrogate Biomarker for Detecting Viral Hepatitis B-Induced Liver Fibrosis: A Proof-of-Concept Study. SLAS Technol 2020;25:474-83. [Crossref] [PubMed]
45. Hu GW, Li CY, Ling GH, Zheng CJ, Zhu MSY, Sabarudin A, Duan XH, Li XM, Shen J, Wáng YXJ. A combination of MRI diffusion-derived vessel density (DDVD) and slow diffusion coefficient (SDC) can reliably diagnose liver hemangioma: a testing of three centers’ data. J Gastrointest Oncol 2025;16:2336-56. [Crossref] [PubMed]
46. Zheng CJ, Yao DQ, Li CY, Duan XH, Zhang G, Yan ZH, Shi GZ, Li XM, Shen J, Wáng YXJ. Lower diffusion-derived vessel density (DDVD) measure of liver focal nodular hyperplasia than those of hepatocellular carcinoma and liver metastasis allows potential differential diagnosis: quantitative and semi-quantitative analyses of two-center data. J Gastrointest Oncol 2025;16:1144-56. [Crossref] [PubMed]
47. He J, Chen C, Xu L, Xiao B, Chen Z, Wen T, Wáng YXJ, Liu P. Diffusion-Derived Vessel Density Computed From a Simplified Intravoxel Incoherent Motion Imaging Protocol in Pregnancies Complicated by Early Preeclampsia: A Novel Biomarker of Placental Dysfunction. Hypertension 2023;80:1658-67. [Crossref] [PubMed]
48. Lu T, Yao DQ, Xiao BH, Sheng W, Chen M, Wáng YXJ. The relevance of placenta MRI diffusion-derived vessels density and morphological features in diagnosing placenta accreta spectrum. BMC Med Imaging 2025;25:180. [Crossref] [PubMed]
49. Li XM, Yao DQ, Quan XY, Li M, Chen W, Wáng YXJ. Perfusion of hepatocellular carcinomas measured by diffusion-derived vessel density biomarker: Higher hepatocellular carcinoma perfusion than earlier intravoxel incoherent motion reports. NMR Biomed 2024;37:e5125. [Crossref] [PubMed]
50. Ju ZG, Leng XM, Xiao BH, Sun MH, Huang H, Hu GW, Zhang G, Sun JH, Zhu MSY, Guglielmi G, Wáng YXJ. Influences of the second motion probing gradient b-value and T2 relaxation time on magnetic resonance diffusion-derived 'vessel density' (DDVD) calculation: the examples of liver, spleen, and liver simple cyst. Quant Imaging Med Surg 2025;15:74-87. [Crossref] [PubMed]