The impacts of time of echo and time of repetition on slow diffusion coefficient (SDC) measure and the potential age- and gender-related variations in liver and spleen SDC values: studies of healthy volunteers

Introduction

Diffusion weighted imaging (DWI) plays a pivotal role in magnetic resonance imaging (MRI) evaluation of a variety of pathologies. For example, in the case of liver, DWI at high b-values provides a low background signal from normal liver parenchyma and thereby results in increased contrast between the background liver and lesions. DWI is especially useful in the detection of small lesions around vessels and in the periphery of the liver. However, in addition to tissue perfusion and diffusion, apparent diffusion coefficient (ADC) is also substantially affected by tissue T2 (i.e., the so called ‘T2-shine through’), and this can lead to erroneous results in many scenarios (1-6). Empirical evidence strongly suggests that there exists a ‘T2-ADC curve’. T2 values can be divided into three bands: short T2 band [<60 milliseconds (ms)], intermediate T2 band (60–80 ms), and long T2 band (>80 ms, 3.0 T). For the short T2 time band, there is a negative correlation between T2 and ADC. Conversely, for the long T2 time band, there is a positive correlation between T2 and ADC. A tissue is likely to measure a low ADC if its T2 is close to 70 ms (such as the case with lymphoma and the acute phase of brain ischemic stroke). On the other hand, a tissue is likely to measure a high ADC if its T2 is far away from 70 ms (being much shorter than 70 ms or much longer than 70 ms). This can explain many of the initially puzzling observations. For example, solid cartilage has a high ADC due to a very short T2, chondrosarcoma has a very high ADC value (2.3×10⁻³ mm²/s) due to its very long T2 (2). The spleen (with a T2 of around 60 ms at 3.0 T, ADC of only around 0.8×10⁻³ mm²/s) and parotid gland Warthin’ tumors (with a T2 of around 80 ms at 3.0 T) have low ADCs despite having rich blood perfusion (4,7). Pyogenic abscess fluid (i.e., pus) tends to demonstrate a very low ADC regardless of the location of the abscess, due to that the abscess pus is likely to have a T2 of about 70–80 ms (5). Mechanistic explanation for this ADC ‘T2-shine through’ has been recently provided (3,4). The new DWI metric slow diffusion coefficient (SDC) was proposed aiming to mitigate the difficulties associated with the ‘T2-shine through’ of ADC (8). In its basic form, SDC is derived from the subtraction of a high b-value DWI image (e.g., b=400 s/mm²) and a higher b-value DWI (e.g., b=600 s/mm²). With SDC analysis, the spleen has a faster diffusion than the liver, hepatocellular carcinoma (HCC) has a faster diffusion than liver parenchyma, liver hemangiomas have a faster diffusion than simple liver cysts, and liver pyogenic abscess has faster diffusion than adjacent liver parenchyma. These results are more reasonable than the conventional ADC values. The impacts of data acquisition time of echo (TE) and time of repetition (TR) on ADC have been described. In one study (9), an increase in TE was associated with an increase in ADC value for the liver and for the spleen; while an increase in TR was associated with a decrease in ADC value for the liver and the spleen. One of the goals of the current study is to investigate the impact of TE and TR on SDC values of the liver and the spleen.

An age-related decline of liver ADC values both for men and for women has been described by many authors (10-12). Yu et al. described an age-related decline of spleen ADC values for women, but not for men with men’s normative values showing a high level of heterogeneity (13). Following aging, there is a reduction in the liver perfusion as measured by physiological/histological methods (14-16) and as well as by a DWI metric diffusion-derived ‘vessel density’ (DDVD) which reflects tissue perfusion (12,17,18). It is likely that age-related reduction of liver perfusion contributes to the age-related reduction of liver ADC to a varying degree depending on the b-values to calculate the ADC (12,19). Liver steatosis also leads to a lower liver ADC (20-22). Bülow et al. (21) described that ADC decreased significantly with steatosis grade in subjects without iron and fibrosis. In general populations, liver fat content increases with age. Compared to men, liver iron concentration in women remains relatively low until menopause, after which there is a steep increase (16). Liver/spleen iron is negatively correlated to their T2* values. Schwenzer et al. (23) reported a negative correlation between age and liver T2* in women (r=−0.46) and in men (r=−0.30). A shorter liver T2* depresses ADC measure (11,21,24). Therefore, a lower perfusion level but a higher liver fat content and a higher iron liver level can lead to a reduction in ADC. Whether there is a true diffusion decrease of liver/spleen following aging remains not clarified. Another goal of this study is to investigate whether there is an age-related reduction of liver slow diffusion as measured by SDC.

Methods

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The healthy volunteer upper abdomen MRI data acquisition was approved by the institutional ethical committees, and informed consent was obtained for all subjects. All the study participants were all known to be healthy at the MRI exam and at the 6-month follow-up after the exam, without liver, spleen, or other abdominal organ disease history, and not on any regular medication.

To test the impact of TR and TE on SDC value, liver and spleen DWI data acquisition was conducted with young healthy volunteers (dataset 1, three men aged between 26 and 32 years, three women aged between 28 and 30 years). DWI scan utilized a single-shot spin-echo echo-planar sequence with a 3.0 T magnet (Ingenia Elition X, Philips Healthcare, Best, Netherlands). Fat suppression was achieved using the Spectral Attenuated Inversion Recovery (SPAIR) technique. Scan parameters included slice thickness of 5 mm, slice gap of 1 mm, acquisition matrix of 64×56, field of view of 350 mm × 350 mm, number of excitations (NEX) =1, and slice number of 20. When TE was considered as a variable and changed with steps of TE =46, 52, 60, 70, 80 ms, TR was fixed at 2,000 ms. When TR was considered as a variable and changed with steps of TR =200, 300, 500, 1,000, 2,000 ms, TE was fixed at 46 ms. The b-values included 0, 1, 2, 10, 400, and 600 s/mm². During the scan, the study participants were instructed to have shallow free breathing (25,26). In addition to standard dummy scans, multiple scans were continuously acquired in each session. For all acquired MRI data, images with notable motion and artifact were discarded. Only images with b-values of 400 and 600 s/mm² were used in this study.

To test the potential age and gender related changes of liver and spleen SDC values, liver and spleen DWI data acquisition was conducted with healthy volunteers (dataset 2). For all scans, participants were asked to fast for 6 hours before imaging. Study subjects were scanned twice during the same session as long as the study subject could tolerate being within the magnet and lied still, with the subjects’ position and selected scan planes unchanged. The intravoxel incoherent motion (IVIM) type of diffusion scan was based on a single-shot spin-echo type echo-planar sequence using a 1.5-T magnet (Achieva, Philips Healthcare, Best, Netherlands). Fat suppression was achieved using the SPAIR technique. Image data were acquired with respiratory-gating. The TR was 1,600 ms and the TE was 63 ms, with one TR per respiratory cycle. Other parameters included slice thickness =7 mm and inter-slice gap 1 mm, matrix =124×97, FOV =375 mm × 302 mm, NEX =2, number of slices =7. The included slices were focused on the central part of the liver with the largest axial parenchyma. IVIM series images with 16 b-values of 0, 2, 4, 7, 10, 15, 20, 30, 46, 60, 72, 100, 150, 200, 400, 600 s/mm² were acquired (12). Only images with b-values of 400 and 600 s/mm² were used in this study. The DWI acquisition window was limited only to the expiratory phase while dummied to the inspiratory phase (27). For all acquired MRI data, images with notable motion and artefacts were discarded. Finally included for analysis in this study were 68 men (mean age: 50.2 years, range: 25–70 years) and 43 women (45.6 years, range: 20–71 years). In this study, the median natural menopause age was assumed to be 51 years (28), and the post menopause effect on the liver and spleen was well seen by the age of 54 years.

SDC was calculated according to:

SDC=[S(b1)−S(b2)]/(b1−b2)[unit:arbitraryunit(au)/s][1]

where b₁ and b₂ refer to a high b-value (i.e., 400 mm²/s) and a higher b-value respectively (i.e., 600 mm²/s), where S(b₁) and S(b₂) denote the DW image signal-intensity acquired at the b-value of 400 and 600 mm²/s respectively. A higher SDC value indicates a more rapid signal decay between the two b-values, reflecting faster diffusion.

Image segmentation was performed using ITK-SNAP (http://www.itksnap.org) and data analysis was conducted with MATLAB (MathWorks, Natick, MA, USA). Free-hand regions-of-interest (ROIs) were manually placed on b=400 s/mm² image to cover a large portion of liver and spleen parenchyma while avoiding large vessels and then copied on to b=600 s/mm² images of this slice. To account for the potential inter-scan motion, the copied ROIs on b=600 s/mm² images were additionally manually adjusted.

For all analysis, the mean of all included slices’ measurements was regarded as the value of the examination, with the last step weighted by the percentage ROI area for each slice (i.e., assuming the sum pixel number of all ROIs for each subject being 100%, according to pixel number in each slice’s ROI, a percentage was assigned for each slice).

For dataset 1, the impact of TE and TR on ADC and DDVD had been measured and reported by us (9), and those results were compared with the results of the current study. For dataset 2, the age and gender related changes in ADC and DDVD had been measured and reported by us (12). The values of ADC_b0b600 (i.e., ADC calculated with b=0 and b=600 s/mm² images), ADC_b60b600 (i.e., ADC calculated with b=60 and b=600 s/mm² images), and DDVD_b0b2 (i.e., DDVD calculated with b=0 and b=2 s/mm² images) were reused in this study to allow a comparison with the SDC values obtained in this study. The ROIs were broadly the same as in the current study, except for the adjustment to the respiration caused motion.

For statistical analysis, data were processed using GraphPad Prism (San Diego, CA, USA). Comparisons were performed using the Kruskal-Wallis test. The significances of diffusion measures and ages were tested with Pearson correlation. A P value <0.05 was considered statistically significant.

Results

Data 1 showed that, following the increase in TE from 46 to 80 ms, the SDC value decreased by a median value of 63.9% for the liver and a median value of 31.0% for the spleen. The SDC_spleen/SDC_liver ratio increased by a median value of 150.3% (Table 1, Figure 1). Following the increase in TR from 200 to 2,000 ms, there was an increase in SDC value by a median value of 478% for the liver, and there was a biphasic change in spleen SDC value. Spleen SDC value was highest when TR was 1,000 ms, and SDC values were equally low when TR was 200 and 2,000 ms. SDC_spleen/SDC_liver ratio was approximately unchanged following the increase in TR (Table 1, Figure 2).

Figure 1 Changes in SDC value (in box-and-whiskers plot) following the increase in TE from 46 to 80 ms [(A) liver; (B) spleen], and the SDC_spleen/SDC_liver ratio (C). (A) P<0.0001; (B) P=0.0837; (C) P<0.0001, all by Kruskal-Wallis test. n: number of scans. SDC, slow diffusion coefficient; TE, time of echo.

Figure 2 Changes in SDC value (in box-and-whiskers plot) following the increase in TR from 200 to 2,000 ms [(A) liver; (B) spleen], and the SDC_spleen/SDC_liver ratio (C). (A) P=0.0329; (B) P<0.0001; (C) P=0.9199, all by Kruskal-Wallis test. n: number of scans. SDC, slow diffusion coefficient; TR, time of repetition.

Data 2 showed that, there was no age-related change in SDC value for men’s liver (r=0.091), for men’s spleen (r=0.059), and for the livers of women aged <54 years (n=27, r=0.006). There was an age-related decrease in SDC value for the livers of women of all ages (n=43 inclusive of those aged ≥54 years, r=−0.376, P=0.013), for women’s spleen (r=−0.400 and P=0.040 for aged <54 years; r=−0.558 and P=0.0001 for all female volunteers, Figure 3). The liver median SDC values were ‘women aged <54 years (0.099 au/s)’ > ‘women >54 years (0.072 au/s)’ > ‘men (0.055 au/s)’. The spleen median SDC values were also ‘women aged <54 years (0.189 au/s)’ > ‘women >54 years (0.105 au/s)’ > ‘men (0.083 au/s)’, which followed the same trend as that of the liver. For all comparisons, the spleen values were higher than the liver values (Figure 4).

Figure 3 Age-related changes of liver (A-C) and spleen SDC (D-F) values for male volunteers and female volunteers. The Spearman rs=0.41 (P=0.0063) in (C). F, female; M, male; SDC, slow diffusion coefficient; yrs, years.

Figure 4 A comparison between the SDC values of male volunteers and female volunteers, and the SDC values of the liver and spleen. F, female; M, male; SDC, slow diffusion coefficient.

Re-using the recently published results with data of the same volunteers acquired during the same scan sessions with the same TR, TE, and spatial resolutions, data 2 showed, for men’s liver, the strength of negative correlation was: ADC_b0b600 > DDVD_b0b2 > ADC_b60b600 > SDC_b400b600 (minimal). For the livers of women aged <54 years (n=27), the strength of negative correlation was: ADC_b0b600 > ADC_b60b600 > DDVD_b0b2 > SDC_b400b600 (minimal). For the livers of women of all ages (n=43), the strength of negative correlation was approximately the same for SDC_b400b600, ADC_b0b600, ADC_b60b600, and DDVD_b0b2. For men’s spleen, the strength of negative correlation was: ADC_b60b600 > ADC_b0b600 > DDVD_b0b2 (minimal) > SDC_b400b600 (minimal). For the spleens of women aged <54 years (n=27), the strength of negative correlation was: ADC_b60b600 = SDC_b400b600 > ADC_b0b600 > DDVD_b0b2. For the spleens of women of all ages (n=43), the strength of negative correlation was: SDC_b400b600 > ADC_b60b600 > ADC_b0b600 > DDVD_b0b2 (Figure 5).

Figure 5 Comparisons of Pearson r value of correlation between age and DWI metrics (ADC_b0b600, ADC_b60b600, DDVD_b0b2, and SDC_b400b600) for men and women, for the liver (A-C) and for the spleen (D-F). ADC, apparent diffusion coefficient; DDVD, diffusion-derived ‘vessel density’; DWI, diffusion weighted imaging; F, female; M, male; SDC, slow diffusion coefficient.

Discussion

The new DWI metric SDC has shown practical application in various scenarios. For example, in a study of 63 patients with diffuse gliomas [30 isocitrate dehydrogenase (IDH)-mutant and 33 IDH-wildtype], IDH mutant negative tumors had SDC_b500b750 value of 0.339±0.055 au/s, IDH mutant positive tumors had SDC_b500b750 value of 0.437±0.097 au/s, with an area under receiver operating characteristic curve (AUROC) of 0.828 for separation. IDH mutant negative tumors had ADC_b0b1000 value of 0.985±0.235 mm²/s, IDH mutant positive tumors had ADC_b0b1000 value of 1.290×10⁻³±0.381×10⁻³ mm²/s, with an AUROC of 0.760 for separation. Thus, SDC as a biomarker offers a better lesion differentiation power than ADC. A combination of DDVD, ADC, and SDC achieved an AUROC of 0.9 for separating IDH-mutant and IDH-wildtype gliomas (29,30). In studies of parotid gland tumors, DDVD ratio (DDVDr), SDC ratio (SDCr), and ADC ratio (ADCr) were the metrics of the tumor divided by the metrics of tumor free parotid gland tissue. A combination of ADCr_b0b800, SDCr_b600b800, and DDVDr_b20 separated parotid gland malignant tumors (MTs) and benign tumors (i.e., Warthin’s tumors and pleomorphic adenomas) with an AUROC of 0.805 (31). Based on the T2 weighted image signal and these three metrics of DDVD, SDC, and ADC, we applied a scoring scheme termed ‘LiverMss-FNH’ to evaluate liver solid mass. In two studies totaling 25 focal nodular hyperplasia (FNH) and 132 liver MTs, LiverMss ≥3.0 suggests the possibility of a liver mass being FNH, and LiverMss ≥4 can strongly favor the diagnosis for FNH (32,33). A typical SDC signal, i.e., being iso-signal or slightly high signal (but not high signal), has an odd ratio of 38 suggesting the diagnosis of liver FNH against liver MTs (32,33). More recently, we showed that, a liver mass with an iso-signal or slightly high DDVD signal while with an SDC higher or equal to that of the kidneys suggested the possibility of this mass being intrahepatic cholangiocarcinoma with an odds ratio of 34.7 favoring intrahepatic cholangiocarcinoma against HCC (34).

This study investigated two aspects concerning SDC: the impact of TR and TE on the SDC, and age and gender-related changes of SDC value for the liver and the spleen. These two aspects are related, as an increase of liver/spleen iron and thus the shortening of T2* of these two organs would be equivalent to an increase in TE from MRI signal perspective, allowing a faster signal decay. We recently described that, following the increase in TE from 46 to 80 ms, ADC_b0b600 value increases by 23.9% (median) for the liver and 18.2% (median) for the spleen. The ADC_spleen/ADC_liver ratio is lower when TE is longer (9). Following the increase in TR from 200 to 2,000 ms, ADC_b0b600 value decreases by 4.8% (median) for the liver and 14.6% (median) for the spleen. The ADC_spleen/ADC_liver ratio is lower when TR is longer. As TE increased, DDVD_b0b2 decreased by 37.9% (median) for the liver and 17.0% (median) for the spleen. DDVD value is determined by the difference in signal strength between the b=0 image and the nonzero low b-value image (for example, 2 or 10 s/mm²); therefore, a longer TE, or a shorter ‘measured’ T2, decreases the signal strength difference between these two DWI images. As the liver has a shorter T2 than the spleen, this TE dependence of DDVD is more apparent for the liver than for the spleen. Therefore, when TE is longer, spleen DDVD was measured higher relative to the liver (9). The current study shows, following the increase in TE from 46 to 80 ms, SDC value decreased by a median value of 63.9% for the liver and a median value of 31.0% for the spleen. The SDC_spleen/SDC_liver ratio increased by a median value of 150.3%. As the liver has a shorter T2 than the spleen, this TE dependence of SDC was also more apparent for the liver than for the spleen. When TE was longer, spleen SDC was measured higher relative to the liver. Therefore, the SDC response to the increasing TE value was to the opposite of that of ADC, whereas it was the same pattern as that of the DDVD. Following the increase in TR from 200 to 2,000 ms, there was a biphasic change in DDVD value, both for the liver and for the spleen. Liver and spleen DDVD values were highest when TR was 500 ms, and DDVD values were lowest at 200 ms (9). In the current study, as TR increased, liver SDC increased. For the spleen, SDC measured highest when TR was 1,000 ms. SDC_spleen/SDC_liver ratio was approximately unchanged following the increase in TR.

It should be noted that, during the interpretation of ADC map, DDVD map, and SDC map, the relative ratio is practically more useful. For example, a liver lesion is considered as ‘low SDC or high SDC’ compared with the adjacent liver parenchyma, and spleen parenchyma is also often used as the reference tissue. The liver and spleen have markedly different T2/T1 values (approximately, liver T2: 40 ms, spleen T2: 60 ms, liver T1: 800 ms, spleen T1: 1,300 ms, 3.0 T data). Spleen has a T2 similar to most of the HCC (i.e., around 60 ms at 3 T), but with a perfusion similar to that of the liver (35,36). It has been reported that an implanted spleen tissue in the liver mimics liver cancer (37). By maximizing the SDC contrast between the spleen and the liver (i.e., maximizing SDC_spleen/SDC_liver ratio), the contrast between a liver cancer and the liver is also potentially maximized. For tissues with T2 of around 40–60 ms, it has been shown that, by applying a longer TE such as 80 ms or a very short TR such as 300 ms, the DDVD of tissues with longer T2 such as the spleen will be measured higher than tissues with shorter T2 such as the liver, thus the DDVD_spleen/DDVD_liver ratio will be higher (38). For the separation of liver FNH and liver MT, a modestly long TE (such as 80 ms) has been shown to improve the classification (36,38). The same may be applied to the SDC. For the separation of liver FNH and liver cancer, a modestly long TE (such as 80 ms) might improve the classification (32,33). When TE is longer, the SDC of liver cancers (which mostly have a richer perfusion and a longer T2) would be measured even higher relative to the liver.

Physiology of liver aging has been well studied. Macroscopically the liver undergoes ‘brown atrophy’ with old age. The brown appearance is secondary to the accumulation of pigmented waste products within hepatocytes. Hepatocytes in elderly subjects contain denser body compartments, such as secondary lysosomes and lipofuscin, than do hepatocytes in younger subjects (39). Lipofuscin accumulation has been associated with chronic oxidative stress and a failure to degrade damaged and denatured proteins (40). At the cellular level, hepatocytes grow in size but decrease in numbers with age (41). Mitochondria of hepatocytes increase in size but decrease in overall number with age (42). Post-mortem studies suggest that there is an age-related fall in liver volume. It is estimated that, compared with those under 40 years of age, individuals above the age of 65 years have 25–35% lower liver volume (43). T1rho relaxometry studies also showed shorter liver T1rho and spleen T1rho among older subjects which may not relate to their iron level (44-46), reflecting biochemical changes among the older subjects. Physiological age-related decrease in liver blood flow has been well documented using a variety of technical methods including histology, dye dilution, indicator clearance, as well as DDVD (14-16). In general populations, liver fat content increases with age. Nonalcoholic fatty liver disease (NAFLD) is common among assumed healthy populations. Epidemiological studies show male predominance of NAFLD from the paediatric population up to fifth decade of life in adults. After the age of 60 years, women overtake their male counterparts in the prevalence of NAFLD. One ultrasonographic study of 26,527 Chinese subjects (age: 47.41±10.13 years, range: 20–70 years) receiving medical health check-ups shows NAFLD prevalence was 31% in men and 16% in women (47). Kühn et al. (48) quantified liver proton density fat fraction in a population-based study of 2,561 German participants (1,336 women; median age, 52 years), and reported the median fat fraction was 3.9% (range, 0.6–41.5%). In men, liver-fat content increased continuously between age 20 and 50 years; in women, liver fat content increase began 20 years later, extending from 40 to 65 years (48). In healthy subjects without diet iron deficiency, liver iron concentration rises sharply in men toward the end of the adolescent growth spurt in the late teens and reached maximum before 40 years old. After 40 years old, liver iron level remains constant or slightly increases until approximately age 70 years. In women, liver iron concentration remains relatively low until after the fourth decade of life, after which they exhibit a steep rise. Maximum levels observed in women after menopause are approximately two thirds of those for men of comparable age (49-51). This study shows, as measured by SDC, there was no age-related change in slow diffusion for women aged <54 years and for men. On the other hand, there was a fast reduction of SDC for women >54 years. With the same study cohort of dataset 2, we recently reported that there was a statistically significant age-related decline of liver ADC_b0b600 values both for men and for women (12). Three factors can have contributed to the decline of liver ADC following aging, i.e., a reduction of vessel volume, an increase of liver fat, and an increase of liver iron in post-menopausal women, rather than true restricted diffusion. It has been well established that a higher liver fat level and a higher liver iron level led to decreased liver ADC measure (11,20-24). Vessel volume reduction as shown by histology studies and DDVD measure will contribute to the age-related reduction of ADC. For the livers of men, Figure 5 shows the negative correlation was strongest for ADC_b0b600, followed by ADC_b60b600. This can be explained by that ADC_b0b600 reflects the age-related reduction of both perfusion and the ‘apparent diffusion’ as measured by ADC_b60b600. The correlation was the weakest for SDC. It should be noted that diffusion metric measurement is more stable for the liver than for the spleen, as the spleen is smaller in size (13). By using high b-values to calculate SDC, the perfusion compartment is eliminated. Note that, the size of a water molecule is 280 picometers. If we consider the size of a hepatocyte is 25 µm in diameter, then the size ratio of a water molecule to a hepatocyte is about 1/100,000. If we consider the size of a spleen cell is 6.5 µm in diameter, then the size ratio of a water molecule to a hepatocyte is about 1/26,000. Hepatic sinusoids (about 10–15 µm in diameter) are also quite ‘big’ considering the size of a water molecule. Water molecules may be freer to move inside vivo tissue than we anticipated. This study also suggests the possibility that liver fat content has no impact on the liver SDC measure, though this should be confirmed with more studies with high grade steatotic livers.

Following menopause, women’s liver iron level increase, and the increased susceptibility effect, i.e., shortening of T2*, likely contributed to the SDC declining for older women. In the current study, this SDC change in post-menopausal women’s liver was very substantial. Different to that of the liver, there was an age-related decline of spleen SDC for women even for the pre-menopausal women. The cause of this could not be investigated in this study, but could be due to that there is an age-related gradual increase in iron level in the spleen before menopause (thus, an age-related gradual shortening of spleen T2*).

The higher SDC for the spleen than for the liver is consistent with that T2* is shorter for the liver than for the spleen (23), and spleen is waterier than the liver. The spleen is an organ storing blood. The spleen has a longer T2 than the liver, and the spleen has a lower computed tomography (CT) density than the liver. From the MRI signal measurement point of view, as shown in Figure 1, a longer T2 can be seen as equivalent to a shorter TE which is associated with a higher SDC. The higher liver and spleen SDC values for women than for men can be also explained by the lower iron level and thus the longer T2* for women than for men. Physiologically, blood volume per unit tends to be higher for women than for men (52,53), liver DDVD and spleen DDVD are also measured higher for women than for men (12,54). As blood has a long T2 value (55-57), the longer blood-related T2 in the liver and spleen for women than for men may also be associated with a higher SDC for women’s liver and spleen.

It is intriguing that T2* and T2 had an impact on liver ADC value in the opposite direction, while T2* and T2 had an impact on SDC value in the same direction. A shorting of liver T2* (e.g., a higher liver iron level) leads to both a lower liver ADC value and a lower liver SDC value [the same can be said that an elongation of T2* (e.g., a lower liver iron level) leads to both a higher ADC value and a higher SDC value] (Figure 3) (11,21). An elongation of T2 (such as the development of HCC with edema) leads to a lower ADC measure but a higher SDC value (1,3,9,19). This is also consistent with that a longer TE is associated with an increase in the liver ADC measure but a decrease of SDC measure.

There are a number of limitations to this study. For dataset 1, the volunteer of numbers was limited. When TR was short (such as 200 ms), the noise level was high. To increase the signal strength and shorten the scan duration, we applied a low matrix size which led to a large pixel size and low resolution. For dataset 1, we did not scan TR higher than 2,000 ms. The goal of this study was to study the TE and RE impact on SDC in trend, rather than specific TR and TE values. To speed up the data acquisition, in our studies we usually use TR ≤2,000 ms for DWI (such as the case for dataset 2). For dataset 2, we did not have data for pediatric and adolescent populations. We did not have liver steatosis patients to test the impact of a higher-level liver fat on liver SDC. We did not provide intra- and inter-observer variability data for SDC measurement, though we do not expect this to be an issue as the ROI placements are reasonably straightforward.

Conclusions

In conclusion, this study demonstrates the TE and TR have very notable impacts on the SDC values of the liver and spleen. The liver and the spleen respond in different magnitudes for their respective SDC values following the TE/TR changes. There may be no true tissue diffusion change following aging both for men and women. The difference in liver SDC between pre-menopausal women value and post-menopausal women value suggest that iron-related T2* shortening lead to a lower SDC measure. While SDC is sensitive to T2*, SDC may be insensitive to perfusion volume and fat signal. We expect the findings of this study will be relevant for diffusion metrics as biomarkers of liver diseases classification, as well as for understanding physiology related to gender differences and aging for the liver and spleen.

Acknowledgments

Parts of the research was conducted at CUHK MRI Facility, which received instruments support from Kai Chong Tong, HKSAR Research Matching Grant Scheme and the Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong.

Footnote

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2026-1-0319/dss

Funding: National Key Research and Development Program of China (2022YFC2305105); General Project of the Basic Research Program, Natural Science Foundation of Shenzhen (JCYJ20240813101907011).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2026-1-0319/coif). Y.X.J.W. serves as the Editor-In-Chief of Quantitative Imaging in Medicine and Surgery. Y.X.J.W. is the founder of Yingran Medicals Ltd., which develops medical image-based diagnostics software. The metric DDVD is associated with a granted China patent (ZL201910125747.2). The metric SDC is associated with a pending patent application (Y.X.J.W. and F.Y.X.). The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are 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. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The healthy volunteer upper abdomen MRI data acquisition was approved by the institutional ethical committees, and informed consent was obtained for all subjects.

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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