|Year : 2022 | Volume
| Issue : 2 | Page : 230-235
Fluid-attenuated inversion recovery diffusion-weighted imaging (DWI) for evaluating chemotherapy response in patients with acute leukemia: Comparison with conventional DWI
Xue Tian1, Jinliang Niu2, Wenjin Li3, Xiaohong Joe Zhou4, Wenqi Wu2, Xiaojun Li2, Jun Wang2, Hongwei Wang5
1 Department of Radiology, Shanxi cardiovascular hospital, Taiyuan, Shanxi, China
2 Department of Radiology, the Second Hospital, Shanxi Medical University, Taiyuan, Shanxi, China
3 Department of Stomatology, the Second Hospital, Shanxi Medical University, Taiyuan, Shanxi, China
4 Department of Radiology, Neurosurgery, and Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA; Department of Clinical Molecular Biology Lab, the Second Hospital, Shanxi Medical University, Taiyuan, Shanxi, China
5 Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, Illinois, USA
|Date of Submission||28-Aug-2019|
|Date of Decision||06-Oct-2020|
|Date of Acceptance||19-Dec-2020|
|Date of Web Publication||16-Jul-2021|
Department of Radiology, the Second Hospital, Shanxi Medical University, Taiyuan, Shanxi
Source of Support: None, Conflict of Interest: None
Background: At present, the diagnosis and efficacy evaluation of acute leukemia (AL) are assessed by bone marrow aspiration, which is invasive and subject to sampling errors. Therefore, there is a pressing need to develop a noninvasive and accurate imaging method to evaluate bone marrow changes in patients with AL. This study aimed to compare the apparent diffusion coefficient (ADC) values obtained from fluid-attenuated inversion recovery diffusion-weighted imaging (FLAIR-DWI) and conventional DWI in the lumbar bone marrow of patients with AL and to investigate their performance for evaluating response to induction chemotherapy.
Methods: A total of 28 patients with newly diagnosed AL and 25 patients with AL after induction chemotherapy underwent MRI scans at 1.5 Tesla using a conventional DWI and a FLAIR-DWI sequence on sagittal planes covering the lumbar bone marrow. Further, the ADC values from these two sequences, denoted as ADCCON and ADCFLAIR, were measured on multiple vertebrae. The percentage of leukemia cells in bone marrow was recorded, and bone marrow aspiration was performed on treated patients to determine complete remission (CR) and nonremission (NR).
Results: ADCFLAIR [(0.453 ± 0.103) × 10−3 mm2/s] was significantly lower than ADCCON [(0.486 ± 0.096) × 10−3 mm2/s] in the 28 untreated patients (t = 3.051, P = 0.005). In the 25 treated patients, ADCFLAIR and ADCCON values [(0.566 ± 0.239) × 10−3 mm2/s] and [(0.716 ± 0.235) × 10−3 mm2/s], respectively, were higher compared with the untreated patients. The ADCCON values showed a nonsignificant difference between the CR (n = 18) and NR (n = 7) groups (t = 1.409, P = 0.305). However, the ADCFLAIR values exhibited statistically significant difference (t = 2.542, P = 0.018) between the two groups. In a receiver operator characteristic (ROC) analysis, the area under the curve (AUC) using ADCFLAIR (0.770) was larger than that of ADCCON (0.611) in distinguishing the CR and NR patients following the chemotherapy.
Conclusion: Although both ADCCON and ADCFLAIR are sensitive to tissue changes induced by chemotherapy, FLAIR-DWI outperformed conventional DWI in separating AL patients with CR from NR after chemotherapy. A possible mechanism is that FLAIR-DWI suppresses signals from free water, making the ADC measurement more sensitive to structural changes in the bone marrow.
Keywords: Acute leukemia (AL), bone marrow, chemotherapy response, diffusion-weighted imaging (DWI), fluid-attenuated inversion recovery (FLAIR)
Fluid-attenuated inversion recovery diffusion-weighted imaging can suppress free water signal in the apparent diffusion coefficient measurement , outperformed conventional diffusion-weighted imaging in efficacy evaluation of acute leukemia.
|How to cite this article:|
Tian X, Niu J, Li W, Zhou XJ, Wu W, Li X, Wang J, Wang H. Fluid-attenuated inversion recovery diffusion-weighted imaging (DWI) for evaluating chemotherapy response in patients with acute leukemia: Comparison with conventional DWI. Indian J Cancer 2022;59:230-5
|How to cite this URL:|
Tian X, Niu J, Li W, Zhou XJ, Wu W, Li X, Wang J, Wang H. Fluid-attenuated inversion recovery diffusion-weighted imaging (DWI) for evaluating chemotherapy response in patients with acute leukemia: Comparison with conventional DWI. Indian J Cancer [serial online] 2022 [cited 2022 Sep 28];59:230-5. Available from: https://www.indianjcancer.com/text.asp?2022/59/2/230/321674
| » Introduction|| |
Diffusion-weighted imaging (DWI) is an magnetic resonance imaging (MRI) technique that is sensitive to tissue microenvironment and microstructures affecting the Brownian motion of water molecules., Following its success in brain and body applications, DWI has been increasingly used in musculoskeletal MRI examinations. Major applications of DWI in the musculoskeletal system include characterization of primary soft-tissue neoplasm, detection of bone metastasis, and assessment of treatment response.,, Conventionally, the treatment response of marrow disorders are assessed by invasive iliac crest biopsy, which is invasive and subject to sampling errors. Therefore, there is a pressing need to develop a noninvasive and accurate imaging method to manage bone marrow diseases. As a quantitative imaging biomarker, the apparent diffusion coefficient (ADC) obtained from DWI has been increasingly used for monitoring treatment response and evaluating prognosis in several hematologic malignancies such as multiple myeloma and lymphoma.,,
Acute leukemia (AL) is one of the hematologic malignancies that progresses over weeks to months ultimately culminating in bone marrow failure. This marrow disease is typically treated with standard induction chemotherapy. Imaging method to monitor response to the treatment, however, has not been well established other than a very limited number of DWI studies. During chemotherapy, many changes such as tumor cell necrosis, cytolysis, sinus expansion, and exudation can lead to the increased content of extracellular free water in the marrow of patients with AL, resulting in an increase in ADC value., The percentage of primitive leukemia cells in the bone marrow has been conventionally employed as an indicator for evaluating treatment response. In a typical voxel of DWI, the increased presence of extracellular free water compromises the sensitivity of ADC to monitoring changes in primitive leukemia cells owing to the partial volume effect. We, therefore, hypothesize that incorporating fluid-attenuated inversion recovery (FLAIR) into DWI can be an effective way to suppress the contribution of free water molecules to the ADC measurement, making the ADC value (denoted as ADCFLAIR) more sensitive to changes in primitive leukemia cells than the ADC value (denoted as ADCCON) from conventional DWI, which is analogous to what has been reported for identifying the reversible ischemic injury., This study aims to test this hypothesis by comparing changes in ADCFLAIR and ADCCON in the lumbar bone marrow of patients with AL before and after standard induction chemotherapy and investigate the utility of ADCFLAIR and ADCCON for distinguishing remission versus nonremission.
| » Materials and Methods|| |
The study was conducted in the Second Hospital of Shanxi Medical University, and approved by the ethics committee of the performing site. Diagnosis of AL was made according to the World Health Organization (WHO) classification of hematopoietic tissue., The patient inclusion criteria were as follows: (a) absence of prior chemotherapy, (b) no other abnormalities in the vertebral bodies, (c) stable vital signs for an MRI examination, and (d) no contraindications to MRI examination at 1.5 Tesla (T).
Between January 2018 and October 2018, a total of 28 patients, comprising 16 male and 12 female (age range: 15–77 years), with newly clinically diagnosed AL were recruited. Meanwhile, an additional 25 patients (age range: 15–70 years) who received standard induction chemotherapy were also examined.
MR imaging of the lumbar vertebral bone marrow was performed on a GE Signa 1.5 Tesla MRI scanner (GE Healthcare, Waukesha, Wisconsin) using an 8-channel phased-array spine coil. The imaging protocol included routine fast spin-echo sagittal T1-weighted (TR 400.0 milliseconds (ms); TE 9.3 ms; section thickness 5.0 millimeter (mm); spacing 0.0 mm; NEX 4; FOV 36 centimeter (cm) × 36 cm; matrix 320 × 192; acquisition time 2 minutes (min) 29 seconds (s), conventional DWI (b = 0,500 s/mm2 with trace-weighting using three successive diffusion gradients along the orthogonal axes; TR 4000.0 ms; TE 66.5 ms; section thickness 5.0 mm; spacing 0.0 mm; NEX 4; FOV 36 cm × 28.8 cm; matrix 128 × 96; acquisition time 2 min 12 s), and FLAIR-DWI with parameters identical to those in the conventional DWI sequence except for the following parameters (TR 10000 ms; TE 66.3 ms; TI 2500 ms; acquisition time 2 min 45 s).
The diffusion-weighted images were analyzed on an Advantage Windows Workstation 4.4 (GE Healthcare, Waukesha, Wisconsin) where both ADCFLAIR and ADCCON maps were calculated using commercial software FuncTool from the corresponding datasets. Regions of interest (ROIs) were selected centrally in the lumbar vertebral cancellous bone (L1–L5), which was intended to minimize the effect caused by vertebral end-plate, vertebral venous plexus, and cerebrospinal fluid. The vertebral bodies with an irregular shape, such as wedging of the vertebra, vertebrae with Schmorl's nodes, and vertebral growth deformity, were excluded from the analysis. Using these criteria, 3 to 5 lumbar vertebral bodies were measured in each patient, and the average value across all ROIs within an exam was taken as the ADC value of the patient. The ROI-based individual ADCCON and ADCFLAIR values were expressed as mean ± standard deviation (x¯±s).
Two comparisons between ADCCON and ADCFLAIR were made using paired t-tests. To demonstrate the sensitivity of ADC to treatment-induced tissue changes, the first comparison was focused on pre-and posttreatment ADC variations for all patients without subdividing them into CR and NR groups. The second comparison aimed at evaluating the specificity to CR versus NR patients using ADCCON and ADCFLAIR, respectively. Both comparisons were performed using Statistical Package for the Social Sciences (SPSS) software (IBM Corporation, Armonk, New York). A P value of 0.05 was chosen to declare statistical significance. Using the clinical results from bone marrow aspiration as a reference, a receiver operating characteristic (ROC) analysis was performed to determine the area under the curve (AUC) when using ADCCON or ADCFLAIR for distinguishing CR from NR patients after the standard induction chemotherapy.
| » Results|| |
Patient grouping and the number of vertebral bodies measured in patients with AL
After induction chemotherapy, based on the conventional criteria for treatment response, 18 out of the 25 patients achieved complete remission (CR) with the median bone marrow blasts proportion reduced to 1.5% (0.5%–4.5%) assessed by bone marrow aspiration. Seven patients did not reach complete remission (nonremission, NR) with a median bone marrow blasts proportion of 26.5% (8%–45%).
A total of 114 vertebral bodies of the 28 untreated patients were analyzed, together with 113 vertebral bodies from the treated patients (80 vertebral bodies from the 18 CR patients and 33 vertebral bodies from the seven NR patients). The mean ROI size was 218 mm2 with a range of 142–285 mm2.
Comparison of all patients before and after treatment
The mean ADCFLAIR value [(0.453 ± 0.103) × 10−3 mm2/s] of the 28 untreated patients was lower than the mean ADCCON [(0.486 ± 0.096) × 10−3 mm2/s]. The difference was statistically significant (t = 3.051, P = 0.005), as detailed in [Table 1] and [Figure 1]. After treatment, the mean ADCFLAIR of the 25 patients [(0.566 ± 0.239) × 10−3 mm2/s] was higher compared with the untreated patients, but remained lower than the mean ADCCON [(0.716 ± 0.235) × 10−3 mm2/s]. The mean ADCCON was also higher after therapy compared with untreated patients. The difference between ADCFLAIR and ADCCON in patients posttreatment was also statistically significant (t = 6.795, P < 0.001; as detailed in [Table 1] and [Figure 1]).
|Figure 1: ADCCON (upper row; a-c) and ADCFLAIR (lower row; d-f) maps for three individual patients. A 15-year-old woman before treatment with average ADCCON = 0.557 × 10−3 mm2/s (a) and ADCFLAIR = 0.492 × 10−3 mm2/s (d); a 42-year-old man after treatment with CR [ADCCON = 0.869 × 10−3 mm2/s (b) and ADCFLAIR = 0.784 × 10−3 mm2/s (e)]; and a 38-year-old man after treatment with NR [ADCCON = 0.592 × 10−3 mm2/s (c) and ADCFLAIR = 0.306 × 10−3 mm2/s(f)]|
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|Table 1: Comparison of ADC values (×10-3 mm2/s) before and after chemotherapy for all AL patients|
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Comparison of CR and NR patients
After treatment, the mean ADCCON [(0.637 ± 0.225) × 10−3 mm2/s] of the NR patients was lower than that [(0.747 ± 0.237) × 10−3 mm2/s] of the CR patients. The difference, however, was not statistically significant (t = 1.409, P = 0.305; [Table 2] and [Figure 1]). In contrast, the mean ADCFLAIR [(0.408 ± 0.263) × 10−3 mm2/s] of the NR patients was significantly lower than that [(0.617 ± 0.194) × 10−3 mm2/s] of the CR patients (t = 2.542, P = 0.018; [Table 2] and [Figure 1]). When ADCFLAIR was used for differentiating the CR and NR patient groups, the ROC analysis produced an AUC of 0.770, whereas the AUC was reduced to 0.611 while using ADCCON [Figure 2]. ADCFLAIR outperformed ADCCON in evaluating the chemotherapy response.
|Figure 2: Comparison of ROC curves of using ADCCON and ADCFLAIR for distinguishing CR from NR on the 25 patients with AL following induction chemotherapy. ADCFLAIR shows a higher AUC (0.770) than ADCCON (AUC = 0.611)|
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|Table 2: Comparison of ADC values (×10-3 mm2/s) for patients with CR and NR after chemotherapy|
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| » Discussion|| |
DWI has been used for differential diagnosis between benign and malignant bone marrow disease and, more recently, for assessing its response to treatment.,, The ADC value is superior to biopsy for tissue characterization in situations such as detection of necrosis, which can be identified by ADC before observable changes on histology in hematological malignancy of bone marrow. It was also reported that the ADC value of active myeloma was significantly higher than the marrow in remission. For patients with newly diagnosed AL, induction chemotherapy is presently a standard treatment strategy. However, very limited imaging studies have been reported to describe the effect of the infiltrated bone marrow in AL patients following chemotherapy. Ballon et al. observed that the ADC values in AL approximately tripled its baseline value only 14 days into chemotherapy. Our results showing that the ADCCON values of the treated patients were higher than that of untreated patients [Figure 1] and [Table 1], which are consistent with Ballon's findings. In addition, ADCFLAIR also exhibited significant changes between the treated and untreated patient groups, but with a lower sensitivity (i.e., a smaller ADC change) than ADCCON [Table 1]. Importantly, we observed that the ADCCON value was not significantly different between the CR and NR patients, which has not been reported previously. This observation revealed a possible limitation of the conventional ADC values.
Using FLAIR-DWI, ADCFLAIR was able to show the difference between the CR and NR patient groups. Unlike conventional DWI, FLAIR-DWI suppresses free water signals and thus considerably reduces their contribution to ADC calculations. In general, successful chemotherapy causes tumor cell death, resulting in increased water mobility and, consequently, increased ADC values. With induction chemotherapy on the AL patients, the toxicity of the chemotherapeutic drugs leads to several pathophysiological changes in the bone marrow, including tumor necrosis, apoptosis, cytolysis, and dilated and hyperpermeable sinus. All of these factors can contribute to elevated water mobility. However, the changes induced by the chemotherapeutic agent can be masked by the presence of background free water, which explains the insignificant difference in the ADCCON value between the CR and NR groups. In contrast, FLAIR-DWI can effectively suppress the background free water, making ADCFLAIR more sensitive than ADCCON, as indicated by our results in [Table 2]. This explanation is also consistent with other studies on identifying reversible ischemic injury using FLAIR-DWI.,,
Presently, the percent of blasts of the bone marrow is the primary indicator in diagnosis and evaluating response to treatment of AL. The bone marrow samples are usually taken from the back of the pelvic (hip) bone, but it is repeated several times to probe whether the leukemia is responding to treatment. Our results showed that the ADCFLAIR was significantly different between CR and NR patients and the ADCFLAIR AUC of 0.770 was larger than that for ADCCON (AUC=0.611) in evaluating treatment response [Figure 2]. The comparison between treated and untreated patient groups [Table 1] and [Figure 1] indicates that both ADCCON and ADCFLAIR are sensitive to tissue changes induced by chemotherapy. Although ADCCON exhibited better sensitivity to treatment (i.e., a larger change in the ADC value), its specificity to CR versus NR was inferior to ADCFLAIR.
Our study has several limitations. Firstly, all evaluations were performed at 1.5 T. However, the recent installation of a 3 T magnet has allowed the research to be continued at the higher field strength. Secondly, theoretically, a TI of 2500 ms would be optimal to suppress free water (such as the signals from the cerebrospinal fluid at 1.5 T). However, at this optimal TI, we still observed measurable free water signals in the spinal canal. Thus, free water suppression in this study was suboptimal. Thirdly, a simple monoexponential model was used in our ADC calculations. The effect of tissue microcapillary perfusion, for example, can be removed using an intravoxel incoherent motion (IVIM) diffusion model. In addition, more sophisticated non-Gaussian diffusion models may provide additional insights into microstructural changes of the bone marrow during induction chemotherapy., Finally, the number of patients enrolled in this study was moderate, particularly in the NR group due to the difficulty in keeping the critically ill patients on the protocol.
Despite these limitations in this study, we have demonstrated that both ADCCON and ADCFLAIR are sensitive to treatment-induced tissue changes following induction chemotherapy on AL patients. Although ADCCON exhibited better sensitivity to treatment (i.e., a larger change in the ADC value), its specificity to CR versus NR was inferior to ADCFLAIR. More importantly, FLAIR-DWI can suppress a significant confounding factor—free water signal—in ADC measurement in the bone marrow of patients with AL, resulting in the superior performance of ADC values from the FLAIR-DWI sequence than the conventional ADC values for assessing treatment response in patients with AL.
Financial support and sponsorship
This work was supported in part by a grant from the National Institute of Health Grant No. 1S10RR028898. Research Project Supported by Shanxi Scholarship Council of China.No. 2016-119.
Conflicts of interest
There are no conflicts of interest.
| » References|| |
Subhawong TK, Jacobs MA, Fayad LM. Insights into quantitative diffusion-weighted MRI for musculoskeletal tumor imaging. AJR Am J Roentgenol 2014;203:560-72.
Filograna L, Magarelli N, Cellini F, Manfrida S, Leone A, Colosimo C, et al
. Diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) values for detection of malignant vertebral bone marrow lesions. Eur Rev Med Pharmacol Sci 2018;22:590-7.
Bhojwani N, Szpakowski P, Partovi S, Maurer MH, Grosse U, von Tengg-Kobligk H, et al
. Diffusion-weighted imaging in musculoskeletal radiology-clinical applications and future directions. Quant Imaging Med Surg 2015;5:740-53.
Pawlyn C, Fowkes L, Otero S, Jones JR, Boyd KD, Davies FE, et al
. Whole-body diffusion-weighted MRI: A new gold standard for assessing disease burden in patients with multiple myeloma? Leukemia 2016;30:1446-8.
Perez-Lopez R, Mateo J, Mossop H, Blackledge MD, Collins DJ, Rata M, et al
. Diffusion-weighted imaging as a treatment response biomarker for evaluating bone metastases in prostate cancer: A pilot study. Radiology 2017;283:168-77.
Percival ME, Lai C, Estey E, Hourigan CS. Bone marrow evaluation for diagnosis and monitoring of acute myeloid leukemia. Blood Rev 2017;31:185-92.
Messiou C, Giles S, Collins DJ, West S, Davies FE, Morgan GJ, et al
. Assessing response of myeloma bone disease with diffusion-weighted MRI. Br J Radiol 2012;85:1020-203.
Giles SL, Messiou C, Collins DJ, Morgan VA, Simpkin CJ, West S, et al
. Whole-body diffusion-weighted MR imaging for assessment of treatment response in myeloma. Radiology 2014;271:785-94.
Balbo-Mussetto A, Saviolo C, Fornari A, Gottardi D, Petracchini M, Macera A, et al
. Whole body MRI with qualitative and quantitative analysis of DWI for assessment of bone marrow involvement in lymphoma. Radiol Med 2017;122:623-32.
Webster JA, Pratz KW. Acute myeloid leukemia in the elderly: Therapeutic options and choice. Leuk Lymphoma 2018;59:274-87.
Ballon D, Dyke J, Schwartz LH, Lis E, Schneider E, Lauto A, et al
. Bone marrow segmentation in leukemia using diffusion and T (2) weighted echo planar magnetic resonance imaging. NMR Biomed 2000;13:321-8.
Horger M, Weisel K, Horger W, Mroue A, Fenchel M, Lichy M. Whole-body diffusion-weighted MRI with apparent diffusion coefficient mapping for early response monitoring in multiple myeloma: Preliminary results. AJR. Am J Roentgenol 2011;196:W790-5.
Chen PE, Simon JE, Hill MD, Sohn CH, Dickhoff P, Morrish WF, et al
. Acute ischemic stroke: Accuracy of diffusion-weighted MR imaging--effects of b value and cerebrospinal fluid suppression. Radiology 2006;238:232-9.
Ni JM, Mogensen MA, Chen ZA, Shuang C, Shen TZ, Huang G. Influence of fluid-attenuated inversion-recovery on stroke apparent diffusion coefficient measurements and its clinical application. Eur J Radiol 2010;75:76-81.
Bykowski JL, Latour LL, Warach S. More accurate identification of reversible ischemic injury in human stroke by cerebrospinal fluid suppressed diffusion-weighted imaging. Stroke 2004;35:1100-6.
Vardiman JW. The World Health Organization (WHO) classification of tumors of the hematopoietic and lymphoid tissues: An overview with emphasis on the myeloid neoplasms. Chem Biol Interact 2010;184:16-20.
Modkharkar S, Navale P, Amare PK, Chougule A, Patkar N, Tembhare P, et al
. Applicability of 2008 World Health Organization classification system of hematolymphoid neoplasms: Learning experiences. Indian J Pathol Microbiol 2018;61:58-65.
] [Full text]
Bonaffini PA, Ippolito D, Casiraghi A, Besostri V, Franzesi CT, Sironi S. Apparent diffusion coefficient maps integrated in whole-body MRI examination for the evaluation of tumor response to chemotherapy in patients with multiple myeloma. Acad Radiol 2015;22:1163-71.
Puskás T, Henits I. Use of whole-body diffusion-weighted magnetic resonance imaging for the diagnosis of and therapeutic response in multiple myeloma. Orv Hetil 2014;155:1241-5.
Park HJ, Lee SY, Rho MH, Chung EC, Kim MS, Kwon HJ, et al
. Single-shot echo-planar diffusion-weighted MR imaging at 3T and 1.5T for differentiation of benign vertebral fracture edema and tumor infiltration. Korean J Radiol 2016;17:590-7.
Biffar A, Dietrich O, Sourbron S, Duerr HR, Reiser MF, Baur-Melnyk A. Diffusion and perfusion imaging of bone marrow. Eur J Radiol 2010;76:323-8.
Latifoltojar A, Hall-Craggs M, Bainbridge A, Rabin N, Popat R, Rismani A, et al
. Whole-body MRI quantitative biomarkers are associated significantly with treatment response in patients with newly diagnosed symptomatic multiple myeloma following bortezomib induction. Eur Radiol 2017;27:5325-36.
Lim HK, Jee WH, Jung JY, Paek MY, Kim I, Jung CK, et al
. Intravoxel incoherent motion diffusion-weighted MR imaging for differentiation of benign and malignant musculoskeletal tumours at 3 T. Br J Radiol 2018;91:20170636.
Xu J, Li K, Smith RA, Waterton JC, Zhao P, Ding Z, et al
. A comparative assessment of preclinical chemotherapeutic response of tumors using quantitative non-Gaussian diffusion MRI. Magn Reson Imaging 2017;37:195-202.
Hall MG, Bongers A, Sved P, Watson G, Bourne RM. Assessment of non-Gaussian diffusion with singly and doubly stretched biexponential models of diffusion-weighted MRI (DWI) signal attenuation in prostate tissue. NMR Biomed 2015;28:486-95.
[Figure 1], [Figure 2]
[Table 1], [Table 2]