Role of Functional MRI in Liver SBRT: Comparison
Please note this is a comparison between Version 2 by Dean Liu and Version 1 by Sirisha Tadimalla.

Magnetic resonance imaging (MRI) is becoming increasingly important in the planning and delivery of radiation therapy of liver cancers. While most commonly utilised for anatomical detail, the utility of functional MRI for the development of personalised treatment approaches is an emerging area of research. 

  • magnetic resonance imaging
  • MRI
  • liver

1. Introduction

Stereotactic body radiation therapy (SBRT) is increasingly utilised for treatment of primary liver cancer as well as liver metastases, most often in patients who are not eligible for other local therapies such as surgical resection, ablation or embolization techniques [1,2,3][1][2][3]. SBRT uses several, precisely focused beams of radiation, enabling the delivery of higher radiation dose to the tumour with less dose to surrounding liver parenchyma in fewer fractions than other external beam radiation treatment techniques. High-dose SBRT for unresectable primary and metastatic liver cancer has demonstrated excellent local control rates [4]. However, the ability to deliver higher doses safely is limited by the risk of toxicity in the non-tumour liver. A critical volume of 700 cc, receiving <15 Gy in 3 fractions is recommended for SBRT for liver metastases, with the volume estimate adapted from partial hepatectomy guidelines [5]. In the case of primary liver cancer, such as hepatocellular carcinoma (HCC) where liver function is already compromised, the goal is to deliver a therapeutic dose of radiation whilst minimising the risk of deterioration of liver function.
Traditionally, normal tissue complication probability (NTCP) models that predict liver toxicity are based on dose-volume parameters [6]. However, these models do not take into account the heterogeneity of an individual patient’s liver function prior to treatment, or the heterogeneity of changes in local liver function as a response to radiation as treatment progresses. Efforts are ongoing on the use of functional imaging techniques to obtain the spatial distribution of liver function to guide treatment planning for selection of poorly functioning liver regions that can be sacrificed in order to spare more high functioning liver [7]. These methods may also be useful for assessing early local changes in liver function to radiation treatment, which can support personalised treatment adaptations such as mid-treatment dose escalation to maximise tumour control, or for identifying patients at greater risk for radiation-induced liver disease (RILD).

2. Use of Functional MRI for Liver SBRT

2.1. Use in Treatment Planning

MRI offers excellent soft-tissue resolution for the detection and characterisation of liver tumours. While CT remains the workhorse of radiation therapy, MRI has several advantages such as zero ionising radiation exposure, superior tissue contrast, availability of hepatocyte-specific contrast agents and the ability to obtain anatomic and functional images within a single scan. MRI is, therefore, increasingly being used to provide complementary information to CT images for SBRT planning, although it is not mandated in most liver SBRT guidelines [72,73,74][8][9][10]. In current liver SBRT treatment planning, MRI is often fused with CT to guide target delineation. However, this requires accurate image registration between CT and MRI, which adds to the complexity of liver SBRT planning. MRI-only planning has already been developed in brain, head and neck and prostate, and is an emerging alternative in other body sites [75][11]. Using deep learning, Liu et al. have developed methods to generate synthetic liver CT images from 3D T1w MRI images that achieved SBRT dose distributions comparable to a traditional CT image-based plan [76][12]. A major concern with the use of MRI for SBRT treatment planning is the presence of geometric distortions in MRI images, which can lead to dosimetric uncertainties. In a simulation study [77][13], it was found that distortion of up to 3 mm, measured separately on phantoms and averaged across several T1w and T2w MRI sequences, result in small dose uncertainties of <1 Gy. However, for small targets ( 15 mm diameter), the impact can be substantially larger, resulting in dose errors of up to 15% [78][14]. Breathing motion is another source of error in treatment planning, as traditional MRI image acquisition is relatively slow and several breathing cycles pass by the time an image is acquired, leading to image blurring. Respiratory-triggered image acquisition with the patient in the treatment position using optimised MRI sequences can improve image quality although there is the penalty of increased scan times [79][15]. Implantation of radio-opaque fiducial markers to guide treatment delivery and real-time tumour tracking using external intra-fraction monitoring devices are other approaches to motion management [80,81][16][17]. Additionally, emerging methods of 4D MRI and hybrid MR-linac (MRI + linear accelerator) can track the motion of tumours and other structures in real-time, enabling adaptive treatment and significantly reducing the impact of breathing motion on treatment accuracy [82,83,84][18][19][20]. While the use of functional MRI in this context is limited, there is growing evidence to suggest that gadoxetate enhancement can allow the sustained visualisation of tumours that have poor visibility on anatomical MRI [85,86][21][22]. However, repeated administration of Gadolinium-based contrast agents has been linked to Gadolinium deposition in the brain [87][23], therefore, more research on low-dose gadoxetate MRI as well as other functional MRI techniques such as DWI is required. While currently not used in SBRT planning, preliminary studies have shown that DWI can improve accuracy in tumour delineation [88][24]. Future implementations of liver SBRT on MR-linacs can include functional MRI methods to enable daily personalised treatment planning and optimisation of SBRT dose. Regional liver function measurements are not currently used to guide liver SBRT planning. While research in this area is still in its infancy, preliminary studies have showed promise. Proof of concept studies using retrospective data from small groups of patients (<20) with HCC and liver metastases have demonstrated benefits of using spatial liver function maps to identify and spare high functioning liver from irradiation in terms of significant dose reduction to functional liver, while maintaining target coverage and OAR sparing comparable to plans designed based on the anatomy only [21,23,89,90,91,92,93][25][26][27][28][29][30][31]. A prospective clinical trial on 15 participants has been recently performed to compare differences in the functional liver reserve when using SBRT plans based on SPECT-HIDA scans vs. standard SBRT plans. The trial also evaluated the proportion of patients for whom the SPECT-based SBRT plans were chosen for treatment over the standard SBRT plans (NCT03338062: A pilot study to assess theragnostically planned liver radiation to optimize radiation therapy). Preliminary results show that 4 of the 15 patients showed >5% improvement in functional liver reserve, and the SPECT-based plans were selected for 11 patients [94][32]. Larger prospective trials with longer follow up are needed to determine the safety and efficacy of the function-based approach. In studies conducted thus far, liver function was measured semi-quantitatively—as a percentage of maximum tracer uptake in SPECT images, normalised iodine density (NID; obtained as the ratio of iodine density in liver and aorta) in DECT images, and liver-to-spleen intensity ratios in gadoxetate DCE-MRI images. Only one study used pharmacokinetic modeling of gadoxetate DCE-MRI to derive quantitative perfusion and uptake rates [93][31]. In studies using SPECT, high functioning liver was identified based on thresholds determined from published correlations between the parameters and clinical liver function measures such as CP scores [95[33][34],96], and was defined as regions with tracer uptake ≥ 50% relative to the maximum uptake. For quantitative perfusion and uptake rates derived from gadoxetate DCE-MRI, voxels with uptake and perfusion >36% of the values measured in a manually selected region with ’normal’ function were defined as high functioning [93][31]. There is as yet no global consensus on the definition of high functioning liver in imaging studies. Furthermore, as most of the liver function estimates are not direct measures of hepatocellular function, there can be considerable variation in the function-based plans. For example, although liver perfusion and function are closely related [97][35], Simeth et al. have reported that mismatch in definitions of high functioning regions based on perfusion and uptake spatial maps can result in variations as large as 10% in the mean dose reduction to functional liver [93][31]. Wei et al. have similarly found that the dose that causes a 50% loss in function (gadoxetate uptake rates) is significantly lower compared to the dose that causes the same loss in perfusion (portal venous flow) [98][36]. The relationship between liver perfusion and function was also found to vary between patients with HCC tumours and patients with non-HCC tumours (liver metastases and cholagiocarcinoma), with the same amount of liver perfusion translating to less probability of liver function in patients with HCC [99][37]. Despite correlations observed between chronic liver disease and DWI-derived parameters, there have been no studies using functional DWI parameters to guide liver SBRT planning, and the role of this functional MRI technique in liver SBRT planning remains unexplored.

2.2. Use in Response Assessment

In the clinic, response assessment after liver SBRT follows general assessment criteria for liver cancers, such as the Response Evaluation Criteria In Solid Tumours (RECIST), modified RECIST (mRECIST), the European Association of Study of the Liver (EASL) or the Liver Imaging Reporting and Data System (LI-RADS) criteria. These criteria typically assess changes in tumour size and in the case of mRECIST, EASL and LI-RADS criteria, also include observations on arterial enhancement of the tumours in contrast-enhanced CT or MRI images. Imaging is usually performed every 3 months after treatment for response evaluation. After SBRT, HCC tumours shrink slowly, however, change in size is not always correlated with treatment success [100][38]. Price et al. suggest that reduced vascularity of HCC tumours or non-enhancement in DCE-CT/DCE-MRI indicating necrosis is potentially a more useful indicator of treatment success than tumour size [101][39]. However, the presence of persistent arterial phase hyperenhancement, even up to 1 year following SBRT, does not necessarily indicate residual viable tumour [102,103][40][41]. The RECIST criteria is similarly limited in the response evaluation of liver metastases following SBRT, and criteria such as mRECIST and EASL which combine assessment of size as well as contrast enhancement are recommended [104][42]. However, there is no general consensus on the optimal criteria to use for response assessment after liver SBRT [104][42]. Furthermore, all the response assessment criteria are qualitative, and functional, quantitative liver MRI is rarely, if ever, used clinically. There are no assessment criteria that account for the radiation-related response of the liver parenchyma. However, several imaging studies report morphological and physiological changes in the immediate surrounding liver parenchyma following SBRT [105][43]. These changes are collectively referred to as focal liver reaction (FLR). Morphological alterations in the appearance of liver surrounding tumours in T2w and T1w (pre- and post-Gadolinium contrast injection) images have been observed as early as 6 weeks following SBRT [106][44]. Irradiated liver parenchyma appears hypointense on T1w images, and hyperintense on T2w images, which may be related to hepatic edema which can occur very early after SBRT and is accompanied by a slight increase in ADC values. On hepatobiliary DCE-MRI images, the FLR appears as a well-demarcated hypo-intense region up to 6 months after treatment. Between 1–3 months after treatment, the surrounding irradiated parenchyma exhibits arterial enhancement in DCE-MRI images, which without subsequent wash-out in the delayed phase indicates a focal liver reaction, differentiating it from residual tumour. Another focal reaction is steatosis, which manifests as decreased signal intensity on opposed-phase and T2w images [105,107,108][43][45][46]. Furthermore, a reduction in liver volume has been observed after SBRT (from 3 to >12 months following treatment), with a wide range of volume reduction from 24% to 60% reported in the literature [105,107][43][45]. Fibrosis is another response of liver parenchyma to radiation, and manifests as delayed enhancement on DCE-MRI images [107][45]. Tumour ADC (in both HCC and liver metastases) has been observed to increase significantly compared to baseline as early as 1 week into treatment. In HCC patients treated with SBRT, a tumour ADC increment within 6 months following treatment has been observed to be indicative of favorable response, with estimated minimum effect size ranging from 20% to 25% [109,110][47][48]. However, these studies were retrospective, included small numbers of patients with short follow up times and only assessed tumour response radiologically, with no histological confirmation. Increase in ADC following liver SBRT has also been observed in peri-tumour regions and irradiated liver parenchyma, with no significant change in non-irradiated liver parenchyma [111][49]. The increase in tumour ADC has been correlated with radiation dose [111][49]. However, there is no robust evidence for correlation between increase in parenchymal ADC with radiation dose, with some preliminary studies showing that the ADC increase occurs in regions irradiated with low (<15 Gy) and high (>30 Gy) doses [112][50]. Few studies have evaluated the predictive/prognostic value of IVIM or DKI in the context of liver SBRT. This may be due to the greater precision errors associated with measurement of IVIM parameters, particularly f and D*, when compared to ADC. While preliminary studies have reported changes in IVIM parameters in liver parenchyma following SBRT, demonstrating sensitivity to dose deposition [113][51], prospective studies with large sample sizes and improved DWI acquisition and post-processing methods are needed. Qualitative assessment of DCE-MRI images is already part of routinely used evaluation criteria, with early arterial, portal venous and hepatobiliary phase enhancement used as indicators of tumour response and parenchymal reaction to radiation as described above. Correlations of tumour and hepatic response with semi-quantitative and quantitative DCE-MRI parameters have also been reported in some studies. For example, an increased wash-in slope and peak enhancement in HCC tumours as early as two weeks following radiotherapy has been linked to improved local response [114][52]. Similarly, quantitative portal venous blood flow to intra-hepatic tumours decreases significantly following treatment, and in the non-tumour liver is found to correlate with ICG-R15 measurements before, during and 1 and 2 months after irradiation [115][53]. Uptake rates of gadoxetate in liver parenchyma were found to be reduced 1 month post-SBRT in patients with HCC, however, it is possible that the decrease is a combined response to both the delivered radiation dose as well as hepatic inflammation [116][54]. Further validation of treatment-related changes in the DCE-MRI parameters is required in larger patient datasets with longer follow up times.

2.3. Use for Dose-Response Assessment and Mid-Treatment Adaptation

RILD is the main complication from liver SBRT and results from radiation induced damage to the liver parenchyma. The reported complication rate for liver SBRT is <5%, when strict dose-volume constraints are applied and patients without cirrhosis or well-compensated cirrhosis are selected for treatment. RILD is seen most often in patients with pre-existing chronic liver disease and is typically defined by an increase in the CP or ALBI score after treatment [107,108][45][46]. Current NTCP models are geared toward predicting the risk of RILD. However, they are based on studies which did not differentiate between patients with HCC, with compromised liver function, and patients with liver metastases, with better liver function. The models also do not account for spatial variation of liver function due to the underlying liver disease and liver damage from prior treatments which can increase the risk of RILD after SBRT. Approaches for treatment planning guided by the spatial distribution of baseline liver function have been already described in a previous section. In most studies, while the radiation dose distribution was modified to spare high functioning liver, dose–response and post-treatment liver function were not considered during plan optimisation. However, Wu et al. found that plans that are designed to spare highly functioning regions of the liver do not necessarily retain the most post-treatment global liver function [117][55]. The authors suggest that plans where damaging doses are delivered to fewer high functioning liver voxels can retain more liver function post-treatment as long as doses delivered to these voxels are tolerable. They estimated the thresholds for damaging and tolerable doses (>50 Gy-EQD2 and <20 Gy-EQD2 where EQD2 is the equivalent dose in 2 Gy fractions) based on dose–response relationships obtained from a small, retrospective study within their institution. However, dose–response can vary across patients and depend on the baseline liver function [101][39]. For instance, using visible focal liver reaction on MRI obtained 3–5 months post-treatment, Yadav et al. estimated an upper dose threshold of 35 Gy mean dose to the liver [118][56]. Another study reported that the dose threshold for liver dysfunction on post-treatment MRI is different for cirrhotic and non-cirrhotic livers (BED2 = 40 Gy in cirrhotic livers and 70 Gy in normal livers) [119][57]. Ideally, the liver SBRT dose should be guided by the baseline liver function and liver function dose–response for each individual patient. Predictive mathematical models of tumour dynamics and dose response similar to those being developed in the context of lung cancer treatments [120,121][58][59] could enable the identification of patients at risk of post-treatment liver dysfunction and facilitate mid-treatment dose adaptation. Implementation of individualised, mid-treatment adaptation of liver SBRT has been realised using ICG tests for measurement of liver function [15][60]. In a Phase II clinical trial on 90 patients (23% CP grade B), pre- and mid-treatment liver function measurements of ICG-R15 have been used to modify prescribed dose after 3 SBRT fractions, successfully identifying patients at higher risk for liver dysfunction who could not be treated further and patients who could tolerate further treatment after a 1 month pause and lower doses at subsequent SBRT fractions. The individualised adaptive approach demonstrated in this trial achieved high rates of local control of 99% at 1 year and 95% at 2 years after treatment, as well as significantly altered the predicted loss of liver function [17][61]. Another trial with 80 patients with CP-B liver disease and HCC also achieved high rates of 1 year local control of 92% using the same individualised adaptive SBRT approach with ICG-R15 liver function measurements [122][62], demonstrating the benefit of personalised, adaptive treatment especially for patients with liver cirrhosis at baseline. These studies demonstrate the potential for achieving high rates of tumour control without compromising safety for patients who are already at an increased risk of liver dysfunction. At present, no similar studies using functional liver MRI have been performed. Research is ongoing; a University of Michigan clinical trial (https://clinicaltrials.gov/ct2/show/NCT02460835, accessed on 27 September 2022, NCT02460835: A pilot study of individualised adaptive radiation therapy for hepatocellular carcinoma) aims to develop a function-based planning and adaptive SBRT approach using portal venous perfusion maps to estimate regional liver function and is due to complete in 2023. Another clinical trial commencing in 2022 at the University of Sydney (https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=383543&isReview=true, accessed on 27 September 2022, ACTRN12622000371796: Personalised liver stereotactic body radiation therapy using magnetic resonance imaging (PRISM)) is examining the feasibility of using liver function measurements from pharmacokinetic modeling of gadoxetate DCE-MRI for liver SBRT planning and mid-treatment adaptation.

References

  1. Gerum, S.; Jensen, A.D.; Roeder, F. Stereotactic body radiation therapy in patients with hepatocellular carcinoma: A mini-review. World J. Gastrointest. Oncol. 2019, 11, 367–376.
  2. Lewis, S.; Dawson, L.; Barry, A.; Stanescu, T.; Mohamad, I.; Hosni, A. Stereotactic body radiation therapy for hepatocellular carcinoma: From infancy to ongoing maturity. JHEP Rep. 2022, 4, 100498.
  3. John, R.G.; Ho, F.; Appalanaido, G.K.; Chen, D.; Tey, J.; Soon, Y.Y.; Vellayappan, B.A. Can radiotherapy finally “go live” in the management of liver metastases? Hepatoma Res. 2020, 6, 56.
  4. Ohri, N.; Tomé, W.A.; Romero, A.M.; Miften, M.; Ten Haken, R.K.; Dawson, L.A.; Grimm, J.; Yorke, E.; Jackson, A. Local control after stereotactic body radiation therapy for liver tumors. Int. J. Radiat. Oncol. Biol. Phys. 2021, 110, 188–195.
  5. Pan, C.C.; Kavanagh, B.D.; Dawson, L.A.; Li, X.A.; Das, S.K.; Miften, M.; Ten Haken, R.K. Radiation-associated liver injury. Int. J. Radiat. Oncol. Biol. Phys. 2010, 76, S94–S100.
  6. Miften, M.; Vinogradskiy, Y.; Moiseenko, V.; Grimm, J.; Yorke, E.; Jackson, A.; Tomé, W.A.; Ten Haken, R.K.; Ohri, N.; Méndez Romero, A.; et al. Radiation Dose-Volume Effects for Liver SBRT. Int. J. Radiat. Oncol. Biol. Phys. 2021, 110, 196–205.
  7. Zhou, P.X.; Zhang, Y.; Zhang, Q.B.; Zhang, G.Q.; Yu, H.; Zhang, S.X. Functional Liver Imaging in Radiotherapy for Liver Cancer: A Systematic Review and Meta-Analysis. Front. Oncol. 2022, 12, 898435.
  8. Potters, L.; Kavanagh, B.; Galvin, J.M.; Hevezi, J.M.; Janjan, N.A.; Larson, D.A.; Mehta, M.P.; Ryu, S.; Steinberg, M.; Timmerman, R.; et al. American Society for Therapeutic Radiology and Oncology (ASTRO) and American College of Radiology (ACR) Practice Guideline for the Performance of Stereotactic Body Radiation Therapy. Int. J. Radiat. Oncol. Biol. Phys. 2010, 76, 326–332.
  9. Sahgal, A.; Roberge, D.; Schellenberg, D.; Purdie, T.; Swaminath, A.; Pantarotto, J.; Filion, E.; Gabos, Z.; Butler, J.; Letourneau, D.; et al. The Canadian Association of Radiation Oncology Scope of Practice Guidelines for Lung, Liver and Spine Stereotactic Body Radiotherapy. Clin. Oncol. 2012, 24, 629–639.
  10. Apisarnthanarax, S.; Barry, A.; Cao, M.; Czito, B.; DeMatteo, R.; Drinane, M.; Hallemeier, C.L.; Koay, E.J.; Lasley, F.; Meyer, J.; et al. External Beam Radiation Therapy for Primary Liver Cancers: An ASTRO Clinical Practice Guideline. Pract. Radiat. Oncol. 2022, 12, 28–51.
  11. Bredfeldt, J.S.; Liu, L.; Feng, M.; Cao, Y.; Balter, J.M. Synthetic CT for MRI-based liver stereotactic body radiotherapy treatment planning. Phys. Med. Biol. 2017, 62, 2922–2934.
  12. Liu, Y.; Lei, Y.; Wang, Y.; Wang, T.; Ren, L.; Lin, L.; McDonald, M.; Curran, W.J.; Liu, T.; Zhou, J.; et al. MRI-based treatment planning for proton radiotherapy: Dosimetric validation of a deep learning-based liver synthetic CT generation method. Phys. Med. Biol. 2019, 64, 145015.
  13. Han, S.; Yin, F.F.; Cai, J. Evaluation of dosimetric uncertainty caused by MR geometric distortion in MRI-based liver SBRT treatment planning. J. Appl. Clin. Med. Phys. 2019, 20, 43–50.
  14. Pappas, E.P.; Alshanqity, M.; Moutsatsos, A.; Lababidi, H.; Alsafi, K.; Georgiou, K.; Karaiskos, P.; Georgiou, E. MRI-Related Geometric Distortions in Stereotactic Radiotherapy Treatment Planning: Evaluation and Dosimetric Impact. Technol. Cancer Res. Treat. 2017, 16, 1120–1129.
  15. Ken, S.; Tournier, A.; Rives, M.; Izar, F.; Aziza, R.; Morel, N.; Sekkal, Y.; Parent, L. 50. Magnetic Resonance Imaging optimization for liver SBRT: Breath-triggered acquisition in treatment position to improve lesion contouring. Phys. Medica 2016, 32, 365–366.
  16. Oldrini, G.; Taste-George, H.; Renard-Oldrini, S.; Baumann, A.S.; Marchesi, V.; Troufléau, P.; Peiffert, D.; Didot-Moisei, A.; Boyer, B.; Grignon, B.; et al. Implantation of fiducial markers in the liver for stereotactic body radiation therapy: Feasibility and results. Diagn. Interv. Imaging 2015, 96, 589–592.
  17. Lee, Y.Y.D.; Nguyen, D.T.; Moodie, T.; O’Brien, R.; McMaster, A.; Hickey, A.; Pritchard, N.; Poulsen, P.; Tabaksblat, E.M.; Weber, B.; et al. Study protocol of the LARK (TROG 17.03) clinical trial: A phase II trial investigating the dosimetric impact of Liver Ablative Radiotherapy using Kilovoltage intrafraction monitoring. BMC Cancer 2021, 21, 494.
  18. van de Lindt, T.N.; Fast, M.F.; van den Wollenberg, W.; Kaas, J.; Betgen, A.; Nowee, M.E.; Jansen, E.P.; Schneider, C.; van der Heide, U.A.; Sonke, J.J. Validation of a 4D-MRI guided liver stereotactic body radiation therapy strategy for implementation on the MR-linac. Phys. Med. Biol. 2021, 66, 105010.
  19. Paulson, E.S.; Ahunbay, E.; Chen, X.; Mickevicius, N.J.; Chen, G.P.; Schultz, C.; Erickson, B.; Straza, M.; Hall, W.A.; Li, X.A. 4D-MRI driven MR-guided online adaptive radiotherapy for abdominal stereotactic body radiation therapy on a high field MR-Linac: Implementation and initial clinical experience. Clin. Transl. Radiat. Oncol. 2020, 23, 72–79.
  20. Gani, C.; Boeke, S.; McNair, H.; Ehlers, J.; Nachbar, M.; Mönnich, D.; Stolte, A.; Boldt, J.; Marks, C.; Winter, J.; et al. Marker-less online MR-guided stereotactic body radiotherapy of liver metastases at a 1.5 T MR-Linac—Feasibility, workflow data and patient acceptance. Clin. Transl. Radiat. Oncol. 2021, 26, 55–61.
  21. Wojcieszynski, A.P.; Rosenberg, S.A.; Brower, J.V.; Hullett, C.R.; Geurts, M.W.; Labby, Z.E.; Hill, P.M.; Bayliss, R.A.; Paliwal, B.; Bayouth, J.E.; et al. Gadoxetate for direct tumor therapy and tracking with real-time MRI-guided stereotactic body radiation therapy of the liver. Radiother. Oncol. 2016, 118, 416–418.
  22. Thomas, H.R.; Miao, X.; Ferguson, D.; Calvin, C.; Bhaskar Krishnamurthy, U.; Anwar, M.; Feng, M.; Scholey, J. Contrast-enhanced 4D-MRI for internal target volume generation in treatment planning for liver tumors. Radiother. Oncol. 2022, 173, 69–76.
  23. Gulani, V.; Calamante, F.; Shellock, F.G.; Kanal, E.; Reeder, S.B. Gadolinium deposition in the brain: Summary of evidence and recommendations. Lancet Neurol. 2017, 16, 564–570.
  24. Nemiro, I.; Utehina, O.; Boka, G.; Boka, V.; Riga, L.V. Functional MRI imaging for precise target determination and results evaluation in liver Stereotactic Body Radiotherapy. In Proceedings of the European Congress of Radiology—ECR 2014, Vienna, Austria, 6–10 March 2014.
  25. Ohira, S.; Kanayama, N.; Toratani, M.; Ueda, Y.; Koike, Y.; Karino, T.; Shunsuke, O.; Miyazaki, M.; Koizumi, M.; Teshima, T. Stereotactic body radiation therapy planning for liver tumors using functional images from dual-energy computed tomography. Radiother. Oncol. 2020, 145, 56–62.
  26. Bowen, S.R.; Saini, J.; Chapman, T.R.; Miyaoka, R.S.; Kinahan, P.E.; Sandison, G.A.; Wong, T.; Vesselle, H.J.; Nyflot, M.J.; Apisarnthanarax, S. Differential hepatic avoidance radiation therapy: Proof of concept in hepatocellular carcinoma patients. Radiother. Oncol. 2015, 115, 203–210.
  27. Long, D.E.; Tann, M.; Huang, K.C.; Bartlett, G.; Galle, J.O.; Furukawa, Y.; Maluccio, M.; Cox, J.A.; Kong, F.M.S.; Ellsworth, S.G. Functional liver image guided hepatic therapy (FLIGHT) with hepatobiliary iminodiacetic acid (HIDA) scans. Pract. Radiat. Oncol. 2018, 8, 429–436.
  28. Furukawa, Y.; Long, D.E.; Ellsworth, S.G. Functional liver-image guided hepatic therapy (FLIGHT): A technique to maximize hepatic functional reserve. Med. Dosim. 2020, 45, 117–120.
  29. Fode, M.M.; Petersen, J.B.; Sørensen, M.; Holt, M.I.; Keiding, S.; Høyer, M. 2-fluoro-2-deoxy-d-galactose positron emission tomography guided functional treatment planning of stereotactic body radiotherapy of liver tumours. Phys. Imaging Radiat. Oncol. 2017, 1, 28–33.
  30. Tsegmed, U.; Kimura, T.; Nakashima, T.; Nakamura, Y.; Higaki, T.; Imano, N.; Doi, Y.; Kenjo, M.; Ozawa, S.; Murakami, Y.; et al. Functional image-guided stereotactic body radiation therapy planning for patients with hepatocellular carcinoma. Med. Dosim. 2017, 42, 97–103.
  31. Simeth, J.; Baughan, N.; Dow, J.; Ten Haken, R.; Johansson, A.; Aryal, M.; Owen, D.; Cunco, K.; Lawrence, T.; Cao, Y.; et al. Impact of Mis-Match Between Liver Function and Hepatic Perfusion On Functional Avoidance Treatment Planning. In Medical Physics; Wiley: Hoboken, NJ, USA, 2018; Volume 45, p. E582.
  32. Long, D.E.; Huang, C.; Tann, M.; Dawson, B.; Bartlett, G.; Maluccio, M.A.; Rhome, R.; Kong, F.M.S.; Ellsworth, S.G. Prospective trial of functional liver image-guided hepatic therapy (FLIGHT) with hepatobiliary iminodiacetic acid (HIDA) scans and update of institutional experience. J. Clin. Oncol. 2019, 37, 373.
  33. Groshar, D.; Slobodin, G.; Zuckerman, E. Quantitation of liver and spleen uptake of 99mTc-phytate colloid using SPECT: Detection of liver cirrhosis. J. Nucl. Med. 2002, 43, 312–317.
  34. Matesan, M.M.; Bowen, S.R.; Chapman, T.R.; Miyaoka, R.S.; Velez, J.W.; Wanner, M.F.; Nyflot, M.J.; Apisarnthanarax, S.; Vesselle, H.J. Assessment of functional liver reserve: Old and new in 99mTc-sulfur colloid scintigraphy. Nucl. Med. Commun. 2017, 38, 577–586.
  35. Takahashi, H.; Shigefuku, R.; Yoshida, Y.; Ikeda, H.; Matsunaga, K.; Matsumoto, N.; Okuse, C.; Sase, S.; Itoh, F.; Suzuki, M. Correlation between hepatic blood flow and liver function in alcoholic liver cirrhosis. World J. Gastroenterol. 2014, 20, 17065–17074.
  36. Wei, L.; Aryal, M.; Simeth, J.; Cuneo, K.; Matuszak, M.; Lawrence, T.; Ten Haken, R.; Cao, Y.; El Naqa, I. Comparison of NTCP Models Using Liver Function Obtained From Different Contrast Agent-Based DCE-MRI after SBRT in Hepatocellular Carcinoma. Int. J. Radiat. Oncol. Biol. Phys. 2021, 111, e134–e135.
  37. Wang, H.; Feng, M.; Jackson, A.; Ten Haken, R.K.; Lawrence, T.S.; Cao, Y. Local and Global Function Model of the Liver. Int. J. Radiat. Oncol. Biol. Phys. 2016, 94, 181–188.
  38. Mendiratta-Lala, M.; Masch, W.R.; Shampain, K.; Zhang, A.; Jo, A.S.; Moorman, S.; Aslam, A.; Maturen, K.E.; Davenport, M.S. MRI assessment of hepatocellular carcinoma after local-regional therapy: A comprehensive review. Radiol. Imaging Cancer 2020, 2, e190024.
  39. Price, R.G.; Apisarnthanarax, S.; Schaub, S.K.; Nyflot, M.J.; Chapman, T.R.; Matesan, M.; Vesselle, H.J.; Bowen, S.R. Regional Radiation Dose-Response Modeling of Functional Liver in Hepatocellular Carcinoma Patients With Longitudinal Sulfur Colloid SPECT/CT: A Proof of Concept. Int. J. Radiat. Oncol. Biol. Phys. 2018, 102, 1349–1356.
  40. Mendiratta-Lala, M.; Gu, E.; Owen, D.; Cuneo, K.C.; Bazzi, L.; Lawrence, T.S.; Hussain, H.K.; Davenport, M.S. Imaging Findings Within the First 12 Months of Hepatocellular Carcinoma Treated With Stereotactic Body Radiation Therapy. Int. J. Radiat. Oncol. Biol. Phys. 2018, 102, 1063–1069.
  41. Mendiratta-Lala, M.; Masch, W.; Shankar, P.R.; Hartman, H.E.; Davenport, M.S.; Schipper, M.J.; Maurino, C.; Cuneo, K.C.; Lawrence, T.S.; Owen, D. Magnetic Resonance Imaging Evaluation of Hepatocellular Carcinoma Treated With Stereotactic Body Radiation Therapy: Long Term Imaging Follow-Up. Int. J. Radiat. Oncol. Biol. Phys. 2019, 103, 169–179.
  42. Tétreau, R.; Llacer, C.; Riou, O.; Deshayes, E. Evaluation of response after SBRT for liver tumors. Rep. Pract. Oncol. Radiother. 2017, 22, 170–175.
  43. Yip, C.; Cook, G.J.R.; Owczarczyk, K.; Goh, V. Challenges in imaging assessment following liver stereotactic body radiotherapy: Pitfalls to avoid in clinical practice. Chin. Clin. Oncol. 2017, 6, S11.
  44. Boda-Heggemann, J.; Jahnke, A.; Chan, M.K.H.; Ghaderi Ardekani, L.S.; Hunold, P.; Schäfer, J.P.; Huttenlocher, S.; Wurster, S.; Rades, D.; Hildebrandt, G.; et al. Direct dose correlation of MRI morphologic alterations of healthy liver tissue after robotic liver SBRT. Strahlenther. Onkol. 2018, 194, 414–424.
  45. Navin, P.J.; Olson, M.C.; Mendiratta-Lala, M.; Hallemeier, C.L.; Torbenson, M.S.; Venkatesh, S.K. Imaging Features in the Liver after Stereotactic Body Radiation Therapy. RadioGraphics 2022, 42, 220084.
  46. Kellock, T.; Liang, T.; Harris, A.; Schellenberg, D.; Ma, R.; Ho, S.; Yap, W.W. Stereotactic body radiation therapy (SBRT) for hepatocellular carcinoma: Imaging evaluation post treatment. Br. J. Radiol. 2018, 91, 20170118.
  47. Lo, C.H.; Huang, W.Y.; Hsiang, C.W.; Lee, M.S.; Lin, C.S.; Yang, J.F.; Hsu, H.H.; Chang, W.C. Prognostic Significance of Apparent Diffusion Coefficient in Hepatocellular Carcinoma Patients treated with Stereotactic Ablative Radiotherapy. Sci. Rep. 2019, 9, 14157.
  48. Yu, J.I.; Park, H.C.; Lim, D.H.; Choi, Y.; Jung, S.H.; Paik, S.W.; Kim, S.H.; Jeong, W.K.; Kim, Y.K. The role of diffusion-weighted magnetic resonance imaging in the treatment response evaluation of hepatocellular carcinoma patients treated with radiation therapy. Int. J. Radiat. Oncol. Biol. Phys. 2014, 89, 814–821.
  49. Eccles, C.L.; Haider, E.A.; Haider, M.A.; Fung, S.; Lockwood, G.; Dawson, L.A. Change in diffusion weighted MRI during liver cancer radiotherapy: Preliminary observations. Acta Oncol. 2009, 48, 1034–1043.
  50. Omiya, Y.; Motosugi, U.; Morisaka, H.; Onishi, H. Liver parenchymal change after stereotactic radiotherapy for hepatocellular carcinoma using DWI and MRE. In Proceedings of the Annual Meeting of the International Society of Magnetic Resonance Imaging 2021, Beijing, China, 10–12 September 2021.
  51. Lewis, B.C. Radiotherapy Response Using Intravoxel Incoherent Motion Magnetic Resonance Imaging in Liver Patients Treated with Stereotactic Body Radiotherapy. Ph.D. Thesis, Virginia Commonwealth University, Richmond, VA, USA, 2019.
  52. Liang, P.C.; Ch’ang, H.J.; Hsu, C.; Tseng, S.S.; Shih, T.T.F.; Wu Liu, T. Dynamic MRI signals in the second week of radiotherapy relate to treatment outcomes of hepatocellular carcinoma: A preliminary result. Liver Int. 2007, 27, 516–528.
  53. Cao, Y.; Wang, H.; Johnson, T.D.; Pan, C.; Hussain, H.; Balter, J.M.; Normolle, D.; Ben-Josef, E.; Ten Haken, R.K.; Lawrence, T.S.; et al. Prediction of liver function by using magnetic resonance-based portal venous perfusion imaging. Int. J. Radiat. Oncol. Biol. Phys. 2013, 85, 258–263.
  54. Wei, L.; Simeth, J.; Aryal, M.P.; Matuszak, M.; Ten Haken, R.K.; Cuneo, K.; Lawrence, T.S.; Cao, Y. The Effect of Stereotactic Body Radiation Therapy for Hepatocellular Cancer on Regional Hepatic Liver Function. Int. J. Radiat. Oncol. Biol. Phys. 2022.
  55. Wu, V.W.; Epelman, M.A.; Wang, H.; Edwin Romeijn, H.; Feng, M.; Cao, Y.; Ten Haken, R.K.; Matuszak, M.M. Optimizing global liver function in radiation therapy treatment planning. Phys. Med. Biol. 2016, 61, 6465–6484.
  56. Yadav, P.; Kuczmarska-Haas, A.; Musunuru, H.B.; Witt, J.; Blitzer, G.; Mahler, P.; Bassetti, M.F. Evaluating dose constraints for radiation induced liver damage following magnetic resonance image guided Stereotactic Body radiotherapy. Phys. Imaging Radiat. Oncol. 2021, 17, 91–94.
  57. Doi, H.; Shiomi, H.; Masai, N.; Tatsumi, D.; Igura, T.; Imai, Y.; Oh, R.J. Threshold doses and prediction of visually apparent liver dysfunction after stereotactic body radiation therapy in cirrhotic and normal livers using magnetic resonance imaging. J. Radiat. Res. 2016, 57, 294–300.
  58. Ghita, M.; Drexler, D.A.; Kovács, L.; Copot, D.; Muresan, C.I.; Ionescu, C.M. Model-Based Management of Lung Cancer Radiation Therapy. IFAC-PapersOnLine 2020, 53, 15928–15933.
  59. Ghita, M.; Billiet, C.; Copot, D.; Verellen, D.; Ionescu, C.M. Model Calibration of Pharmacokinetic-Pharmacodynamic Lung Tumour Dynamics for Anticancer Therapies. J. Clin. Med. 2022, 11, 1006.
  60. Suresh, K.; Owen, D.; Bazzi, L.; Jackson, W.; Ten Haken, R.K.; Cuneo, K.; Feng, M.; Lawrence, T.S.; Schipper, M.J. Using Indocyanine Green Extraction to Predict Liver Function After Stereotactic Body Radiation Therapy for Hepatocellular Carcinoma. Int. J. Radiat. Oncol. Biol. Phys. 2018, 100, 131–137.
  61. Feng, M.; Suresh, K.; Schipper, M.J.; Bazzi, L.; Ben-Josef, E.; Matuszak, M.M.; Parikh, N.D.; Welling, T.H.; Normolle, D.; Ten Haken, R.K.; et al. Individualized Adaptive Stereotactic Body Radiotherapy for Liver Tumors in Patients at High Risk for Liver Damage: A Phase 2 Clinical Trial. JAMA Oncol. 2018, 4, 40–47.
  62. Jackson, W.C.; Tang, M.; Maurino, C.; Mendiratta-Lala, M.; Parikh, N.D.; Matuszak, M.M.; Dow, J.S.; Cao, Y.; Mayo, C.S.; Ten Haken, R.K.; et al. Individualized Adaptive Radiation Therapy Allows for Safe Treatment of Hepatocellular Carcinoma in Patients With Child-Turcotte-Pugh B Liver Disease. Int. J. Radiat. Oncol. Biol. Phys. 2021, 109, 212–219.
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