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Wang H, Yang J, Lee A, Phan J, Lim TY, Fuller CD, Han EY, Rhee DJ, Salzillo T, Zhao Y, Chopra N, Pham M, Castillo P, Sobremonte A, Moreno AC, Reddy JP, Rosenthal D, Garden AS, Wang X. MR-guided stereotactic radiation therapy for head and neck cancers. Clin Transl Radiat Oncol 2024; 46:100760. [PMID: 38510980 PMCID: PMC10950743 DOI: 10.1016/j.ctro.2024.100760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 02/01/2024] [Accepted: 03/06/2024] [Indexed: 03/22/2024] Open
Abstract
Purpose MR-guided radiotherapy (MRgRT) has the advantage of utilizing high soft tissue contrast imaging to track daily changes in target and critical organs throughout the entire radiation treatment course. Head and neck (HN) stereotactic body radiation therapy (SBRT) has been increasingly used to treat localized lesions within a shorter timeframe. The purpose of this study is to examine the dosimetric difference between the step-and-shot intensity modulated radiation therapy (IMRT) plans on Elekta Unity and our clinical volumetric modulated arc therapy (VMAT) plans on Varian TrueBeam for HN SBRT. Method Fourteen patients treated on TrueBeam sTx with VMAT treatment plans were re-planned in the Monaco treatment planning system for Elekta Unity MR-Linac (MRL). The plan qualities, including target coverage, conformity, homogeneity, nearby critical organ doses, gradient index and low dose bath volume, were compared between VMAT and Monaco IMRT plans. Additionally, we evaluated the Unity adaptive plans of adapt-to-position (ATP) and adapt-to-shape (ATS) workflows using simulated setup errors for five patients and assessed the outcomes of our treated patients. Results Monaco IMRT plans achieved comparable results to VMAT plans in terms of target coverage, uniformity and homogeneity, with slightly higher target maximum and mean doses. The critical organ doses in Monaco IMRT plans all met clinical goals; however, the mean doses and low dose bath volumes were higher than in VMAT plans. The adaptive plans demonstrated that the ATP workflow may result in degraded target coverage and OAR doses for HN SBRT, while the ATS workflow can maintain the plan quality. Conclusion The use of Monaco treatment planning and online adaptation can achieve dosimetric results comparable to VMAT plans, with the additional benefits of real-time tracking of target volume and nearby critical structures. This offers the potential to treat aggressive and variable tumors in HN SBRT and improve local control and treatment toxicity.
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Affiliation(s)
- He Wang
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Jinzhong Yang
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Anna Lee
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Jack Phan
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Tze Yee Lim
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Clifton D. Fuller
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Eun Young Han
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Dong Joo Rhee
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Travis Salzillo
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Yao Zhao
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Nitish Chopra
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Mary Pham
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Pam Castillo
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Angela Sobremonte
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, USA
| | - Amy C. Moreno
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Jay P. Reddy
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - David Rosenthal
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Adam S. Garden
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Xin Wang
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX, USA
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Khamis Y, Mohamed AS, Abobakr M, He R, Wahid KA, Ahmed SM, Salzillo T, Dede C, Naser M, Ding Y, Wang J, Preston K, El-Habashy D, Fadel S, Ismail AA, Fuller CD. Dynamic Contrast Enhanced MRI as a Biomarker of Tumor Response and Oncologic Outcomes in Head and Neck Cancer: Results of a Single Institution Prospective Imaging Study. Int J Radiat Oncol Biol Phys 2023; 117:e677-e678. [PMID: 37785995 DOI: 10.1016/j.ijrobp.2023.06.2134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) We aim to determine the correlation between vascular parameters of Dynamic contrast enhanced (DCE) MRIs and tumor response and outcomes in head and neck (HNC) patients treated with definitive radiation therapy (RT). MATERIALS/METHODS Eighty-two HNC patients are included in this prospective study in one institute. All patients had malignant head and neck neoplasm indicative of curative- intent treatment. Patients were imaged using MRIs pre-, mid-, and post-RT completion at 8-12 weeks. T2-weighted sequences were used for tumor contouring then it was co-registered to respective DCE images. The response to treatment was checked at mid-radiotherapy (mid-RT) and at the end of RT. Mid-RT MRI was co-registered to baseline images and the manually segmented baseline primary tumor regions of interest were propagated to mid-RT images. Quantitative maps (Ktrans, Kep, Ve and Vp) were generated with the extended Tofts pharmacokinetic models and were used for analysis. These vascular parameters were presented as a mean value and percentile using histogram analysis and the following parameters were extracted using an in-house programming environment script: mean, 5th, 10th, 20th, 30th, 40th, 50th (i.e., median), 60th, 70th, 80th, 90th, 95th percentile. The non-parametric Wilcoxon signed-rank test was used to assess the changes of mid-RT DCE parameters compared to baseline. Recursive partitioning analysis (RPA) was used to identify the delta DCE threshold associated with relapse. We assessed the identified thresholds' correlation with oncological and survival endpoints using Cox regression with and without standard clinical variables. RESULTS The median age for patients is 61 years old (33-78 range). Never smokers are 39 (47%), 35 (43%) are former smoker and 8 (10%) are current smoker with a mean value of 14 pack per year and 26 standard deviations. Using AJCC 8th edition, 39 (47%) are stage I and 19 (23%) are stage II and stage III and IV are 15 (18%) and 9 (10%) respectively. HPV positive are 72 (88%). For patients with GTV-P at baseline (n = 60), 11 (18%) had mid-RT CR at the primary site which increased to 50 (83%) post-RT. The LC and RFS for the entire cohort were 91.4%, and 79.2% respectively. In GTV-P, none of the pre-radiotherapy DCE parameters were correlated with LC or RFS. Wilcoxon signed rank test was statistically significant in 80, 90 and 95 percentiles with (p<0.05). RPA analysis identified different thresholds for each DCE parameter, and its inclusions to the multivariate model improved its performance. In GTV-P, RPA analysis identified ΔKtrans 40 percentiles >15.6% at mid-RT as the most significant point. When this value of ΔKtrans added to the multivariate analysis it was associated with a significantly better model performance in RFS (p = 0.00001). CONCLUSION DCE parameters are a very promising tool to correlate with response and outcomes in H&N cancer patients. Future work is warranted for external validation of our findings.
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Affiliation(s)
- Y Khamis
- MD Anderson Cancer Center, Houston, TX; Department of clinical oncology and nuclear medicine, Faculty of Medicine, Alexandria University, Alexandria, Egypt
| | - A S Mohamed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - M Abobakr
- MD Anderson Cancer Center, Houston, TX
| | - R He
- MD Anderson Cancer Center, Houston, TX
| | - K A Wahid
- MD Anderson Cancer Center, Houston, TX
| | - S M Ahmed
- MD Anderson Cancer Center, Houston, TX
| | | | - C Dede
- MD Anderson Cancer Center, Houston, TX
| | - M Naser
- MD Anderson Cancer Center, Houston, TX
| | - Y Ding
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - J Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - K Preston
- MD Anderson Cancer Center, Houston, TX
| | | | - S Fadel
- Department of clinical oncology and nuclear medicine, Faculty of Medicine, Alexandria University, Alexandria, Egypt
| | - A A Ismail
- Department of clinical oncology and nuclear medicine, Faculty of Medicine, Alexandria University, Alexandria, Egypt
| | - C D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
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3
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El-Habashy D, Wahid KA, He R, Ding Y, Wang J, Preston K, Salzillo T, Naser M, McDonald B, Abobakr M, Shehata MA, Elkhouly E, Alagizy H, Hegazy AH, Fuller CD, Mohamed AS. Longitudinal Monitoring of Quantitative Imaging Kinetics of Primary Tumor and Nodal Volumes Using the MR-Linac Device in Head and Neck Cancer Patients. Int J Radiat Oncol Biol Phys 2023; 117:e663-e664. [PMID: 37785964 DOI: 10.1016/j.ijrobp.2023.06.2102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) We aim to characterize the serial quantitative apparent diffusion coefficient (ADC) changes of the target disease volume using diffusion-weighted imaging (DWI) acquired weekly during radiation therapy (RT) on a 1.5T MR-Linac and correlate these changes with tumor response and oncologic outcomes for head and neck squamous cell carcinoma (HNSCC) patients. MATERIALS/METHODS Thirty patients with pathologically confirmed HNSCC and received curative-intent RT at the University of Texas MD Anderson Cancer Center, were included in this prospective study. Baseline and weekly MRIs (weeks 1-6) were obtained, and various ADC parameters (mean, 5th, 10th, 20th, 30th, 40th, 50th, 60th, 70th, 80th, 90th and 95th percentile) were extracted from the target regions of interest (ROIs). Pre-RT and weekly ADC parameters were correlated with response during RT, loco-regional control, and the development of relapse using the Mann-Whitney U test. The Wilcoxon signed-rank test was used to compare the weekly ADC versus baseline values. Weekly volumetric changes (Δvolume) for each ROI were correlated with ΔADC using Spearman's Rho test. Recursive partitioning analysis (RPA) was performed to identify the optimal ΔADC threshold associated with different oncologic outcomes. RESULTS There was an overall significant rise in all ADC parameters during different time points of RT compared to baseline values for both GTV-P & GTV-N. The increased ADC values for GTV-P were statistically significant only for primary tumors achieving CR during RT. RPA identified GTV-P ΔADC 5th percentile >13% at the 3rd week of RT as the most significant parameter associated with CR for GTV-P during RT (p <0.001). Baseline ADC parameters didn't significantly correlate with response to RT or other oncologic outcomes. There was a significant decrease in residual volume of both GTV-P & GTV-N throughout the course of RT. Additionally, a significant negative correlation between mean ΔADC and Δvolume for GTV-P at the 3rd and 4th week of RT was detected (r = -0.39, p = 0.044 & r = -0.45, p = 0.019, respectively). CONCLUSION Assessment of ADC kinetics at regular intervals throughout RT is potentially able to predict the response to RT and oncologic outcome. Further studies with larger cohorts and multi-institutional data are needed for validation of our results.
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Affiliation(s)
- D El-Habashy
- MD Anderson Cancer Center, Houston, TX; Faculty of medicine, Menoufia university, Egypt, Shebin Elkom, Egypt
| | - K A Wahid
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - R He
- MD Anderson Cancer Center, Houston, TX
| | - Y Ding
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - J Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - K Preston
- MD Anderson Cancer Center, Houston, TX
| | | | - M Naser
- MD Anderson Cancer Center, Houston, TX
| | | | - M Abobakr
- MD Anderson Cancer Center, Houston, TX
| | - M A Shehata
- Faculty of medicine, Menoufia university, Egypt, Shebin Elkom, Egypt
| | - E Elkhouly
- Menoufia University, Shebin Elkom, Al Minufiy, Egypt
| | - H Alagizy
- Faculty of medicine, Menoufia university, Egypt, Shebin Elkom, Egypt
| | - A H Hegazy
- Faculty of medicine, Menoufia university, Egypt, Shebin Elkom, Egypt
| | - C D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - A S Mohamed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
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Abobakr M, He R, Wahid KA, Salzillo T, Ahmed SM, El-Habashy D, Khamis Y, Dede C, Ding Y, Wang J, Lai SY, Fuller CD, Mohamed AS. Assessment of Dynamic Contrast Enhanced (DCE) MRI for Detection of Radiotherapy Induced Alteration in Mandibular Vasculature. Int J Radiat Oncol Biol Phys 2023; 117:S31-S32. [PMID: 37784475 DOI: 10.1016/j.ijrobp.2023.06.295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) We aim to determine the kinetics of DCE-MRI changes in various mandibular risk volumes based on radiation (RT) dose received. MATERIALS/METHODS Eighty-eight head and neck cancer (HNC) patients (Pts) who underwent definitive RT were enrolled in this prospective study after IRB approval and informed consent. Images were acquired at pre-RT (Baseline), 3 weeks after RT start date (Mid-RT), 3 mos post-RT (PostRT1), and 6 mos post-RT (PostRT2). Manually segmented mandibular volumes on T2-weighted images were propagated to co-registered DCE-MRIs. Planning CTs and dose grids were also co-registered to corresponding baseline T2 images to create 3-D dose subvolumes. These were used to create 3 risk subvolumes; <30 Gy, 30-50 Gy, and >50 Gy ROIs. DCE images of different timepoints (TPs) were deformably co-registered and the dose subvolumes were propagated to each TP. We used the extended-Tofts model to generate the vascular quantitative maps (Ktrans and Ve). Each subvolume histogram parameters were extracted at each TP. Wilcoxon Signed Rank test was used to compare the changes at different TPs compared to baseline. We classified Pts' delta parameters at different TPs -based on our prior extensive QA assessment- into Pts with stable vascular profile (±25% change), Pts with significant increase (>25% change) and Pts with significant decrease (<-25%). Chi-square test was used to assess the change at different TPs. RESULTS For <30 Gy subvolumes, there were no significant changes (p > 0.05) in the studied DCE parameters at all TPs except a significant decrease (p < 0.001) in median Ktrans at PostRT2. For 30-50 Gy subvolumes, there was a significant increase in median Ktrans that started at MidRT (p = 0.006) and continued at PostRT1 (p = 0.04) but recovered to baseline values at PostRT2. Median Ve on the other hand only showed significant increase at PostRT1 (p = 0.001), but other TPs were not significantly different compared to baseline. Similarly, subvolumes >50 Gy showed same kinetics as in 30-50 Gy with significant increase of Ktrans at MidRT and PostRT1 and significant increase in Ve in only PostRT1 (P <0.05). For <30 Gy, there was significant increase in the number of Pts with stable or decrease in Ktrans at PostRT2 compared to earlier TPs (70% vs. 60% at PostRT1 and 54% at MidRT p = 0.003). 30-50 Gy subvolumes showed similar profile like <30 Gy with significant increase in the percentage of Pts with recovery at PostRT2. However, for >50 Gy, there was no significant increase in the number of Pts who recovered at PostRT2 (p = 0.3). Ve showed no significant increase in the percentage of Pts with recovery at different TPs (p > 0.05). CONCLUSION Results showed that for all dose mandibular subvolumes, there is an acute vascular insult that tends to recover at +6 months post-RT except for a selective group of patients who continue to have persistence of the vascular insult at high dose subvolumes. These findings are of importance for future selection of high risk population for prophylactic intervention against osteoradionecrosis.
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Affiliation(s)
- M Abobakr
- MD Anderson Cancer Center, Houston, TX
| | - R He
- MD Anderson Cancer Center, Houston, TX
| | - K A Wahid
- MD Anderson Cancer Center, Houston, TX
| | | | - S M Ahmed
- MD Anderson Cancer Center, Houston, TX
| | | | - Y Khamis
- MD Anderson Cancer Center, Houston, TX
| | - C Dede
- MD Anderson Cancer Center, Houston, TX
| | - Y Ding
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - J Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - S Y Lai
- Department of Head and Neck Surgery, The University of Texas M.D. Anderson Cancer Center, Houston, TX
| | - C D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - A S Mohamed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
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El-Habashy DM, Wahid KA, Renjie H, McDonald B, Mulder SJ, Ding Y, Salzillo T, Stephen L, Christodouleas J, Dresner A, Wang J, Naser MA, Fuller CD, Mohamed ASR. Weekly Intra-Treatment Diffusion Weighted Imaging Dataset for Head and Neck Cancer Patients Undergoing MR-linac Treatment. medRxiv 2023:2023.08.18.23294280. [PMID: 37645931 PMCID: PMC10462225 DOI: 10.1101/2023.08.18.23294280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Radiation therapy (RT) is a crucial treatment for head and neck squamous cell carcinoma (HNSCC), however it can have adverse effects on patients' long-term function and quality of life. Biomarkers that can predict tumor response to RT are being explored to personalize treatment and improve outcomes. While tissue and blood biomarkers have limitations, imaging biomarkers derived from magnetic resonance imaging (MRI) offer detailed information. The integration of MRI and a linear accelerator in the MR-Linac system allows for MR-guided radiation therapy (MRgRT), offering precise visualization and treatment delivery. This data descriptor offers a valuable repository for weekly intra-treatment diffusion-weighted imaging (DWI) data obtained from head and neck cancer patients. By analyzing the sequential DWI changes and their correlation with treatment response, as well as oncological and survival outcomes, the study provides valuable insights into the clinical implications of DWI in HNSCC. [Table: see text].
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Affiliation(s)
- Dina M El-Habashy
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Clinical Oncology and Nuclear Medicine, Menoufia University, Shebin Elkom, Egypt
| | - Kareem A Wahid
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - He Renjie
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Brigid McDonald
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Samuel J. Mulder
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yao Ding
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Travis Salzillo
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Lai Stephen
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Molecular and Cellular Oncology, Division of Basic Science Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Alex Dresner
- Philips Healthcare MR Oncology, Cleveland, Ohio, USA
| | - Jihong Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Mohamed A Naser
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Abdallah Sherif Radwan Mohamed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Radiation Oncology, Baylor College of Medicine, Houston, TX, USA
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McDonald BA, Salzillo T, Mulder S, Ahmed S, Dresner A, Preston K, He R, Christodouleas J, Mohamed ASR, Philippens M, van Houdt P, Thorwarth D, Wang J, Shukla Dave A, Boss M, Fuller CD. Prospective evaluation of in vivo and phantom repeatability and reproducibility of diffusion-weighted MRI sequences on 1.5 T MRI-linear accelerator (MR-Linac) and MR simulator devices for head and neck cancers. Radiother Oncol 2023; 185:109717. [PMID: 37211282 PMCID: PMC10527507 DOI: 10.1016/j.radonc.2023.109717] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 05/12/2023] [Accepted: 05/13/2023] [Indexed: 05/23/2023]
Abstract
INTRODUCTION Diffusion-weighted imaging (DWI) on MRI-linear accelerator (MR-linac) systems can potentially be used for monitoring treatment response and adaptive radiotherapy in head and neck cancers (HNC) but requires extensive validation. We performed technical validation to compare six total DWI sequences on an MR-linac and MR simulator (MR sim) in patients, volunteers, and phantoms. METHODS Ten human papillomavirus-positive oropharyngeal cancer patients and ten healthy volunteers underwent DWI on a 1.5 T MR-linac with three DWI sequences: echo planar imaging (EPI), split acquisition of fast spin echo signals (SPLICE), and turbo spin echo (TSE). Volunteers were also imaged on a 1.5 T MR sim with three sequences: EPI, BLADE (vendor tradename), and readout segmentation of long variable echo trains (RESOLVE). Participants underwent two scan sessions per device and two repeats of each sequence per session. Repeatability and reproducibility within-subject coefficient of variation (wCV) of mean ADC were calculated for tumors and lymph nodes (patients) and parotid glands (volunteers). ADC bias, repeatability/reproducibility metrics, SNR, and geometric distortion were quantified using a phantom. RESULTS In vivo repeatability/reproducibility wCV for parotids were 5.41%/6.72%, 3.83%/8.80%, 5.66%/10.03%, 3.44%/5.70%, 5.04%/5.66%, 4.23%/7.36% for EPIMR-linac, SPLICE, TSE, EPIMR sim, BLADE, RESOLVE. Repeatability/reproducibility wCV for EPIMR-linac, SPLICE, TSE were 9.64%/10.28%, 7.84%/8.96%, 7.60%/11.68% for tumors and 7.80%/9.95%, 7.23%/8.48%, 10.82%/10.44% for nodes. All sequences except TSE had phantom ADC biases within ± 0.1x10-3 mm2/s for most vials (EPIMR-linac, SPLICE, and BLADE had 2, 3, and 1 vials out of 13 with larger biases, respectively). SNR of b = 0 images was 87.3, 180.5, 161.3, 171.0, 171.9, 130.2 for EPIMR-linac, SPLICE, TSE, EPIMR sim, BLADE, RESOLVE. CONCLUSION MR-linac DWI sequences demonstrated near-comparable performance to MR sim sequences and warrant further clinical validation for treatment response assessment in HNC.
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Affiliation(s)
| | | | - Samuel Mulder
- The University of Texas MD Anderson Cancer Center, USA
| | - Sara Ahmed
- The University of Texas MD Anderson Cancer Center, USA
| | | | | | - Renjie He
- The University of Texas MD Anderson Cancer Center, USA
| | | | | | | | | | | | - Jihong Wang
- The University of Texas MD Anderson Cancer Center, USA
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Wahid K, Ahmed S, He R, van Dijk L, Teuwen J, McDonald B, Salama V, Mohamed A, Salzillo T, Dede C, Taku N, Lai S, Fuller C, Naser M. Auto-Segmentation of Oropharyngeal Cancer Primary Tumors Using Multiparametric MRI-Based Deep Learning. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2021.12.072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Wahid KA, Ahmed S, He R, van Dijk LV, Teuwen J, McDonald BA, Salama V, Mohamed AS, Salzillo T, Dede C, Taku N, Lai SY, Fuller CD, Naser MA. Evaluation of deep learning-based multiparametric MRI oropharyngeal primary tumor auto-segmentation and investigation of input channel effects: Results from a prospective imaging registry. Clin Transl Radiat Oncol 2022; 32:6-14. [PMID: 34765748 PMCID: PMC8570930 DOI: 10.1016/j.ctro.2021.10.003] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 09/24/2021] [Accepted: 10/10/2021] [Indexed: 12/09/2022] Open
Abstract
BACKGROUND/PURPOSE Oropharyngeal cancer (OPC) primary gross tumor volume (GTVp) segmentation is crucial for radiotherapy. Multiparametric MRI (mpMRI) is increasingly used for OPC adaptive radiotherapy but relies on manual segmentation. Therefore, we constructed mpMRI deep learning (DL) OPC GTVp auto-segmentation models and determined the impact of input channels on segmentation performance. MATERIALS/METHODS GTVp ground truth segmentations were manually generated for 30 OPC patients from a clinical trial. We evaluated five mpMRI input channels (T2, T1, ADC, Ktrans, Ve). 3D Residual U-net models were developed and assessed using leave-one-out cross-validation. A baseline T2 model was compared to mpMRI models (T2 + T1, T2 + ADC, T2 + Ktrans, T2 + Ve, all five channels [ALL]) primarily using the Dice similarity coefficient (DSC). False-negative DSC (FND), false-positive DSC, sensitivity, positive predictive value, surface DSC, Hausdorff distance (HD), 95% HD, and mean surface distance were also assessed. For the best model, ground truth and DL-generated segmentations were compared through a blinded Turing test using three physician observers. RESULTS Models yielded mean DSCs from 0.71 ± 0.12 (ALL) to 0.73 ± 0.12 (T2 + T1). Compared to the T2 model, performance was significantly improved for FND, sensitivity, surface DSC, HD, and 95% HD for the T2 + T1 model (p < 0.05) and for FND for the T2 + Ve and ALL models (p < 0.05). No model demonstrated significant correlations between tumor size and DSC (p > 0.05). Most models demonstrated significant correlations between tumor size and HD or Surface DSC (p < 0.05), except those that included ADC or Ve as input channels (p > 0.05). On average, there were no significant differences between ground truth and DL-generated segmentations for all observers (p > 0.05). CONCLUSION DL using mpMRI provides reasonably accurate segmentations of OPC GTVp that may be comparable to ground truth segmentations generated by clinical experts. Incorporating additional mpMRI channels may increase the performance of FND, sensitivity, surface DSC, HD, and 95% HD, and improve model robustness to tumor size.
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Affiliation(s)
- Kareem A. Wahid
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Sara Ahmed
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Renjie He
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Lisanne V. van Dijk
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Jonas Teuwen
- Department of Medical Imaging, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Brigid A. McDonald
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Vivian Salama
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Abdallah S.R. Mohamed
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Travis Salzillo
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Cem Dede
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Nicolette Taku
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Stephen Y. Lai
- Department of Head and Neck Surgery, University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Clifton D. Fuller
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Mohamed A. Naser
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX USA
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9
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Hall WA, Paulson E, Li XA, Erickson B, Schultz C, Tree A, Awan M, Low DA, McDonald BA, Salzillo T, Glide-Hurst CK, Kishan AU, Fuller CD. Magnetic resonance linear accelerator technology and adaptive radiation therapy: An overview for clinicians. CA Cancer J Clin 2022; 72:34-56. [PMID: 34792808 PMCID: PMC8985054 DOI: 10.3322/caac.21707] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 09/01/2021] [Accepted: 09/22/2021] [Indexed: 12/25/2022] Open
Abstract
Radiation therapy (RT) continues to play an important role in the treatment of cancer. Adaptive RT (ART) is a novel method through which RT treatments are evolving. With the ART approach, computed tomography or magnetic resonance (MR) images are obtained as part of the treatment delivery process. This enables the adaptation of the irradiated volume to account for changes in organ and/or tumor position, movement, size, or shape that may occur over the course of treatment. The advantages and challenges of ART maybe somewhat abstract to oncologists and clinicians outside of the specialty of radiation oncology. ART is positioned to affect many different types of cancer. There is a wide spectrum of hypothesized benefits, from small toxicity improvements to meaningful gains in overall survival. The use and application of this novel technology should be understood by the oncologic community at large, such that it can be appropriately contextualized within the landscape of cancer therapies. Likewise, the need to test these advances is pressing. MR-guided ART (MRgART) is an emerging, extended modality of ART that expands upon and further advances the capabilities of ART. MRgART presents unique opportunities to iteratively improve adaptive image guidance. However, although the MRgART adaptive process advances ART to previously unattained levels, it can be more expensive, time-consuming, and complex. In this review, the authors present an overview for clinicians describing the process of ART and specifically MRgART.
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MESH Headings
- History, 20th Century
- History, 21st Century
- Humans
- Magnetic Resonance Imaging, Interventional/history
- Magnetic Resonance Imaging, Interventional/instrumentation
- Magnetic Resonance Imaging, Interventional/methods
- Magnetic Resonance Imaging, Interventional/trends
- Neoplasms/diagnostic imaging
- Neoplasms/radiotherapy
- Particle Accelerators
- Radiation Oncology/history
- Radiation Oncology/instrumentation
- Radiation Oncology/methods
- Radiation Oncology/trends
- Radiotherapy Planning, Computer-Assisted/history
- Radiotherapy Planning, Computer-Assisted/instrumentation
- Radiotherapy Planning, Computer-Assisted/methods
- Radiotherapy Planning, Computer-Assisted/trends
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Affiliation(s)
- William A. Hall
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Eric Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - X. Allen Li
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Beth Erickson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Christopher Schultz
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Alison Tree
- The Royal Marsden National Health Service Foundation Trust and the Institute of Cancer Research, London, United Kingdom
| | - Musaddiq Awan
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Daniel A. Low
- Department of Radiation Oncology, University of California-Los Angeles, Los Angeles, California
| | - Brigid A. McDonald
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Travis Salzillo
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Carri K. Glide-Hurst
- Department of Radiation Oncology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Amar U. Kishan
- Department of Radiation Oncology, University of California-Los Angeles, Los Angeles, California
| | - Clifton D. Fuller
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
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10
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Wahid KA, He R, McDonald BA, Anderson BM, Salzillo T, Mulder S, Wang J, Sharafi CS, McCoy LA, Naser MA, Ahmed S, Sanders KL, Mohamed ASR, Ding Y, Wang J, Hutcheson K, Lai SY, Fuller CD, van Dijk LV. Intensity standardization methods in magnetic resonance imaging of head and neck cancer. Phys Imaging Radiat Oncol 2021; 20:88-93. [PMID: 34849414 PMCID: PMC8607477 DOI: 10.1016/j.phro.2021.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 11/09/2021] [Accepted: 11/10/2021] [Indexed: 11/10/2022] Open
Abstract
Background and Purpose Conventional magnetic resonance imaging (MRI) poses challenges in quantitative analysis because voxel intensity values lack physical meaning. While intensity standardization methods exist, their effects on head and neck MRI have not been investigated. We developed a workflow based on healthy tissue region of interest (ROI) analysis to determine intensity consistency within a patient cohort. Through this workflow, we systematically evaluated intensity standardization methods for MRI of head and neck cancer (HNC) patients. Materials and Methods Two HNC cohorts (30 patients total) were retrospectively analyzed. One cohort was imaged with heterogenous acquisition parameters (HET cohort), whereas the other was imaged with homogenous acquisition parameters (HOM cohort). The standard deviation of cohort-level normalized mean intensity (SD NMIc), a metric of intensity consistency, was calculated across ROIs to determine the effect of five intensity standardization methods on T2-weighted images. For each cohort, a Friedman test followed by a post-hoc Bonferroni-corrected Wilcoxon signed-rank test was conducted to compare SD NMIc among methods. Results Consistency (SD NMIc across ROIs) between unstandardized images was substantially more impaired in the HET cohort (0.29 ± 0.08) than in the HOM cohort (0.15 ± 0.03). Consequently, corrected p-values for intensity standardization methods with lower SD NMIc compared to unstandardized images were significant in the HET cohort (p < 0.05) but not significant in the HOM cohort (p > 0.05). In both cohorts, differences between methods were often minimal and nonsignificant. Conclusions Our findings stress the importance of intensity standardization, either through the utilization of uniform acquisition parameters or specific intensity standardization methods, and the need for testing intensity consistency before performing quantitative analysis of HNC MRI.
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Affiliation(s)
- Kareem A Wahid
- Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Renjie He
- Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Brigid A McDonald
- Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Brian M Anderson
- Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Travis Salzillo
- Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Sam Mulder
- Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jarey Wang
- Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Christina Setareh Sharafi
- Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Lance A McCoy
- Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Mohamed A Naser
- Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Sara Ahmed
- Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Keith L Sanders
- Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Abdallah S R Mohamed
- Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Yao Ding
- Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jihong Wang
- Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Kate Hutcheson
- Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Stephen Y Lai
- Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Clifton D Fuller
- Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Lisanne V van Dijk
- Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
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11
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Wang J, Salzillo T, Jiang Y, Mackeyev Y, David Fuller C, Chung C, Choi S, Hughes N, Ding Y, Yang J, Vedam S, Krishnan S. Stability of MRI contrast agents in high-energy radiation of a 1.5T MR-Linac. Radiother Oncol 2021; 161:55-64. [PMID: 34089753 PMCID: PMC8324543 DOI: 10.1016/j.radonc.2021.05.023] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 05/24/2021] [Accepted: 05/26/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND Gadolinium-based contrast is often used when acquiring MR images for radiation therapy planning for better target delineation. In some situations, patients may still have residual MRI contrast agents in their tissue while being treated with high-energy radiation. This is especially true when MRI contrast agents are administered during adaptive treatment replanning for patients treated on MR-Linac systems. PURPOSE The purpose of this study was to analyze the molecular stability of MRI contrast agents when exposed to high energy photons and the associated secondary electrons in a 1.5T MR-Linac system. This was the first step in assessing the safety of administering MRI contrast agents throughout the course of treatment. MATERIALS AND METHODS Two common MRI contrast agents were irradiated with 7 MV photons to clinical dose levels. The irradiated samples were analyzed using liquid chromatography-high resolution mass spectrometry to detect degradation products or conformational alterations created by irradiation with high energy photons and associated secondary electrons. RESULTS No significant change in chemical composition or displacement of gadolinium ions from their chelates was discovered in samples irradiated with 7 MV photons at relevant clinical doses in a 1.5T MR-Linac. Additionally, no significant correlation between concentrations of irradiated MRI contrast agents and radiation dose was observed. CONCLUSION The chemical composition stability of the irradiated contrast agents is promising for future use throughout the course of patient treatment. However, in vivo studies are needed to confirm that unexpected metabolites are not created in biological milieus.
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Affiliation(s)
- Jihong Wang
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, United States.
| | - Travis Salzillo
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, United States
| | - Yongying Jiang
- The Institute for Applied Cancer Science, MD Anderson Cancer Center, Houston, United States
| | - Yuri Mackeyev
- Department of Radiation Oncology, Mayo Clinic, Jacksonville, United States
| | - Clifton David Fuller
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, United States
| | - Caroline Chung
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, United States
| | - Seungtaek Choi
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, United States
| | - Neil Hughes
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, United States
| | - Yao Ding
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, United States
| | - Jinzhong Yang
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, United States
| | - Sastry Vedam
- Department of Radiation Oncology, University of Maryland, Baltimore, United States
| | - Sunil Krishnan
- Department of Radiation Oncology, Mayo Clinic, Jacksonville, United States
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12
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Dutta P, Sanchez ER, Zhang Y, Salzillo T, Raj P, Lee J, Millward N, Maitra A, McAllister F, Bhattacharya P. Abstract 370: Hyperpolarized magnetic resonance metabolic imaging in pancreatic cancer research: Early detection, assessing aggressiveness and real-time monitoring treatment response. Cancer Res 2018. [DOI: 10.1158/1538-7445.am2018-370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Pancreatic cancer is on pace to become the second leading cause of cancer-related death. The high mortality rate results from a lack of methods for early detection and the inability to successfully treat patients once diagnosed. Pancreatic cancer cells have extensively reprogrammed metabolism, which is driven by oncogene-mediated pathways and the unique physiology of the tumor microenvironment. In our research, we are interrogating reprogrammed metabolism in pancreatic cancer. We have employed hyperpolarized metabolic imaging to measure noninvasively the metabolic plasticity as the diseases initiate, evolve and respond to the drugs. Genetically engineered mouse (GEM) model with progression of pancreatic intraepithelial neoplasm (PanIN) lesions has been used for early detection, patient-derived xenografts (PDX) model to assess aggressiveness, and orthotopic pancreatic cancer model for monitoring metabolically targeted therapeutic response. Hyperpolarization of pyruvate and in-vivo 13C MRS were performed using Hypersense (Oxford Instruments) and 7T MRI scanner with a dual tuned 1H/13C volume coil (Bruker), respectively. Tissue alanine and lactate concentrations were determined using a Bruker 500 MHz NMR spectrometer coupled with cryoprobe. Histology and immunohistochemistry were performed on excised tissue samples. Hyperpolarized pyruvate metabolism in PDX tumor was well captured in real time. Pyruvate was readily metabolized to lactate and alanine in vivo. The quantitative flux ratios lactate-to-pyruvate (Lac/Pyr) and alanine-to-lactate were determined. The most aggressive tumors showed the highest value of Lac/Pyr ratio. GEM model such as P48Cre;LSLKrasG12D mice were used for detection of early and advanced PanIN, which usually develop in these mice between 20 and 25 weeks. The imaging experiments were performed at the different stages of the disease. Progression of disease from tissue containing predominantly low-grade PanIN to tissue with high-grade PanIN showed a decreasing alanine/lactate concentration ratio as measured by 1H-NMR metabolomics. These results demonstrate that there are significant alterations of alanine transaminase (ALT) and lactate dehydrogenase (LDH) activities that favor the transformation of aggressive pancreatic cancer from PanIN lesion. The efficacy of a metabolically targeted drug was monitored in orthotopic pancreatic cancer mice by measuring flux ratio of Lac/Pyr after injecting hyperpolarized pyruvate before the tumor shrinkage. Metabolic imaging with hyperpolarized pyruvate and NMR metabolomics enabled detection and monitoring of the progression of pancreatic cancer lesions. Translation of this HP-MRI technique to the clinic has the potential to improve early detection and the management of patients' care.
Citation Format: Prasanta Dutta, Erick Riquelme Sanchez, Yu Zhang, Travis Salzillo,, Priyank Raj, Jaehyuk Lee, Niki Millward, Anirban Maitra, Florencia McAllister, Pratip Bhattacharya. Hyperpolarized magnetic resonance metabolic imaging in pancreatic cancer research: Early detection, assessing aggressiveness and real-time monitoring treatment response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 370.
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Affiliation(s)
| | | | - Yu Zhang
- UT MD Anderson Cancer Center, Houston, TX
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13
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Cappuccino C, Mazzeo PP, Salzillo T, Venuti E, Giunchi A, Della Valle RG, Brillante A, Bettini C, Melucci M, Maini L. A synergic approach of X-ray powder diffraction and Raman spectroscopy for crystal structure determination of 2,3-thienoimide capped oligothiophenes. Phys Chem Chem Phys 2018; 20:3630-3636. [DOI: 10.1039/c7cp06679a] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
This work presents a Raman based approach for the rapid identification of the molecular conformation in a series of new 2,3-thienoimide capped quaterthiophenes.
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Affiliation(s)
- C. Cappuccino
- Department of Chemistry “Giacomo Ciamician”
- Via Selmi 2 – University of Bologna
- Bologna
- Italy
| | - P. P. Mazzeo
- Dipartimento di Scienze Chimiche
- della Vita e della Sostenibilità Ambientale
- Università of Parma
- Parma
- Italy
| | - T. Salzillo
- Department of Industrial Chemistry “Toso Montanari” and INSTM-UdR Bologna
- Viale del Risorgimento
- 4 – University of Bologna
- I-40136 Bologna
- Italy
| | - E. Venuti
- Department of Industrial Chemistry “Toso Montanari” and INSTM-UdR Bologna
- Viale del Risorgimento
- 4 – University of Bologna
- I-40136 Bologna
- Italy
| | - A. Giunchi
- Department of Industrial Chemistry “Toso Montanari” and INSTM-UdR Bologna
- Viale del Risorgimento
- 4 – University of Bologna
- I-40136 Bologna
- Italy
| | - R. G. Della Valle
- Department of Industrial Chemistry “Toso Montanari” and INSTM-UdR Bologna
- Viale del Risorgimento
- 4 – University of Bologna
- I-40136 Bologna
- Italy
| | - A. Brillante
- Department of Industrial Chemistry “Toso Montanari” and INSTM-UdR Bologna
- Viale del Risorgimento
- 4 – University of Bologna
- I-40136 Bologna
- Italy
| | - C. Bettini
- Consiglio Nazionale delle Ricerche – Istituto per la Sintesi Organica e per la Fotoreattività (CNR-ISOF) Via P. Gobetti 101
- 40129 Bologna
- Italy
| | - M. Melucci
- Consiglio Nazionale delle Ricerche – Istituto per la Sintesi Organica e per la Fotoreattività (CNR-ISOF) Via P. Gobetti 101
- 40129 Bologna
- Italy
| | - L. Maini
- Department of Chemistry “Giacomo Ciamician”
- Via Selmi 2 – University of Bologna
- Bologna
- Italy
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