David Aramburu Nuñez1,2, Antonio Lopez Medina3, Moises Mera Iglesias4, Francisco Salvador Gomez5, Vaios Hatzoglou6, Ramesh Paudyal1, Alfonso Calzado2, Joseph O Deasy1, Amita Shukla-Dave7, and Victor M Muñoz8
1Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY, United States, 2Department of Radiology, Complutense University, Madrid, Spain, 3Medical Physics & Radiological Protection, Galaria - Hospital do Meixoeiro – Complexo Hospitalario Universitario de Vigo, Vigo, Spain, 4Medical Physics, Oncoserv, Santiago de los Caballeros, Dominican Republic, 5Medical Physics and Radiological Protection, Galaria - Hospital do Meixoeiro – Complexo Hospitalario Universitario de Vigo, Vigo, Spain, 6Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, United States, 7Medical Physics & Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, United States, 8Radiation Oncology, Galaria - Hospital do Meixoeiro – Complexo Hospitalario Universitario de Vigo, Vigo, Spain
Synopsis
Biologically
guided radiotherapy needs an understanding of how different functional imaging
techniques interact and link together. DW-MRI and 18F FDG-PET techniques were
used in this study for achieving this objective. 5 HPV-, HNSCC patients
underwent 20 DW-MRI and 10 18F-FDG-PET/CT scans before and during radiation
therapy. ADC maps derived from DW-MRI and SUV values from 18F-FDG were used for
evaluating tumor response. The initial evaluation of the preliminary results
suggests that in these solid tumors cellularity is inversely proportional to
the glucose metabolic uptake. The survival status and functional metrics show
different trends for NED, AWD and DOD. Purpose
Human
papillomavirus-negative (HPV-) head and neck cancers have poor outcome compared
with HPV positive cancers
1. Thus, in an effort to perform biologically
guided radiotherapy it is critical to understand how different functional
imaging techniques
2 interact and potentially complement each other. Multimodality
imaging can provide useful anatomical and functional data about tumors,
including tumor cellularity measured by diffusion weighted (DW)-MRI and glucose
metabolic status measured by 18F-fluorodeoxyglucose (18F-FDG) PET. In order to characterize the tumor and to
implement new predictive models based on functional imaging data, we must
ensure we can extract as much information as possible from the available data.
Some of the main parameters to characterize tumor behavior, along with
radiation therapy treatment, must be initial tumor density, hypoxia,
malignancy-proliferation, dose to each voxel, and timing of the dose. In this
work we focus on DW-MRI and 18F FDG-PET derived parameters. The purpose of our
study was to non-invasively assess the tumor biology and metabolism of neck
nodal metastases in HPV- head and neck squamous cell carcinoma (HNSCC) by
investigating the relationship between tumor cellularity measured using DW-MRI
and glucose metabolism measured by 18F-FDG PET.
Methods
This study was
approved by local institutional review board and we obtained informed consent
from all patients. Five newly diagnosed HPV- HNSCC patients with metastatic
neck nodes underwent 20 DW-MRI imaging studies i.e. pre-, intra- [2 and 3
weeks] and post- chemo- radiation (dose of 70Gy) therapy. These patients also
had pre- and post-and 10 18F-FDG PET/CT scans. All MRI examinations were performed on a 1.5-T
scanner (Achieva; Philips Healthcare) with a Philips Sense Flex Medium
coil. Standard MR images for
localization and T2w Turbo Spin Echo images were obtained followed by DW-MRI
acquisition using a single-shot echo planar imaging (SS-EPI) (TE/TR (ms) =
77/5270; NEX=4, FOV (cm): 23-25, slice thickness (mm)= 6 with 3 b values of
b=0, 600 and 1000 s/mm², respectively. Whole-body PET/CT scan (Discovery, GE
Healthcare Bio-Sciences Corp.) was performed in 3D mode from head to thigh,
60min after intravenous administration of approximately 370MBq (±10%) of
18F-FDG with a FOV(cm)= 70, matrix 218 × 218. The pixel spacing was 5.47mm with
a slice thickness =3.27 mm. PET images were corrected for attenuation, scatter,
decay, dead time, random coincidences and slice sensitivity. Regions of interest (ROIs) were delineated
for each patient by the neuroradiologist on the primary and nodes using in-house
software. The matched regions of interests from both modalities were analyzed. We
registered all datasets (MRI studies, radiation dose distributions and PET/CT)
in order to extract each voxel’s information (signal intensity, radiation dose
and Uptake) using the software: ARTFIBio 0.6.23. To examine the correlations between DW-MRI derived
apparent diffusion coefficient (ADC [mm2/s]) metric using mono-exponential
fitting4 and mean of standard uptake value (SUV) measurements using
established method5 from 18F-FDG PET, the non-parametric Spearman
correlation coefficient was calculated. All patients had a clinical follow-up
as standard of care and survival status was documented into groups at 1year: no
evidence of disease [NED], alive with disease [AWD], and dead of disease [DOD].
Results
For the 5
patients, a total of 4 primary tumors and 9 nodes were analyzed. One patient
had unknown primary tumor. There was a strong negative correlation between the
mean of the pretreatment ADC (ρ=-0.6, p=0.008) and the 18F-FDG SUV (Figure 1). On
last 1 year clinical follow up the survival status of patients was as follows:
1 NED, 2 AWD and 2 DOD. No primary was visible by MRI for delineation on the
post-treatment MRI study for all patients.
No node was visible by MRI for delineation on the post-treatment MRI
except in the DOD patients. ADC values for pre-, 2 intra- and 1 post -treatment
MRIs from primary and node of representative DOD, AWD and NED patients are
shown in Table 1 (Figure 2). Figure 3 shows different trends depending on the
outcome when ADC is plotted versus radiation dose.
Discussion
Multi modality
imaging offers much more information about tumor biology and metabolism than
the individual datasets on their own. The initial evaluation of the preliminary
results suggests that in these solid tumors cellularity is inversely
proportional to the glucose metabolic uptake. The survival status and
functional metrics show different trends for NED, AWD and DOD.
Conclusion
These initial
findings need to be validated in larger populations so that these patients can
receive individualized radiation therapy.
Acknowledgements
We thank the
National Health Institute of Spain for supporting this work with ISCIII Grant
PI11/02035,BIOCAPS, and the Galician Government through the project CN 2012/260
“Consolidation Research Units: AtlantTIC”.References
1.
Fakhry C, Westra WH, Li S, Cmelak A, Ridge JA, Pinto H, Forastiere A, Gillison
ML, “Improved survival of patients with human papillomavirus-positive head and
neck squamous cell carcinoma in a prospective clinical trial” J Natl Cancer
Inst. 2008 Feb 20;100(4):261-9.
2. Jansen JF,
Schöder H, Lee NY, Stambuk HE, Wang Y, Fury MG, Patel SG, Pfister DG, Shah JP,
Koutcher JA, Shukla-Dave A. Tumor
metabolism and perfusion in head and neck squamous cell carcinoma: pretreatment
multimodality imaging with 1H magnetic resonance spectroscopy, dynamic
contrast-enhanced MRI, and [18F]FDG-PET. Int J Radiat Oncol Biol Phys. 2012;82(1):299-307.
3.
Landesa-Vázquez, I.., Alba-Castro, J.L, Mera-Iglesias, M., Aramburu-Núñez, D.,
López-Medina, and A. Muñóz-Garzón, V., "ARTFIBio: A Cross-Platform Image
Registration Tool for Tumor Response Quantification in Head and Neck
Cancer," in 2nd IEEE Int. Conf. on Biomedical and Health Informatics,
Valencia (Spain), 2014.
4. Stejskal,
E. O. and Tanner, J. E., "Spin diffusion measurements: spin echoes in the
presence of a time dependent field gradient," J Chem Phys, p. 42:288–292,
1965.
5. IAEA,
Quantitative Nuclear Medicine Imaging: Concepts, Requirements and Methods, IAEA
Library, 2014.