Prospective Study
Copyright ©The Author(s) 2017. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Radiol. Jan 28, 2017; 9(1): 17-26
Published online Jan 28, 2017. doi: 10.4329/wjr.v9.i1.17
Multimodality functional imaging using DW-MRI and 18F-FDG-PET/CT during radiation therapy for human papillomavirus negative head and neck squamous cell carcinoma: Meixoeiro Hospital of Vigo Experience
David Aramburu Núñez, Antonio Lopez Medina, Moisés Mera Iglesias, Francisco Salvador Gomez, Abhay Dave, Vaios Hatzoglou, Ramesh Paudyal, Alfonso Calzado, Joseph O Deasy, Amita Shukla-Dave, Victor M Muñoz
David Aramburu Núñez, Antonio Lopez Medina, Francisco Salvador Gomez, Department of Medical Physics and Radiological Protection, Galaria - Meixoeiro, University Hospital Complex of Vigo, 36200 Vigo, Spain
David Aramburu Núñez, Abhay Dave, Ramesh Paudyal, Joseph O Deasy, Amita Shukla-Dave, Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, United States
David Aramburu Núñez, Alfonso Calzado, Department of Radiology, Complutense University, 28040 Madrid, Spain
Moisés Mera Iglesias, Department of Medical Physics, Oncoserv, Santiago de los Caballeros 51000, Dominican Republic
Vaios Hatzoglou, Amita Shukla-Dave, Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, United States
Victor M Muñoz, Department of Radiation Oncology, Galaria - Meixoeiro, University Hospital Complex of Vigo, 36200 Vigo, Spain
Author contributions: Aramburu Núñez D, Lopez Medina A and Shukla-Dave A designed the study, performed MRI research, analyzed the data and wrote the paper; Dave A and Paudyal R analyzed the data and reviewed the paper; Mera Iglesias M and Salvador Gomez F performed MRI research and provided software support; Muñoz VM enrolled patients, and performed clinical assessment as per standard of care; Hatzoglou V performed the radiologic assessment; Calzado A and Deasy JO provided support.
Supported by The National Health Institute of Spain: ISCIII Grant PI11/02035 and DTS14/00188; BIOCAPS project (FP7/REGPOT-2012-2013.1), No. 316265; MSKCC internal IMRAS grant; and in part through the NIH/NCI Cancer Center, No. P30 CA008748.
Institutional review board statement: Six patients were enrolled in the Meixoeiro Hospital of Vigo Research Protocol entitled “Radioterapia adaptativa y predicción de la respuesta tumoral basadas en estudios funcionales de RM y PET/CT en cáncer de cabeza y cuello” (ISCIII Grant PI1102035).
Informed consent statement: All patients gave informed consent for their participation in the study approved by the hospital, which was conducted in accordance with the Declaration of Helsinki.
Conflict-of-interest statement: All authors have no conflicts of interest with regard to this manuscript.
Data sharing statement: Upon formal request and with proper motivation, all original data in anonymized format is available from the corresponding author for local inspection, but cannot leave Meixoeiro Hospital of Vigo and Memorial Sloan Kettering Cancer Center.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Amita Shukla-Dave, PhD, Director Quantitative Imaging, Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, United States. davea@mskcc.org
Telephone: +1-212-6393184 Fax: +1-212-7173010
Received: August 17, 2016
Peer-review started: August 18, 2016
First decision: October 21, 2016
Revised: October 29, 2016
Accepted: November 21, 2016
Article in press: November 23, 2016
Published online: January 28, 2017

Abstract
AIM

To noninvasively investigate tumor cellularity measured using diffusion-weighted magnetic resonance imaging (DW-MRI) and glucose metabolism measured by 18F-labeled fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) during radiation therapy (RT) for human papillomavirus negative (HPV-) head and neck squamous cell carcinoma (HNSCC).

METHODS

In this prospective study, 6 HPV- HNSCC patients underwent a total of 34 multimodality imaging examinations (DW-MRI at 1.5 T Philips MRI scanner [(n = 24) pre-, during- (2-3 wk), and post-treatment (Tx), and 18F-FDG PET/CT pre- and post-Tx (n = 10)]. All patients received RT. Monoexponential modeling of the DW-MRI data yielded the imaging metric apparent diffusion coefficient (ADC) and the mean of standardized uptake value (SUV) was measured from 18F-FDG PET uptake. All patients had a clinical follow-up as the standard of care and survival status was documented at 1 year.

RESULTS

There was a strong negative correlation between the mean of pretreatment ADC (ρ = -0.67, P = 0.01) and the pretreatment 18F-FDG PET SUV. The percentage (%) change in delta (∆) ADC for primary tumors and neck nodal metastases between pre- and Wk2-3 Tx were as follows: 75.4% and 61.6%, respectively, for the patient with no evidence of disease, 27.5% and 32.7%, respectively, for those patients who were alive with disease, and 26.9% and 7.31%, respectively, for those who were dead with disease.

CONCLUSION

These results are preliminary in nature and are indicative, and not definitive, trends rendered by the imaging metrics due to the small sample size of HPV- HNSCC patients in a Meixoeiro Hospital of Vigo Experience.

Key Words: Diffusion-weighted magnetic resonance imaging, Human papillomavirus negative head and neck squamous cell carcinoma, 18F-labeled fluorodeoxyglucose positron emission tomography/computed tomography

Core tip: In the modern era of adaptive radiotherapy, it is crucial to understand how different imaging techniques interact and complement each other for application in cancer care. The quantitative imaging metrics, apparent diffusion coefficient and standardized uptake value, play a significant role in understanding the efficacy of the radiotherapy treatment. Tumor cellularity and glucose metabolism were investigated before, during, and after radiotherapy in human papillomavirus negative head and neck squamous cell carcinoma patients using the diffusion-weighted magnetic resonance imaging and 18F-labeled fluorodeoxyglucose positron emission tomography/computed tomography imaging techniques.


  • Citation: Aramburu Núñez D, Lopez Medina A, Mera Iglesias M, Salvador Gomez F, Dave A, Hatzoglou V, Paudyal R, Calzado A, Deasy JO, Shukla-Dave A, Muñoz VM. Multimodality functional imaging using DW-MRI and 18F-FDG-PET/CT during radiation therapy for human papillomavirus negative head and neck squamous cell carcinoma: Meixoeiro Hospital of Vigo Experience. World J Radiol 2017; 9(1): 17-26
  • URL: https://www.wjgnet.com/1949-8470/full/v9/i1/17.htm
  • DOI: https://dx.doi.org/10.4329/wjr.v9.i1.17

INTRODUCTION

The Spanish Cancer Registries reported that in 2014, 241284 new cases of cancer were diagnosed in Spain[1]. Out of these, 12696 were head and neck (HN) cancers in which approximately 90% were specifically squamous cell carcinomas (SCC)[2]. The main subgroup for the patients was oropharyngeal SCC wherein 52%-72% of the cases were caused by infection from the human papillomavirus (HPV)[3]. It has been previously reported that HPV negative (-) HNSCC patients have poor outcomes compared with HPV-positive (HPV+) cancers[4]. Thus, in an effort to perform biologically guided adaptive radiotherapy, it is critical to understand how different functional imaging techniques interact and potentially complement each other[5]. Multimodality imaging, such as diffusion-weighted magnetic resonance imaging (DW-MRI) and 18F-labeled fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT), can provide useful anatomical and functional quantitative imaging metrics.

DW-MRI provides a noninvasive measurement for the degree of random motion of water in tissue; the rate of this diffusion is quantified by a quantitative imaging metric, the apparent diffusion coefficient (ADC)[6]. The advantage of DW-MRI over traditional anatomical MRI is that it can reflect the tissue cellularity and the integrity of cell membranes[7]. A recent metaanalysis reported that ADC has an inverse correlation with tissue cell density[8]. Kim et al[9] have shown that a significant increase in ADC was observed within 1 wk of treatment in HNSCC patients who were complete responders (P < 0.01). The Vandecaveye et al[10] study further established the utility of ADC in differentiating responding from non-responding HNSCC by providing a threshold (25% and 20% for primary tumors and lymph node metastases, respectively) for the percent relative (Δ) ADC change between pre-treatment (Tx) and 3 wk post-chemoradiotherapy (post-CRT).

Another quantitative imaging metric, standardized uptake value (SUV), obtained from 18F-FDG PET is a measure of glucose metabolism. An abnormally elevated SUV can be observed in most primary and metastatic cancers including HNSCC[11]. The 18F-FDG PET/CT has an established role in HNSCC management, including staging and monitoring CRT response[12,13]. The Schwartz et al[14] study showed that primary tumor SUV was a promising prognostic factor in HNSCC patients.

A better understanding of the association between 18F-FDG PET/CT and DW-MRI derived quantitative imaging metrics is needed in order for them to become the building blocks for a biologically-guided adaptive radiotherapy. Recently there have been few reports showing correlations between these multimodality imaging techniques and their initial role in the prognosis of HNSCC patients[15]. However, there are limited studies initiated to explore the use of these techniques together in a treatment planning setting for radiation oncology[16]. Our study is the first experience in Spain with multimodality imaging in HPV- HNSCC patients for its use in biologically-guided adaptive radiotherapy. The purpose of the current study is to noninvasively investigate tumor cellularity measured using DW-MRI and glucose metabolism measured by 18F-FDG-PET/CT during RT for HPV- HNSCC.

MATERIALS AND METHODS
Patients

This prospective study was conducted in accordance with the Declaration of Helsinki[17]. The study protocol was approved by the local ethics committee; informed consent was obtained from all patients. All patients eligible for this study had biopsy-proven newly diagnosed squamous cell carcinoma of the head and neck. Diagnostic biopsies were also performed to evaluate HPV status. Six HPV- HNSCC patients underwent a total of 34 multimodality imaging examinations [DW-MRI at 1.5 T Philips MRI scanner (n = 24) pre-, during (2-3 wk) and post-Tx, and 18F-FDG PET/CT pre- and post-Tx (n = 10)] (Figure 1). All the patients were treated with intensity-modulated radiation therapy (IMRT), and the prescribed doses varied between 66 Gy and 70 Gy to the local planning target volume (PTV). Patient characteristics are given in Table 1.

Table 1 Characteristics of the patients involved in this study.
CharacteristicsValue
Demographics
Mean age (yr)65
Age range (yr)52-79
Male/female5/1
Location of primary tumor
Oropharynx6
Metastatic loco-regional nodes11
Radiation therapy techniqueIMRT
Dose (Gy)66-70
Fractions32
Outcome
Alive with disease3
Dead of disease2
No evidence of disease1
Figure 1
Figure 1 Workflow representing the study design performed in all the patients. 18F-FDG: Fluorine-18 Fludeoxyglucose; PET/CT: Positron emission tomography/computed tomography; DW-MRI: Diffusion-weighted magnetic resonance imaging.

All the patients had a clinical follow-up as the standard of care and survival status was documented into groups at 1 year. The four groups for patients were as follows: No evidence of disease (NED), alive with disease (AWD), dead of disease (DOD), and dead of other causes (DOC). Additionally, local-regional and distant metastases statuses were noted for all patients[18].

DWI-MRI

All MRI examinations were performed on a 1.5-Tesla Achieva scanner (Philips Healthcare, The Netherlands) with a Philips Sense Flex coil over the neck. For MRI, all patients were in the supine position with an immobilization system that was also used during the radiotherapy treatment delivery. A thermoplastic mask, head support, and flat table were used to minimize distortion and improve the registration process between the different imaging modalities. The head support and flat table were adapted to the MRI/safety requirements. The MRI protocol consisted of the standard anatomic MRI scans (T1-/T2-weighted images) and DW-MRI.

DW-MRI acquisition was performed using single-shot echo planar imaging (SS-EPI) with three b values (b = 0, 600 and 1000 s/mm2). Other parameters included repetition time (TR) = 5000 ms, echo time (TE) = 77-100 ms, number of excitations (NEX) = 2, field of view (FOV): 24 cm, and slice thickness = 6 mm. The total acquisition time for obtaining the DW-MRI data was approximately 5 min. The acquisition matrix of 120 × 97 was zero filled to 256 × 256 during image reconstruction.

18F-FDG PET/CT

A whole-body PET/CT scan was performed from head to thigh, 60 min after intravenous administration of approximately 370 MBq (± 10%) of 18F-FDG on a PET/CT Discovery scanner (GE Healthcare Bio-Sciences Corp.). The patient was placed in the supine position, with the same immobilization system as in the radiotherapy treatment delivery. Other parameters included a 70 cm axial FOV, a 218 × 218 matrix. Data was acquired in a 3-D mode. The pixel spacing was 5.47 mm with a slice thickness of 3.27 mm. The spatial resolution varied from 3.99 mm to 4.56 mm. PET images were corrected using the specific software of the equipment for attenuation, scatter, decay, dead time, random coincidences, and slice sensitivity.

Image analysis

All images were registered and analyzed using in-house software (Artfibio-tool)[19]. The registration for DW-MRI and 18F-FDG PET/CT datasets was a two-step process: (1) Manual registration: performing a manual alignment (translation and/or rotation) of the images (DWMRI, CT-Scan, PET-CT) interactively on-screen; and (2) Automatic Rigid Registration: Once the images were approximately aligned, a more precise alignment (full rigid transformation) was performed based on an iterative process evaluated by statistical metrics (Viola and Wells mutual information[20]). Using Artfibio-tool, the signal intensity values were extracted from the whole tumor volumes[19].

DW-MRI: According to Stejskal and Tanner’s[21] and considering the monoexponential approximation (7), the ADC value was calculated using equation 1:

ADC = [loge(s0/s1)]/(b1-b0). (1)

Where S1 and S0 are signal values of the images at b values, b1 and b0, respectively, and ADC is the apparent diffusion coefficient.

Regions of Interest (ROIs) were delineated on the primary tumor and neck nodal metastases by an experienced neuroradiologist on the DW-MRI image (b  =  0 s/mm2). Before contouring the ROIs, the T1-T2-weighted images were used to determine localization and tumor extent.

Finally, a relative percentage (%) change in derived imaging metric (ADC) between pre- and ith intra-Tx week (Wk) was calculated as follows:

ΔADC (%) = [(ADCi-ADC0)/ADC0] × 100. (2)

Where ith represents intra-TX week for ADC metric value and ADC0 represents the pre-Tx metric value.

18F-FDG PET/CT: An experienced radiation oncologist matched the ROIs from the MR images with those of the PET/CT images and analyzed them qualitatively and quantitatively using the attenuation-corrected PET emission images. The ROIs were placed over the areas of focal 18F-FDG uptake in both the primary tumor and neck nodal metastases. The intensity of the 18F-FDG uptake in the ROIs was measured using the SUV normalized by the dilution volume[22]. The imaging data available in units of mCi per mL (mCi/mL) per voxel were decay-corrected to the time of injection and converted to SUV units.

Statistical analysis

In the present study, data was analyzed from a total of 34 multimodality imaging studies [DW-MRI (n = 24) pre-, during- (2-3 wk) and post-Tx and 18F-FDG PET/CT pre- and post-Tx (n = 10)] to capture treatment response. Values were presented as mean ± SD. The mean value comparison was carried out using the Wilcoxon test. A Spearman correlation analysis was performed between SUV and ADC metric values, which we used to report the correlation and P-values. These correlations were reported using the standard guidelines[23] in which an absolute correlation of < 0.3 was considered weak, 0.3-0.5 was considered moderate and 0.5-1.0 was considered strong. The significance level was set at P≤ 0.05. All data analysis was performed using the R software/environment, an open source project that is distributed under the GNU General Public License[24].

RESULTS

All 6 patients were untreated at the first time point of multimodality imaging, had biopsy-proven SCC, and were HPV-. Among the 6 patients, a total of 11 neck nodal metastases and 5 primary tumors were analyzed (3 patients had more than one node and 1 patient had an unknown primary tumor site). Patients were grouped as follows based on clinical outcome: NED = 1, AWD = 3, and DOD = 2 (Table 1). A total of 34 multimodality imaging studies [DW-MRI (n = 24) and 18F-FDG PET/CT (n = 10)] were analyzed to capture RT response. The results showed a significantly strong negative correlation (ρ = -0.67, P = 0.01) between the pre-Tx mean SUV and the pre-Tx mean ADC for the 11 lymph nodes and 5 primary tumors (Figure 2).

Figure 2
Figure 2 Relationship between pre-Tx mean standardized uptake value and pre-Tx mean apparent diffusion coefficient showing a significant strong negative inverse correlation. SUV: Standardized uptake value; ADC: Apparent diffusion coefficient.

A summary of the ADC mean for pre-Tx and during-Tx (2nd and 3rd weeks data were combined) from the three different survival groups as DOD, AWD and NED is shown in Table 2. For a single patient who was NED at the last clinical follow-up, the MRI and the 18F-FDG PET/CT post-treatment showed no evidence of disease at the primary tumor site and neck nodal metastases. Figure 3 shows the DW-MRI and 18F-FDG PET/CT images from a patient who was NED. The ADC values (mean ± SD) for the ROI drawn on the primary tumor were 0.85 ± 0.27 × 10-3 mm2/s, 1.49 ± 0.13 × 10-3 mm2/s for pre-Tx and Wk2-3 Tx, respectively. The ADC values for the ROIs in neck nodal metastases were as follows 0.86 ± 0.20 × 10-3 mm2/s, 1.39 ± 0.08 × 10-3 mm2/s for pre-Tx and Wk2-3 Tx (Table 2). Pre-Tx SUV (mean ± SD) values for primary tumor and neck nodal metastases were 5.99 ± 0.61 and 6.06 ± 0.49, respectively.

Table 2 Apparent diffusion coefficient metric values for human papillomavirus negative head and neck squamous cell carcinoma patients who were classified based on survival as dead of disease, alive with disease and no evidence of disease before, during and post- radiotherapy.
MRIDOD ADC mean (× 10-3 mm2/s)
AWD ADC mean (× 10-3 mm2/s)
NED ADC mean (× 10-3 mm2/s)
PrimaryNodePrimaryNodePrimaryNode
Pre-Tx1.51 ± 0.361.43 ± 0.581.66 ± 0.411.26 ± 0.190.85 ± 0.270.86 ± 0.20
During Tx (2-3 wk)1.92 ± 0.331.54 ± 0.112.12 ± 0.381.41 ± 0.381.49 ± 0.131.39 ± 0.08
Post-TxNo primary0.98 ± 0.29No primary1.93 ± 0.22No primaryNo node
Figure 3
Figure 3 Representative no evidence of disease patient. A and G: Pre-Tx PET/CT of the primary tumor and a neck nodal metastasis; B and H: Primary tumor and representative neck nodal metastasis contoured over a T2-W MRI; C and I: Pre-Tx ADC map overlaid on T2-W MRI; D and J: Wk2-Tx ADC map overlaid on T2-W; E and K: Wk3-Tx ADC map overlaid on T2-W; F and L: T2-W MRI post-Tx with no evidence of primary tumor and neck nodal metastases. PET/CT: Positron emission tomography/computed tomography; MRI: Magnetic resonance imaging; ADC: Apparent diffusion coefficient; IMRT: Intensity modulated radiation therapy.

Three patients were AWD on the last clinical follow-up, and 1 patient had an unknown primary tumor site. Both, MRI and 18F-FDG PET/CT post-treatment showed no evidence of disease at the primary tumor site; however the neck nodal metastases were still present. Figure 4 shows the DW-MRI and 18F-FDG PET/CT images from a patient who was AWD. The ADC values (mean ± SD) for the primary tumors were 1.66 ± 0.41 × 10-3 mm2/s, 2.12 ± 0.38 × 10-3 mm2/s for pre-Tx and Wk2-3 Tx, respectively. The ADC values for the neck nodal metastases were 1.26 ± 0.19 × 10-3 mm2/s, 1.41 ± 0.38 × 10-3 mm2/s, and 1.93 ± 0.22 × 10-3 mm2/s for pre-Tx, Wk2-3 Tx and post-Tx, respectively (Table 2). The SUV mean pre-Tx values for the primary tumor and neck nodal metastases were 1.84 ± 0.83 and 4.85 ± 0.75, respectively.

Figure 4
Figure 4 Representative alive with disease patient. A and G: pre-Tx PET/CT of the primary tumor and two neck nodal metastases; B and H: Primary tumor and representative neck nodal metastasis contoured over a T2-W MRI; C and I: Pre-Tx ADC map overlaid on T2-W MRI; D and J: Wk2-Tx ADC map overlaid on T2-W; E and K: Wk3-Tx ADC map overlaid on T2-W; F and L: T2-W MRI post-Tx with no evidence of primary tumor but with presence of neck nodal metastasis. PET/CT: Positron emission tomography/computed tomography; MRI: Magnetic resonance imaging; ADC: Apparent diffusion coefficient; IMRT: Intensity modulated radiation therapy.

The two patients who were DOD died 2 mo and 6 mo post-Tx. Figure 5 shows the DW-MRI and 18F-FDG PET/CT images from a patient who was DOD. The ADC values (mean ± SD) for the primary tumor were 1.51 ± 0.36 × 10-3 mm2/s and 1.92 ± 0.33 × 10-3 mm2/s for pre-Tx and Wk2-3 Tx, respectively. The ADC values for the neck nodal metastases were 1.43 ± 0.58 × 10-3 mm2/s, 1.54 ± 0.11 × 10-3 mm2/s, and 0.98 ± 0.29 × 10-3 mm2/s for pre-Tx, Wk2-3 Tx and post-Tx, respectively (Table 2). The SUV mean pre-Tx values for the primary tumor and neck nodal metastases were 2.98 ± 0.66 and 3.93 ± 0.45, respectively.

Figure 5
Figure 5 Representative dead of disease patient. A and G: Pre-Tx PET/CT of the primary tumor and three neck nodal metastases; B and H: Primary tumor and representative neck nodal metastasis contoured over a T2-W MRI; C and I: Pre-Tx ADC map overlaid on T2-W MRI; D and J: Wk2-Tx ADC map overlaid on T2-W; E and K: Wk3-Tx ADC map overlaid on T2-W; F and L: T2-W MRI post-Tx with no evidence of primary tumor but with presence of neck nodal metastasis. PET/CT: Positron emission tomography/computed tomography; MRI: Magnetic resonance imaging; ADC: Apparent diffusion coefficient; IMRT: Intensity modulated radiation therapy.

The ΔADC (%) between pre- and Wk2-3 Tx for primary tumors and neck nodal metastases were as follows: 75.4% and 61.6%, respectively, for the patient with NED, 27.5% and 32.7%, respectively, for those patients who were AWD, and 26.9% and 7.31%, respectively, for those who were DOD.

DISCUSSION

This prospective study is the first in Spain conducted in support of integrating functional imaging in a RT setting. We evaluated multimodality imaging in HPV- HNSCC patients for both primary and neck nodal metastases. Specifically, we observed that pretreatment tumor cellularity is inversely proportional to glucose metabolism in these tumors, which was consistent with the previous literature[15,25,26]. The survival status and functional metrics show different % change in ΔADC for the NED, AWD, and DOD survival groups, which would need to be validated in larger patient population studies.

HNSCC is one of the major types of cancer that can be linked to alcohol consumption and tobacco smoking. It typically originates from the mucosal epithelia of the oral cavity, pharynx and larynx[27]. In oropharyngeal SCC, HPV status is an independent prognostic factor for both overall survival and progression-free survival, which is consistent with the hypothesis that HPV+ and HPV- tumors are distinct and have different causes, risk-factor profiles, and survival outcomes[28]. HPV- tumors continue to have poor outcomes compared to their HPV+ counterparts[28]. Future clinical trials should be designed specifically for patients with HPV+ or HPV- HNSCC using appropriate, validated quantitative imaging biomarkers. As there is very scarce imaging literature on HPV+ or HPV- alone, it raises an urgent need to study these cohorts independently and assess the value of multimodality imaging for better cancer patient management.

In recent years, studies by Razek have shown that ADC metric has a prognostic value in HNSCC[29-31]. They reported a mean ADC value in nasopharyngeal carcinoma (NPC) of 0.99 ± 0.11 × 10-3 mm2/s. The ADC value in this study also correlated inversely with tumor volume[29]. In a separate study by the same group, it was reported that the mean ADC value of residual or recurrent lesions (1.17 ± 0.33 × 10-3 mm2/s) was less than that observed in post-therapeutic changes (2.07 ± 0.25 × 10-3 mm2/s)[30]. They also showed that ADC values with metabolic ratio (Ch/Cr) obtained from 1H-MRS are well correlated with several prognostic parameters of HNSCC[31].

The use of multimodality imaging (18F-FDG PET/CT, DW-MRI, DCE-MRI) in general HNSCC populations for assessing both the association between the quantitative imaging biomarkers obtained from each imaging technique and their combined or respective roles in prognosis and/or prediction of outcome[8,25,32,33]. The major technical challenges in IMRT persist in the use of functional images for treatment, one of which includes the identification of a reproducible, RT-compatible patient positioning setup that is consistent between functional techniques and RT. All patients in the present study were in a supine position and fixed in place with the same immobilization system that was used during the RT treatment planning and delivery. A thermoplastic mask, head support, and flat table were used to try to minimize distortion and to improve the registration process between the different imaging modalities. The head support and flat table were adapted to MRI and PET/CT. This reproducible positioning addressed one of the big hurdles in the acquisition of multimodality images that may be used for adaptive RT in the future[34,35]. Dirix et al[36] designed a feasibility, prospective, multimodality imaging study with this prerequisite in mind, recruiting HNSCC patients for dose painting in RT. A pilot study by Subesinghe et al[37] emphasized the importance of reproducing the positioning for assessing early RT treatment response.

18F-FDG PET/CT and DW-MRI have been the focus of numerous studies in general HNSCC cohorts to determine correlation, if any, between SUV and ADC values, with variable results. SUV and ADC remain exploratory imaging metrics yet to be fully explored and understood in HPV-HNSCC patients. A study by Varoquax et al[38] involving 24 primary and 10 recurrent HNSCC showed no significant correlation between SUV values (SUVmax, SUVmean or SUVmin) and ADC values (ADCmax, ADCmean or ADCmin), nor did Choi et al[39] find significant correlation between SUVmean and ADCmean in 47 primary HNSCC. Rather, Nakajo et al[15] found significant negative correlation between SUVmax and ADCmean in a study of 28 primary HNSCC tumors and Nakamatsu et al[26] demonstrated significant negative correlation in 41 neck nodal metastases between SUV values (SUVmax, SUVmean) and ADC values (ADCmean, ADCmin). In our study, similar results were obtained from a total of 11 neck nodal metastases and 5 primary HPV- HNSCC showing a significant strong negative correlation between the ADCmean and SUVmean pre-Tx (ρ = -0.67, P = 0.01). Further validation of the correlations with larger patient populations is needed, but was beyond the scope of this study. Preda et al[40] concluded in a study with 57 HNSCC primary tumors that “the combination of SUVmax and ADCmin improves the prognostic role of the two separate parameters”.

The present study showed an increase in ΔADC Wk2-3 for the HPV- patient with NED in comparison with the DOD and AWD HPV- patients in both primary tumor and neck nodal metastases, in agreement with above-mentioned studies. Also, the pre-Tx ADC values of the primary tumor and neck nodal metastases for NED is lower than in the group of AWD and DOD, showing that lower pre-Tx ADC values are related to a good response to treatment and are consistent with the previous literature[9,41].

The % change in ΔADC for primary tumor and neck nodal metastases depict the different Tx responses, suggesting the possibility of identifying HPV- patients with poor prognosis at an early stage to individualize and adapt RT treatment (i.e., through dose-escalation). Vandecaveye et al[42] showed in neck nodal metastases and primary tumors that ΔADC (Week 2 and Week 4 during CRT) was significantly lower (P < 0.0001) in lesions with recurrence than in lesions with a complete response.

Individualization of treatment is especially important in the subgroup of HPV- patients who were part of this study. A limitation of the study was that there were a relatively small number of HPV- patients as the recruitment was highly selective in Spain. However, we felt that this selectivity was justified given that these subtypes of HPV- patients are the ones who have poor prognoses in HNSCC[28]. The initial results need to be addressed through validation in future studies.

Our study offers insight on how to manage and understand valuable quantitative imaging biomarkers, such as SUV and ADC for HPV- HNSCC, with the objective of integrating them into the development of biological adaptive RT in the future.

These results are preliminary in nature and are indicative, and not definitive, trends rendered by the imaging metrics due to the small sample size of HPV- HNSCC patients in a Meixoeiro Hospital of Vigo Experience.

ACKNOWLEDGMENTS

The authors offer their sincerest thanks to patients who volunteered to participate in this study. Our sincerest thanks to Mr. James Keller, Editor, Department of Medical Physics, Memorial Sloan Kettering Cancer Center for his help in editing this paper. We must be grateful for the exchange program AAPM-SEFM for facilitating the first author’s visit to Memorial Sloan Kettering Cancer Center. We thank the National Health Institute of Spain for supporting this work through the ISCIII Grant PI11/02035, DTS14/00018, BIOCAPS, and the Galician Government through the project CN 2012/260 “Consolidation Research Units: AtlantTIC”. This research was also funded in part through the NIH/NCI Cancer Center Support Grant P30 CA008748.

COMMENTS
Background

Human papillomavirus (HPV) negative (-) head and neck squamous cell carcinoma (HNSCC) patients have poor outcomes compared with HPV-positive (HPV+) cancers. Individualization of radiotherapy is especially important in the subgroup of HPV- patients and imaging metrics derived from multimodality imaging can be critical for its implementation.

Research frontiers

In an effort to perform biologically guided adaptive radiotherapy, it is critical to understand how different functional imaging techniques interact and potentially complement each other.

Innovations and breakthroughs

Multimodality imaging in HPV- HNSCC suggests that tumor cell density is inversely proportional to glucose metabolism in a Meixoeiro Hospital of Vigo Experience. These results are promising and need to be validated in larger populations.

Applications

Diffusion-weighted magnetic resonance imaging and 18F-labeled fluorodeoxyglucose positron emission tomography/computed tomography are two valuable imaging techniques that may help build the framework for adaptive radiotherapy based on functional images in future clinical trials by investigating tumor cellularity and glucose metabolism before, during and after RT in HPV- HNSCC.

Terminology

18F-FDG: Fluorine-18 fludeoxyglucose; ADC: Apparent diffusion coefficient; AWD: Alive with disease; DOC: Dead of other causes; DOD: Dead of disease; DW-MRI: Diffusion-weighted magnetic resonance imaging; HNC: Head and neck cancer; HNSCC: Head and neck squamous cell carcinoma; HPV-: Human papillomavirus negative; HPV+: Human papillomavirus positive; IMRT: Intensity modulated radiation therapy; MRI: Magnetic resonance imaging; NED: No evidence of disease; PET/CT: Positron emission tomography/computed tomography; ROI: Region of interest; RT: Radiotherapy.

Peer-review

This is a good paper.

Footnotes

Manuscript source: Invited manuscript

Specialty type: Radiology, nuclear medicine and medical imaging

Country of origin: United States

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Grade C (Good): 0

Grade D (Fair): 0

Grade E (Poor): 0

P- Reviewer: Razek AAKA, Xiao NH S- Editor: Ji FF L- Editor: A E- Editor: Lu YJ

References
1.  Galceran  Europa: Estimaciones de la incidencia y la supervivencia del cáncer en Espa-a y su situación en Europa, 2014.  [PubMed]  [DOI]
2.  Sanderson RJ, Ironside JA. Squamous cell carcinomas of the head and neck. BMJ. 2002;325:822-827.  [PubMed]  [DOI]
3.  Seijas-Tamayo R, Fernández-Mateos J, Adansa Klain JC, Mesía R, Pastor Borgoñón M, Pérez-Ruiz E, Vázquez Fernández S, Salvador Coloma C, Rueda Domínguez A, Taberna M. Epidemiological characteristics of a Spanish cohort of patients diagnosed with squamous cell carcinoma of head and neck: distribution of risk factors by tumor location. Clin Transl Oncol. 2016;18:1114-1122.  [PubMed]  [DOI]
4.  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;100:261-269.  [PubMed]  [DOI]
5.  Jansen JF, Schöder H, Lee NY, Stambuk HE, Wang Y, Fury MG, Patel SG, Pfister DG, Shah JP, Koutcher JA. 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;82:299-307.  [PubMed]  [DOI]
6.  Padhani AR, Liu G, Koh DM, Chenevert TL, Thoeny HC, Takahara T, Dzik-Jurasz A, Ross BD, Van Cauteren M, Collins D. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia. 2009;11:102-125.  [PubMed]  [DOI]
7.  Chenevert TL, Stegman LD, Taylor JM, Robertson PL, Greenberg HS, Rehemtulla A, Ross BD. Diffusion magnetic resonance imaging: an early surrogate marker of therapeutic efficacy in brain tumors. J Natl Cancer Inst. 2000;92:2029-2036.  [PubMed]  [DOI]
8.  Ng SH, Liao CT, Lin CY, Chan SC, Lin YC, Yen TC, Chang JT, Ko SF, Fan KH, Wang HM. Dynamic contrast-enhanced MRI, diffusion-weighted MRI and (18)F-FDG PET/CT for the prediction of survival in oropharyngeal or hypopharyngeal squamous cell carcinoma treated with chemoradiation. Eur Radiol. 2016;26:4162-4172.  [PubMed]  [DOI]
9.  Kim S, Loevner L, Quon H, Sherman E, Weinstein G, Kilger A, Poptani H. Diffusion-weighted magnetic resonance imaging for predicting and detecting early response to chemoradiation therapy of squamous cell carcinomas of the head and neck. Clin Cancer Res. 2009;15:986-994.  [PubMed]  [DOI]
10.  Vandecaveye V, Dirix P, De Keyzer F, Op de Beeck K, Vander Poorten V, Hauben E, Lambrecht M, Nuyts S, Hermans R. Diffusion-weighted magnetic resonance imaging early after chemoradiotherapy to monitor treatment response in head-and-neck squamous cell carcinoma. Int J Radiat Oncol Biol Phys. 2012;82:1098-1107.  [PubMed]  [DOI]
11.  Schöder H, Fury M, Lee N, Kraus D. PET monitoring of therapy response in head and neck squamous cell carcinoma. J Nucl Med. 2009;50 Suppl 1:74S-88S.  [PubMed]  [DOI]
12.  Ong SC, Schöder H, Lee NY, Patel SG, Carlson D, Fury M, Pfister DG, Shah JP, Larson SM, Kraus DH. Clinical utility of 18F-FDG PET/CT in assessing the neck after concurrent chemoradiotherapy for Locoregional advanced head and neck cancer. J Nucl Med. 2008;49:532-540.  [PubMed]  [DOI]
13.  Wong RJ, Lin DT, Schöder H, Patel SG, Gonen M, Wolden S, Pfister DG, Shah JP, Larson SM, Kraus DH. Diagnostic and prognostic value of [(18)F]fluorodeoxyglucose positron emission tomography for recurrent head and neck squamous cell carcinoma. J Clin Oncol. 2002;20:4199-4208.  [PubMed]  [DOI]
14.  Schwartz DL, Rajendran J, Yueh B, Coltrera MD, Leblanc M, Eary J, Krohn K. FDG-PET prediction of head and neck squamous cell cancer outcomes. Arch Otolaryngol Head Neck Surg. 2004;130:1361-1367.  [PubMed]  [DOI]
15.  Nakajo M, Nakajo M, Kajiya Y, Tani A, Kamiyama T, Yonekura R, Fukukura Y, Matsuzaki T, Nishimoto K, Nomoto M. FDG PET/CT and diffusion-weighted imaging of head and neck squamous cell carcinoma: comparison of prognostic significance between primary tumor standardized uptake value and apparent diffusion coefficient. Clin Nucl Med. 2012;37:475-480.  [PubMed]  [DOI]
16.  Min M, Lee MT, Lin P, Holloway L, Wijesekera Dj, Gooneratne D, Rai R, Xuan W, Fowler A, Forstner D, Liney G. Assessment of serial multi-parametric functional MRI (diffusion-weighted imaging and R2*) with (18)F-FDG-PET in patients with head and neck cancer treated with radiation therapy. Br J Radiol. 2016;89:20150530.  [PubMed]  [DOI]
17.  Goodyear MD, Krleza-Jeric K, Lemmens T. The Declaration of Helsinki. BMJ. 2007;335:624-625.  [PubMed]  [DOI]
18.  Bockmühl U, Ishwad CS, Ferrell RE, Gollin SM. Association of 8p23 deletions with poor survival in head and neck cancer. Otolaryngol Head Neck Surg. 2001;124:451-455.  [PubMed]  [DOI]
19.  Landesa-Vazquez I, Alba-Castro JL, Mera-Iglesias M, Aramburu-Nunez D, Lopez-Medina A, Munoz-Garzon V. ARTFIBio: A Cross-Platform Image Registration Tool for Tumor Response Quantification in Head and Neck Cancer. Ieee-Embs International Conference on Biomedical and Health Informatics (Bhi). 2014;149-152.  [PubMed]  [DOI]
20.  Mattes D, Haynor DR, Vesselle H, Lewellen TK, Eubank W. Nonrigid multimodality image registration. P Soc Photo-Opt Ins. 2001;2:1609-1620.  [PubMed]  [DOI]
21.  Stejskal EO, Tanner JE. Spin Diffusion Measurements: Spin Echoes in the Presence of a Time-Dependent Field Gradient. J Chem Phys. 1965;42:288-292.  [PubMed]  [DOI]
22.  IAEA. Quantitative Nuclear Medicine Imaging: Concepts, Requirements and Methods. Austria: IAEA Library 2014; .  [PubMed]  [DOI]
23.  Cohen J. The statistical power of abnormal-social psychological research: a review. J Abnorm Soc Psychol. 1962;65:145-153.  [PubMed]  [DOI]
24.  R Project. GNU Operating System.  Available from: http://www.gnu.org/licenses/gpl.html.  [PubMed]  [DOI]
25.  Gawlitza M, Purz S, Kubiessa K, Boehm A, Barthel H, Kluge R, Kahn T, Sabri O, Stumpp P. In Vivo Correlation of Glucose Metabolism, Cell Density and Microcirculatory Parameters in Patients with Head and Neck Cancer: Initial Results Using Simultaneous PET/MRI. PLoS One. 2015;10:e0134749.  [PubMed]  [DOI]
26.  Nakamatsu S, Matsusue E, Miyoshi H, Kakite S, Kaminou T, Ogawa T. Correlation of apparent diffusion coefficients measured by diffusion-weighted MR imaging and standardized uptake values from FDG PET/CT in metastatic neck lymph nodes of head and neck squamous cell carcinomas. Clin Imaging. 2012;36:90-97.  [PubMed]  [DOI]
27.  Jemal A, Siegel R, Xu J, Ward E. Cancer statistics, 2010. CA Cancer J Clin. 2010;60:277-300.  [PubMed]  [DOI]
28.  Ang KK, Harris J, Wheeler R, Weber R, Rosenthal DI, Nguyen-Tân PF, Westra WH, Chung CH, Jordan RC, Lu C. Human papillomavirus and survival of patients with oropharyngeal cancer. N Engl J Med. 2010;363:24-35.  [PubMed]  [DOI]
29.  Abdel Razek AA, Kamal E. Nasopharyngeal carcinoma: correlation of apparent diffusion coefficient value with prognostic parameters. La Radiologia medica. 2013;118:534-539.  [PubMed]  [DOI]
30.  Abdel Razek AA, Kandeel AY, Soliman N, El-shenshawy HM, Kamel Y, Nada N, Denewar A. Role of diffusion-weighted echo-planar MR imaging in differentiation of residual or recurrent head and neck tumors and posttreatment changes. AJNR American journal of neuroradiology. 2007;28:1146-1152.  [PubMed]  [DOI]
31.  Razek AA, Nada N. Correlation of Choline/Creatine and Apparent Diffusion Coefficient values with the prognostic parameters of Head and Neck Squamous Cell Carcinoma. NMR in biomedicine. 2016;29:483-489.  [PubMed]  [DOI]
32.  Han M, Kim SY, Lee SJ, Choi JW. The Correlations Between MRI Perfusion, Diffusion Parameters, and 18F-FDG PET Metabolic Parameters in Primary Head-and-Neck Cancer: A Cross-Sectional Analysis in Single Institute. Medicine (Baltimore). 2015;94:e2141.  [PubMed]  [DOI]
33.  Shukla-Dave A, Lee NY, Jansen JF, Thaler HT, Stambuk HE, Fury MG, Patel SG, Moreira AL, Sherman E, Karimi S. Dynamic contrast-enhanced magnetic resonance imaging as a predictor of outcome in head-and-neck squamous cell carcinoma patients with nodal metastases. Int J Radiat Oncol Biol Phys. 2012;82:1837-1844.  [PubMed]  [DOI]
34.  van der Heide UA, Houweling AC, Groenendaal G, Beets-Tan RG, Lambin P. Functional MRI for radiotherapy dose painting. Magn Reson Imaging. 2012;30:1216-1223.  [PubMed]  [DOI]
35.  Thorwarth D, Beyer T, Boellaard R, de Ruysscher D, Grgic A, Lee JA, Pietrzyk U, Sattler B, Schaefer A, van Elmpt W. Integration of FDG-PET/CT into external beam radiation therapy planning: technical aspects and recommendations on methodological approaches. Nuklearmedizin. 2012;51:140-153.  [PubMed]  [DOI]
36.  Dirix P, Vandecaveye V, De Keyzer F, Stroobants S, Hermans R, Nuyts S. Dose painting in radiotherapy for head and neck squamous cell carcinoma: value of repeated functional imaging with (18)F-FDG PET, (18)F-fluoromisonidazole PET, diffusion-weighted MRI, and dynamic contrast-enhanced MRI. J Nucl Med. 2009;50:1020-1027.  [PubMed]  [DOI]
37.  Subesinghe M, Scarsbrook AF, Sourbron S, Wilson DJ, McDermott G, Speight R, Roberts N, Carey B, Forrester R, Gopal SV. Alterations in anatomic and functional imaging parameters with repeated FDG PET-CT and MRI during radiotherapy for head and neck cancer: a pilot study. BMC Cancer. 2015;15:137.  [PubMed]  [DOI]
38.  Varoquaux A, Rager O, Lovblad KO, Masterson K, Dulguerov P, Ratib O, Becker CD, Becker M. Functional imaging of head and neck squamous cell carcinoma with diffusion-weighted MRI and FDG PET/CT: quantitative analysis of ADC and SUV. Eur J Nucl Med Mol Imaging. 2013;40:842-852.  [PubMed]  [DOI]
39.  Choi SH, Paeng JC, Sohn CH, Pagsisihan JR, Kim YJ, Kim KG, Jang JY, Yun TJ, Kim JH, Han MH. Correlation of 18F-FDG uptake with apparent diffusion coefficient ratio measured on standard and high b value diffusion MRI in head and neck cancer. J Nucl Med. 2011;52:1056-1062.  [PubMed]  [DOI]
40.  Preda L, Conte G, Bonello L, Giannitto C, Travaini LL, Raimondi S, Summers PE, Mohssen A, Alterio D, Cossu Rocca M. Combining standardized uptake value of FDG-PET and apparent diffusion coefficient of DW-MRI improves risk stratification in head and neck squamous cell carcinoma. Eur Radiol. 2016;.  [PubMed]  [DOI]
41.  Hatakenaka M, Nakamura K, Yabuuchi H, Shioyama Y, Matsuo Y, Kamitani T, Yonezawa M, Yoshiura T, Nakashima T, Mori M. Apparent diffusion coefficient is a prognostic factor of head and neck squamous cell carcinoma treated with radiotherapy. Jpn J Radiol. 2014;32:80-89.  [PubMed]  [DOI]
42.  Vandecaveye V, Dirix P, De Keyzer F, de Beeck KO, Vander Poorten V, Roebben I, Nuyts S, Hermans R. Predictive value of diffusion-weighted magnetic resonance imaging during chemoradiotherapy for head and neck squamous cell carcinoma. Eur Radiol. 2010;20:1703-1714.  [PubMed]  [DOI]