Browsing by Subject "Head and neck cancer"

Oropharyngeal Squamous Cell Carcinoma (OPSCC) is by far the most predominant form of head and neck cancer in the United States. The survival rate for OPSCC is very high, which, while fortunate, yields many patients who are left with the late term toxicities consequent of their treatment. This project aimed to use patient-reported outcome (PRO) data from two sources – the PRO-CTCAE and the QLQ-C30 – along with the dosimetric data of patients that have already been treated, in order to characterize retrospectively a relationship between patient dosimetric data and the severity of response of PRO data. In particular, PRO data was used as a way to characterize the severity of patient-experienced xerostomia and dysphagia. Additionally, this data was used to fit the radiobiological parameters for two normal tissue complication probability (NTCP) models: the Lyman-Kutcher-Burman (LKB) model, and the Relative Seriality (RS) model. Overall, it was found that the PRO-CTCAE data was more robust than the QLQ-C30 data in its characterization. Based on the PRO-CTCAE data, the V52 (volume which receives at least 52 Gy) of the combined constrictors and the V59 of the superior pharyngeal constrictor show the strongest relationship with patient-reported dysphagia. Additionally, the V27 of the contralaterals and the V12 of the contralateral parotid show the strongest relationship with patient-reported xerostomia. Furthermore, it was found that the dose response curves for both NTCP models fit the data with similar accuracy.

Mice are the predominant animal model used in radiation therapy research for investigating radiobiological kinetics and evaluating new therapeutics to achieve a higher therapeutic ratio in the clinic. A novel carcinogen-induced and genetically engineered head and neck squamous cell carcinoma mouse model was developed at Duke to study head and neck cancer, one of the most widely spread cancers in the world. However, platforms that are able to perform precise and reproducible radiation therapy on these mice to mimic human radiation therapy are lacking. To address this issue, a platform based on the X-RAD 225Cx orthovoltage irradiator was developed. 3D printing technique was used to generate imaging phantoms, immobilization devices, and blocks. A simulation was conducted to optimize imaging protocol. Results were verified on the measurement on both the 3D-printed phantom and the actual mouse. Prior to irradiation, mice were placed on the immobilization device in a supine position, and the isocenter was determined by the position of the device since the irradiator does not have a laser localizer system. The performance of the immobilization was obtained by scanning several mice separately at various time points, ranging from several hours post-imaging to two months post-imaging. In order to make up the deficiency that irradiator only have rectangular and circular collimators which cannot provide moderate protection for organs at risk. Blocks with 3% transmission were designed based on the contours of central nervous system by a state-of-art program, BlockGen.

A protocol was developed for immobilization and image acquisition. 60 kVp was found to give the highest contrast of iodine, so it was set as the tube voltage for image acquisition. The deviations of positioning, i.e. the same mouse in separate scanning, are measured as 0.22±0.44 mm in LR axis, 0.15±0.30 mm in PA axis, and -0.24±0.25 mm in IS axis. Blocks with a 1.5 mm margin which can shield brain and spinal cord even in the worst case, were printed for opposed lateral beams; they were verified on fluoroscopy.

The block system was modified to eliminate potential human errors. Comparison on brain and spinal cord among different mice showed the largest deviation in 2.6 mm, however, with manually selection of the middle one, 1.5 mm margin is enough to shield central nervous system. Indicating that a generic block could be used in the experiment that does not require a very accurate treatment. The generic block can significant save time and effort for preclinical radiation treatment experiment. In this study, a platform that is capable of enhancing contrast imaging and allowing precise radiation therapy to be performed on genetically-engineered mice with head and neck cancer has been developed. This paves the way for more accurate head and neck mice model radiation therapy studies. In addition, the platform could be used in other types of preclinical studies.

Intensity modulated radiation therapy (IMRT) is commonly used to treat head and neck cancer but relies on the experience and skill of the treatment planner. Previous knowledge based radiation therapy (KBRT) used a database of 105 patient cases from Duke University Medical Center to derive the constraints and fluence map to be used as input into Eclipse. Because IMRT relies heavily on the treatment planner, a re-optimized database was created to further improve the current database and its results.

Each of the 105 patient cases was re-optimized to further lower the dose to organs at risk while keeping the planning target volume (PTV) homogeneity. Out of 105 patients, 41 had noticeable improvements and 64 had minimal or no difference. The previous versions of KBRT were used to find the matching patient based on geometry and to derive constraints that would be inputted into Eclipse for optimization. Two methods of KBRT were tested. The first method used a dose warping algorithm to compute constraints and the second method used constraints from the matching patient.

The results from the old database and re-optimized database that used the dose warping algorithm produced dose volume histograms with little to no differences. The results using constraints from matching patient showed improvements in ipsilateral parotid, larynx, oral cavity, and brainstem after re-optimization. Comparing method one and method two, there were no significant benefits of re-optimizing as the dose warping algorithm was able to produce similar results. The dose warping algorithm was significantly worse for contralateral parotid but significantly better for brainstem.

Worldwide, head and neck squamous cell cancers (HNSCC) account for over 375,000 deaths annually. The majority of these cancers arise in the outermost squamous cells which progress through a series of precancerous changes before developing into invasive HNSCC. It is widely accepted that prognosis is strongly correlated to the stage of diagnosis, with early detection more than doubling the patient’s chance of survival. Currently, however, 60% of HNSCCs are diagnosed when they have already progressed to stage 3 or stage 4 disease. The current diagnostic method of visual examination often fails to recognize early indicators of HNSCC, thereby missing an important prevention window.

Determination of cancer from non-malignant tissues is dependent on pathological examination of lesion biopsies. Thus, all patients with any clinically suspicious lesions undergo surgical biopsies. Furthermore, these surgical biopsies carry risks. In addition to the risk of general anesthesia for patients undergoing panedoscopy, some patients have poor healing and develop ulcerations or infections as a result of surgical biopsy at any anatomical site. Additionally, studies have shown that approximately 50% of suspected biopsies are later pathologically confirmed normal. An enormous amount of labor, facility, and monetary resources are expended on non-malignant biopsies and patients who ultimately have no malignancy. It would be of immense overall benefit to clinicians and patients to have a non-invasive and portable technique that could rapidly identify those patients that would benefit from further surgical biopsy from those that only need follow-up clinical observations.

Once carcinoma is confirmed in a patient, treatment currently involves modalities of surgery, radiation, and chemotherapy. Radiotherapy plays a significant role, particularly in the management of localized HNSCC, because it is a non-invasive and function-preserving modality. However, the effectiveness of radiotherapy is limited by hypoxia. Previous studies showed that tumors reoxygenated during radiotherapy treatment may have a better prognosis. Despite decades of work, there is still no reliable, cost-effective way for measuring tumor hypoxia over multiple time points to estimate the prognosis.

To address these unmet clinical needs, three aims were proposed. The first aim was to improve early detection by identifying biomarkers of early pre-cancer as well as developing an objective algorithm to detect early disease. Neovasculature is an important biomarker for early cancer diagnosis. Even before the development of a clinically detectable lesion, the tumor vasculature undergoes structural and morphological changes in response to oncogenic signaling pathways [8]. Without receiving a sufficient supply of oxygen and nutrients to proliferate, early tumor growth is limited to only 1-2 mm. High-resolution optical imaging is well suited to characterize the earliest neovascularization changes that accompany neoplasia owing to its sensitivity to hemoglobin absorption and resolution to visualize capillary level architecture. Dark field microscopy is a low-cost and robust method to image the neovasculature. We imaged neovascularization in vivo in a spontaneous hamster oral mucosa carcinogen model using a label-free, reflected-light spectral dark field microscope. Hamsters’ cheek pouches were painted with 7, 12-Dimethylbenz[a]anthracene (DMBA) to induce precancerous to cancerous changes, or mineral oil as control. Spectral dark field images were obtained during carcinogenesis and in control oral mucosa, and quantitative vascular features were computed. Vascular tortuosity increased significantly in oral mucosa diagnosed as hyperplasia, dysplasia and squamous cell carcinoma (SCC) compared to normal. Vascular diameter and area fraction decreased significantly in dysplasia and SCC compared to normal. The areas under the receiver operative characteristic (ROC) curves (AUC) computed using a Support Vector Machine (SVM) were 0.95 and 0.84 for identifying SCC or dysplasia, respectively, vs. normal and hyperplasia oral mucosa combined. To improve AUCs for identifying dysplasia, quantitative vascular features were computed again after the vessels were split into large and small vessels based on diameter. The large vessels preserved the same significant trends, while small vessels demonstrated the opposite trends. Significant increases in diameter and decreases in area fraction were observed in SCC and dysplasia. The AUCs were improved to 0.99 and 0.92 for identifying SCC and dysplasia. These results suggest that dark field vascular imaging is a promising tool for pre-cancer detection.

Optical imaging can also be applied to quantifying other important characteristics of solid tumors in head and neck cancer (HNC), such as hypoxia, abnormal vascularity and cell proliferation. Diffuse reflectance spectroscopy is a simple and robust method to measure tissue oxygenation, vascularity and cell density. It is particularly suitable for applications in the operation room because of its compact design and portability. In addition, a fiber probe-based system is ideal for obtaining measurements at suspicious lesions in the head and neck area during surgery. Thus, my second aim was to reduce the number of unnecessary HNSCC biopsies by developing a robust tool and rapid analysis method appropriate for clinical settings. We propose the use of morphological optical biomarkers for rapid detection of human HNSCC by leveraging the underlying tissue characteristics in the aerodigestive tracts Prior to biopsy, diffuse reflectance spectra were obtained from malignant and contra-lateral non-malignant tissues of 57 patients undergoing panendoscopy. Oxygen saturation (SO2), total hemoglobin concentration ([THb]), and the reduced scattering coefficient were extracted using an inverse Monte Carlo (MC) method previously developed by former student in our lab. Differences in malignant and non-malignant tissues were examined based on two different groupings: by anatomical site and by morphological tissue type. Measurements were acquired from 252 sites, 51 of which were pathologically classified as SCC. Optical biomarkers exhibited statistical differences between malignant and non-malignant samples. Contrast was enhanced when parsing tissues by morphological classification rather than by anatomical subtype for unpaired comparisons. Corresponding linear discriminant models using multiple optical biomarkers showed improved predictive ability when accounting for morphological classification, particularly in node-positive lesions. The false-positive rate was retrospectively found to decrease by 34.2% in morphologically- vs. anatomically-derived predictive models. In glottic tissue, the surgeon exhibited a false-positive rate of 45.7% while the device showed a lower false-positive rate of only 12.4%. Additionally, comparisons of optical parameters were made to further understand the physiology of tumor staging and potential causes of high surgeon false-positive rates. Optical spectroscopy is a user-friendly, non-invasive tool capable of providing quantitative information to discriminate malignant from non-malignant head and neck tissues. Predictive models demonstrated promising results for diagnostics. Furthermore, the strategy described appears to be well suited to reduce the clinical false-positive rate.

To further improve the speed for extracting the tissue oxygenation and [THb] to reduce the time when patients were under anesthesia, the third aim was to develop a rapid heuristic ratiometric analysis for estimating tissue [THb] and SO2 from measured tissue diffuse reflectance spectra. The analysis was validated in tissue-mimicking phantoms and applied to clinical measurements in head and neck, cervical and breast tissues. The analysis works in two steps. First, a linear equation that translates the ratio of the diffuse reflectance spectra at 584 nm to 545 nm to estimate the tissue [THb] using a Monte carlo (MC)-based lookup table was developed. This equation is independent of tissue scattering and oxygen saturation. Second, SO2 was estimated using non-linear logistic equations that translate the ratio of the diffuse reflectance spectra at 539 nm to 545 nm into the tissue SO2. Correlations coefficients of 0.89 (0.86), 0.77 (0.71) and 0.69 (0.43) were obtained for the tissue hemoglobin concentration (oxygen saturation) values extracted using the full spectral MC and the ratiometric analysis, for clinical measurements in head and neck, breast and cervical tissues, respectively. The ratiometric analysis was more than 4000 times faster than the inverse MC analysis for estimating tissue [THb] and SO2 in simulated phantom experiments. In addition, the discriminatory power of the two analyses was similar. These results show the potential of such empirical tools to rapidly estimate tissue hemoglobin and oxygenation for real-time applications.

In addition to its use as a diagnostic marker for various cancers, tissue oxygenation is believed to play a role in the success of cancer therapies, particularly radiotherapy. However, since little effort has been made to develop tools to exploit this relationship, the fourth aim was to estimate patient prognosis by measuring tumor hypoxia over multiple time points so physicians are able to develop more informed and effective clinical treatment plan. To test if oxygenation kinetics correlates with the likelihood for local tumor control following fractionated radiotherapy, we again used diffuse reflectance spectroscopy to noninvasively measure tumor vascular oxygenation and [THb] associated with radiotherapy of 5 daily fractions (7.5, 9 or 13.5 Gy/day) in FaDu xenografts. Spectroscopy measurements were obtained immediately before each daily radiation fraction and during the week after radiotherapy. SO2 and [THb] were computed using an inverse MC model. Oxygenation kinetics during and after radiotherapy, but before a change in tumor volume, was associated with local tumor control. Locally controlled tumors exhibited significantly faster increases in oxygenation after radiotherapy (days 12-15) compared with tumors that recurred locally. (2) Within the group of tumors that recurred, faster increases in oxygenation during radiotherapy (days 3-5) were correlated with earlier recurrence times. An AUC of 0.74 was achieved when classifying the local control tumors from all irradiated tumors using the oxygen kinetics with a logistic regression model. (3) The rate of increase in oxygenation was radiation dose dependent. Radiation doses ≤9.5 Gy/day did not initiate an increase in oxygenation whereas 13.5 Gy/day triggered significant increases in oxygenation during and after radiotherapy. Additional confirmation is required in other tumor models, but these results suggest that monitoring tumor oxygenation kinetics could aid in the prediction of local tumor control after radiotherapy.

Angiogenesis is a highly regulated process to support tissue growth. Neovasculature is designed by nature to grow toward areas lacking nutrition and oxygen. Cancer cells proliferate too quickly to have their nutritional and oxygen needs completely satisfied, which results in an imbalanced state of angiogenesis leading to tortuous blood vessels, hypoxic tissues and radioresistance. We characterized the tumor-induced vascular features with simple, robust and low-cost dark field microscopy and spectroscopy to enable early cancer diagnosis, improvement of surgical biopsy accuracy and better predict the prognosis of radiotherapy for HNC. Our results demonstrated that these noninvasively measured, label-free vascular features are able to detect pre-cancer, reduce unnecessary surgical biopsies and predict prognosis of radiotherapy.

Purpose: Our primary goal was to examine the effect of PET image reconstruction parameters on baseline and early-treatment FDG-PET/CT quantitative imaging. Early-treatment changes in tumor metabolism in primary tumor and nodes can potentially determine if the patient is responding to therapy, but this assessment can change based on the reconstruction parameters. We investigated the effect of the following reconstruction parameters: number of Ordered-Subset-Expectation-Maximization (OSEM) iterations, post-reconstruction smoothing, and quantitative metrics (SUV-max, SUV-mean, SUV-peak).

A concurrent investigation explored in detail the sampling parameters of SUV-peak by way of a Monte Carlo digital phantom study. SUV-peak was proposed as a compromise between SUV-max and SUV-mean, in hope to retain key attractive features of these two metrics (inter-physician independence of SUV-max, noise-averaging of SUV-mean) but reduce unwanted errors (noise dependence of SUV-max, contour-dependence of SUV-mean). Sampling parameters have vaguely been defined, in particular, the scanning resolution (i.e. 1 voxel, 1/2 voxel, 1/4 voxel, etc.) of the SUV-peak spherical ROI . We examined the role that partial-voxel scanning plays in tumor SUV recovery in both noise-free and realistic OS-EM noise environments.

Materials and Methods: The response assessment investigation involved 19 patients on an IRB-approved study who underwent 2 baseline PET scans (mean-separation = 11 days) prior to chemoradiotherapy (70 Gy, 2 Gy/fraction). An intra-treatment PET scan was performed early in the course of therapy (10-20 Gy, mean = 14 Gy). The images were reconstructed with varying OS-EM iterations (1-12) and Gaussian post-smoothing (0-7 mm). Patients were analyzed in two separate groups, distinguished by the PET/CT scanner used to acquire data: (1) GE Discovery STE; and (2) Siemens Biograph mCT. For each combination of iterations and smoothing, Bland-Altman analysis was applied to quantitative metrics (SUV-max, SUV-mean, SUV-peak) from the baseline scans to evaluate metabolic variability (repeatability, R = 1.96&sigma). The number and extent of early treatment changes that were significant, i.e., exceeding repeatability, was assessed.

An original SUV-peak algorithm was developed, which measures SUV-max and SUV-peak for as small as 1/32 voxel scanning. Two rounds of digital phantoms were generated for the SUV-peak investigation. First, 10,000 spherical tumors were generated at a random matrix location for each diameter 1-4 cm and smoothed with an isotropic Gaussian, FWHM = 0.8 cm, then evaluated using the SUV-peak algorithm. Next, realistic body-sized phantoms were generated with background activity, and 1,000 spherical tumors of activity 4 time the background for each diameter (1-4cm) were placed inside (8 tumors per phantom, location randomized within certain constraints). These images received realistic corrections in projection space for attenuation, spatial resolution, and noise, were reconstructed with an in-house OS-EM algorithm, and then assessed using the SUV-peak algorithm. The mean recovered activity above background and its coefficient of variation were calculated for all metrics for each tumor size, for both simulations. For the realistic noise simulation, various levels of Gaussian smoothing was applied post-reconstruction, the effects summarized in plots showing coefficient of variation vs. mean recovered activity above background - a comparison of the effectiveness of SUV-max and SUV-peak.

Results: For the GE Discovery STE 2D cases averaged over all metrics (SUV-max, SUV-mean, SUV-peak) and structures (GTV, LN), repeatability, R, improved with increasing smoothing and decreasing iterations. Individually, SUV-mean repeatability was less affected by the number of iterations, but demonstrated the same relationship with smoothing. SUV-mean outperformed SUV-max and SUV-peak with regards to the number of cases exceeding repeatability, N. Considering R, N, and the sum of relative metric change outside repeatability, &Omega, averaged over all metrics and all structures, and normalized, several combinations of reconstruction parameters produced five optimal combinations above set thresholds: 1 iteration with 0.1-3.0 mm smoothing; and 2 iterations with 2.0-3.0 mm smoothing. Current GE 2D reconstruction protocol for HN cases uses 2 iterations and 3.0 mm post-smoothing, which lies on the edge, but within these recommendations.

The relationship between repeatability and number of iterations for the 3D cases was more complex; SUV-max demonstrated the best repeatability with 2 iterations, with both SUV-mean and SUV-peak reaching the best repeatability with 4 iterations. The same dependence on smoothing was noted, i.e. increased smoothing gives lover (desirable) repeatability. SUV-mean once again outperformed SUV-max and SUV-peak with regards to the number of cases exceeding repeatability, N. The calculations of N and &Omega averaged over all metrics were limited severely by the low number of cases, damaging the statistical significance of the following recommendation. Three optimal combinations with averaged and normalized R, N, &Omega, above a set threshold are recommended as most effective reconstruction parameter combinations: 4 iterations with 2.0-4.0 mm smoothing. Current Siemens 3D reconstruction protocol for HN cases uses 4 iterations and 3.0 mm post-smoothing, which lies within these recommended parameters. However, no statistically significant conclusions could be drawn from this analysis for this scanner, and performing similar data analysis on a larger patient pool is proposed.

The minimum spherical tumor diameter required for full recovery was 3.0-3.5 cm for SUV-peak, and 2.5-3.0 cm for SUV-max. SUV-max was found to overestimate the recovered value of tumors by up to 46% (vs. 10% for SUV-peak); above the minimum diameter for full recovery, SUV-peak values were significantly closer to actual tumor activity. Considering only the realistic noise tumors, the coefficient of variation for SUV-max ranged from 5.5-17.7%, whereas for SUV-peak these values were lower, 2.7-13.2%. Partial-voxel scanning did not substantially affect the coefficient of variation (<0.2%). Comparison of coefficient of variation vs. mean recovered value demonstrated that SUV-max with additional Gaussian smoothing outperforms SUV-peak by up to 0.8% for 1 cm tumors and 0.2% for 4 cm tumors. Other tumor sizes showed little difference between the two metrics.

Conclusion: For patients scanned on the GE Discovery STE using the HN protocol (2D acquisition mode), images reconstructed for quantitative analysis may benefit from a low number of OS-EM iterations (≤ 2). Some post-reconstruction smoothing proved to be beneficial (1.0 mm ≤ FWHM ≤ 3.0 mm), however, over-smoothing for the sake of more qualitatively appealing images or improved image quality metric (e.g. SNR, CNR) may prove detrimental to quantitative response assessment analysis. Our results for the Siemens Biograph mCT using the HN protocol (3D acquisition mode) demonstrated favor towards 4 iterations and limited range of smoothing (2.0 mm ≤ FWHM ≤ 4.0 mm). These results are statistically limited, further cases are necessary for any conclusive recommendations on reconstruction parameters.

SUV-peak was shown to reduce uncertainties associated with quantitative PET image analysis when compared directly to SUV-max. Above the minimum tumor diameter required for full recovery, SUV-peak also provides a better estimate of the actual tumor activity. However, initial comparisons of SUV-peak and SUV-max over various levels of additional Gaussian smoothing found SUV-max more favorable. Partial-voxel scanning of SUV-peak did not reduce the metric's coefficient of variation in images with realistic noise. Therefore, a phantom investigation is proposed to compare SUV-peak and SUV-max of real scanned images with various levels of post-smoothing, which may conclusively eliminate the need for SUV-peak.

Abstract

Purpose: The aim of this study is to quantify the effectiveness of adaptive radiation therapy (ART) when anatomical changes to the tumor and/or the organs are observed for head and neck patients during the course of intensity modulated radiation therapy (IMRT).

Methods and Materials: In this study, ART was retrospectively studied in 10 head and neck cancer treated patients after examining the 2nd CT, obtained after the first several fractions of radiotherapy, to see if anatomical changes had taken place. The adaptive treatment plan (ATP) was generated on the 2nd CT to mimic the relative dose-volume histograms of the spinal cord, brainstem, parotid glands, larynx, and oral cavity from the original treatment plan. The total ATP was generated as the sum of the original treatment plan delivered to the initial CT for the first several fractions and the ATP delivered to the 2nd CT for the remaining fractions. The delivered treatment plan (DTP) was generated as the sum of the original treatment plan delivered to the initial CT for the first several fractions and the original treatment plan delivered to the 2nd CT for the remaining fractions. For quantification of the effectiveness of ART, planning target volume (PTV) coverage and homogeneity, maximum dose to the brainstem and spinal cord, and median, mean doses, and D1% (highest dose to 1% volume) for the parotid glands, the oral cavity, and the larynx were compared between the adaptive treatment plan (ATP) and delivered treatment plan (DTP) using the Wilcoxon signed-rank test, a non-parametric comparison test. For a total of 15 comparisons, significance was set at p = 0.0033 accounting for Bonferroni correction.

Results: For ATP compared to DTP, PTV44/70 homogeneity was improved by 10.38% (p = 0.0234) and 7.96% (p = 0.04922) respectively. PTV44/70 coverage (%volume covered by prescription dose) were improved by 7.27% (p = 0.0078) and 12.00% (p = 0.0020) respectively. Maximum dose to the spinal cord and brainstem were reduced by 6.47% (p = 0.0195) and 8.24% (p = 0.0098), respectively. Median and mean doses for the parotid glands were reduced by 6.01% (p = 0.0029) and 4.14% (p = 0.0043) respectively whereas D1% remained approximately the same with a reduction of 0.78% (p = 0.8789). Median dose to oral cavity was reduced by 0.20%, but mean dose and D1% increased by 0.43% and 2.12%, respectively; however all oral cavity changes were insignificant (p = 0.9102, p = 0.7344, and p = 0.2031 respectively). Similarly, larynx mean dose was reduced by 3.54%, median dose was reduced by 2.15%, and D1% was reduced by 7.11%, but all reductions were statistically insignificant (p = 0.5625, p = 0.6875, and p = 0.8789 respectively).

Conclusions: In cases where anatomical changes are observed during therapy, ART can be applied to significantly reduce median parotid glands dose and improve target coverage. However, these changes are small and may not be clinically significant, implying that adaptive radiotherapy may not provide benefit for head-and-neck cases, on average.

Purpose: The purpose of this study was to assess the feasibility of using dynamic contrast-enhanced MRI to monitor early treatment-induced changes in pharmacokinetic (PK) parameters in head and neck cancer patients. The intrinsic variability of three parameters (Ktrans, v_e, and iAUC60) without treatment intervention was measured and compared to the treatment-induced variability.

Materials and Methods: Twenty patients were imaged while undergoing chemoradiation therapy (CRT) for head and neck malignancies. The imaging protocol included two baseline scans one week apart (B1, B2), and a third scan after 1-2 weeks of chemoradiation (ETX - early treatment). The images were acquired on a 1.5T scanner in the coronal plane with a temporal resolution of 10 sec. A population-averaged arterial input function was calculated from plasma concentration curves in both the left and the right carotids of each patient at each time point (B1, B2, ETX). The statistical significance of using a left/right AIF or a time-point-specific AIF was evaluated using Bland-Altman plots. To further ensure the correct calculation of PK parameters, the accuracy of the flip angles produced by the MR scanner was measured in phantoms and a volunteer. PK analysis was performed in iCAD (Nashua, NH) based on the modified Tofts model. This study focuses on two PK parameters used in the Tofts model (Ktrans, v_e), and one semi-quantitative parameter that was also calculated in iCAD using an uptake integral approach (iAUC60). Ktrans, v_e, and iAUC60 were averaged over regions of interest (ROIs), some of which covered primary tumors, and others of which covered known nodal metastases. Bland-Altman plots were used to describe the intrinsic variability in each parameter between the two baseline scans. The coefficient of repeatability (CR) between the baseline values was determined from the Bland-Altman plots and compared to the magnitude of the observed treatment-induced changes.

Results: The plasma parameters for the population-averaged AIF were a₁ = 27.1135 kg/liter, a₂ = 17.6486 kg/liter, m₁ = 11.7525 min-1, and m₂ = 0.2054 min-1. The use of a left- or right-sided AIF was determined to be unnecessary, as it did not give statistically different PK parameters than the population-averaged AIF. The use of a time-point-specific AIF was not necessary in most cases, though it may give more accurate results when Ktrans values are > 1 min-1. The flip angle tests revealed high inaccuracies at a flip angle of 5¡ã, so flip angles ¡Ü 5¡ã were not used in PK analysis. The intrinsic variability of Ktrans, v_e, and iAUC60 was very high. For nodes, the CRs from the B1-B2 Bland-Altman plots were 0.725 min-1 for Ktrans, 0.315 for v_e, and 18.15 mM-sec for iAUC60. The fractions of node ROIs which showed treatment-induced changes greater than the CR were 3 out of 14 for Ktrans, 3 out of 17 for v_e, and 7 out of 17 for iAUC60. For primaries, the CRs were 1.385 min-1 for Ktrans, 0.305 for v_e, and 62.85 mM-sec for iAUC60. The fractions of primary ROIs which showed treatment-induced changes greater than the CR were 0 out of 9 for Ktrans, 1 out of 11 for v_e, and 2 out of 12 for iAUC60.

Conclusions: A population-averaged AIF for head and neck was generated that accounts for differences in right vs. left carotids, day-to-day AIF fluctuations, and treatment-induced AIF changes. It is not necessary to use a side-specific or a time-point-specific AIF. When Ktrans is greater than 1 min-1, PK parameter accuracy may be improved with the use of a time-point-specific AIF. Using the average AIF, large intrinsic fluctuations were observed in ROI-averaged values of Ktrans, v_e, and iAUC60, making these parameters poor evaluators of early treatment response in head and neck cancer. Nodes were slightly more likely than primaries to show significant treatment-induced changes. Overall, the use of averaged MR-based PK parameters to assess early treatment response is limited and challenging. An analysis of voxel-based variability might be better suited to this task.