Prognostic Value of 18F-Fluorodeoxyglucose–Positron Emission Tomography/Magnetic Resonance Imaging in Patients With Hypopharyngeal Squamous Cell Carcinoma : Journal of Computer Assisted Tomography

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Neuroimaging: Head and Neck

Prognostic Value of 18F-Fluorodeoxyglucose–Positron Emission Tomography/Magnetic Resonance Imaging in Patients With Hypopharyngeal Squamous Cell Carcinoma

Huang, Caiyun MD∗,†; Zhang, Lingyu MD; Meng, Zhaoting MD; Song, Tianbin MD§; Mukherji, Suresh Kumar MD, MBA, FACR; Chen, Xiaohong MD, PhD; Lu, Jie MD, PhD§,#,∗∗; Xian, Junfang MD, PhD

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Journal of Computer Assisted Tomography 46(6):p 968-977, 11/12 2022. | DOI: 10.1097/RCT.0000000000001365
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Abstract

Hypopharyngeal squamous cell carcinoma (HSCC) is rare, accounting for only 3% to 5% of malignant tumors of the head and neck, but it has the worst prognosis among head and neck cancers.1,2 The current treatments for HSCC include radiotherapy and chemotherapy. However, despite aggressive treatment, the 5-year survival rate of HSCC remains poor, ranging from 25% to 40%.3 Identifying a predictive marker for the prognosis of HSCC patients would enable patients with nonresponsive disease to avoid unnecessary treatment and the financial burden and toxic adverse effects associated with radiotherapy and chemotherapy. The most commonly used and important factor for guiding the treatment of head and neck squamous cell carcinoma (HNSCC) is the TNM staging system. However, TNM staging does not always provide satisfactory results, and tumors are heterogeneous at each stage with different propensities for relapse.4,5 Previous studies reported p53 and vascular endothelial growth factor expressions as prognostic indicators in HNSCC.6 However, obtaining pathological specimens to evaluate their expressions involves invasive procedures. Therefore, it is important to identify new noninvasive prognostic factors to individualize patient treatment strategies and improve survival outcome.

Many imaging markers have been investigated to predict the survival outcomes of cancer patients. For example, quantitative analysis of diffusion magnetic resonance imaging (MRI) can provide value for the prognostic prediction and treatment monitoring of head and neck cancers.7–13 Dynamic contrast enhanced–MRI (DCE-MRI) has been used for diagnosis and monitoring the therapeutic response in head and neck cancers.14–18 In addition, 18F-fluorodeoxyglucose–positron emission tomography/computed tomography (18F-FDG PET/CT) measurement of tumor glucose metabolism evaluates tumor metabolic activity and is valuable for the diagnosis and staging of HNSCC patients, assessing treatment options, and helping predict outcome.19–23 However, few studies have reported the predictive values of diffusion-weighted imaging (DWI)–MRI, DCE-MRI, and 18F-FDG–PET parameters in hypopharyngeal cancer, with the use of multivariable Cox regression analysis or inclusion of clinical parameters.

Integrated PET/MRI has demonstrated enormous potential in the diagnosis, treatment planning, efficacy monitoring, and survival follow-up of cancer patients.24–30 The commonly used methods to obtain MRI parameters and PET parameters are separate imaging modalities. However, integrated PET/MRI synchronizes PET and MRI scans, which can achieve the best registration of structure, function, and molecular imaging information in time and space. This approach avoids time, physiology, or function errors and can obtain the same state metabolic parameters, diffusion parameters, and perfusion parameters to realize the value of synergy gain. Therefore, PET/MRI may be a useful method to obtain data for predicting the prognosis of HSCC patients.

Therefore, this study aimed to provide a new quantitative basis for improving the individual treatment plan of HSCC patients and accurately assessing their prognosis by exploring the value of integrated PET/MRI multiparameters for prognostic evaluation. To the best of our knowledge, few studies have evaluated the prognosis prediction of hypopharyngeal cancer patients using PET/MRI parameters.

MATERIALS AND METHODS

Patients

This prospective study was approved by the institutional review board at Beijing Tongren Hospital. Between February 2017 and March 2019, a total of 21 patients newly diagnosed with pathologically confirmed primary HSCC were finally included. No patients had received radiation or chemotherapy. All patients had a Karnofsky score of more than 60 with a blood glucose level less than 8 mmol/L. We obtained written informed consent from all patients before enrollment.

Positron Emission Tomography/Computed Tomography Imaging Protocol

All patients fasted for at least 6 hours before examination. Patients then received a whole-body 96-loop uMI510 PET/CT scan (United Imaging, China) and integrated 3.0 T PET/MRI (GE Signa, Wis) neck scan on the same day, with one injection of 18F-FDG. Imaging began 60 minutes after intravenous injection of 18F-FDG (target fixed dose of 0.1 mCi/kg) ranging from vertex to the midthigh (slice thickness, 5 mm). Positron emission tomography scanning parameters were performed in 3D mode at 3 minutes per bed for the entire body (5 beds). Time-of-flight (TOF) technology was used to reconstruct the image. The PET reconstruction parameters were 2 iterative ordered subset expectation maximization, 24 subsets, Gaussian filter half-height width 3.0 mm, and scatter correction. Computed tomography scanning parameters were 120 kV, 180 mAs, and pitch 0.9375. Contrast-enhanced CT scans were not performed. In addition, patients were instructed to minimize swallowing, coughing, and other movements during the scans to minimize motion artifact in the region of the hypopharynx.

Positron Emission Tomography/Magnetic Resonance Imaging Protocol

The TOF PET/MRI scanner with a 19-unit phased array of head and neck combined coil was used after completion of the PET/CT scan. The scan ranged from the base of the skull to the inlet of the thoracis. The sequences included an axial T1-weighted image (repetition time [TR]/echo time [TE] = 420/14 ms; slice thickness = 5 mm; matrix = 384 × 256; field of view [FOV] = 22 × 22 cm), an axial T2-weighted image (TR/TE = 5200/93.6 ms; slice thickness = 5 mm; matrix = 512 × 256; FOV = 22 × 22 cm), short τ inversion recovery (STIR)–DWI sequence (TR/TE = 2528/71 ms; slice thickness = 5 mm; matrix = 96 × 96; FOV = 22 × 22 cm; b = 0,800 s/mm2), and DCE sequence (TR/TE = 4.4/1.9 ms; slice thickness = 3.2 mm; matrix = 256 × 224; FOV = 22 × 18 cm). The acquisition time was 10 minutes with one bed position. Time-of-flight technology was used for reconstruction. The PET reconstruction parameters were 2 iterations subset expectation maximization algorithm, 28 subsets, 5-mm Gaussian transaxial filter, FOV of 30 cm, and matrix size of 192 × 192. The PET images attenuate based on the Dixon MR sequences.

Image Analysis

Two radiologists (with 10 and 17 years of experience in head and neck radiology) independently interpreted the PET/CT and PET/MRI images using the AW 4.6 Workstation (GE Healthcare, Wis). The patient/tumor characteristics were age, tumor subsite, T stage, N stage, M stage, and clinical stage. TNM staging and clinical staging were performed according to the eighth edition of the American Joint Committee on Cancer TNM classification.

The maximum standardized uptake value (SUVmax), the average standardized uptake value SUVavg, and the total lesion glycolysis (TLG) were measured by placing a volume of interest (VOI) carefully around the tumors using the workstation. We excluded FDG uptake outside the lesion (such as adjacent physiological uptake) from each VOI as much as possible. The tumor metabolic volume was determined using a threshold value of 40%. Metabolic tumor volume (MTV) = TLG / SUVavg.

The apparent diffusion coefficient (ADC) values (ADCmean and ADCmin) were measured using the Function tool software. Regions of interest were manually drawn along the tumor contour on the slice containing the largest area of the tumor.

The DCE-MRI data were analyzed using the Function tool and Gen IQ software. A round or ovoid region of interest (30 mm2) covering the most enhanced area were delineated for each lesion at its widest section. The region was selected to include as much of the tumor as possible and avoiding air-containing regions, hemorrhage, necrosis, and neighboring anatomical structures. Three quantitative parameters (the rate constant for transfer of contrast agent from plasma to extravascular, extracellular space [Ktrans], the rate constant for transfer of contrast agent from extravascular, extracellular space to the plasma [Kep], and the fractional volume of extravascular extracellular space [Ve]) were derived using a Tofts' 2-compartment pharmacokinetic model.

Six semiquantitative parameters were obtained as follow. The time course of the contrast index (CI) was plotted to obtain a time intensity curve. The parameters derived from the time intensity curve were the pre-enhancement signal intensity (SIpre), the maximum signal intensity (SImax), the time of the SImax (Tmax), and the signal intensity of the last phase of the scanning process (SIend). We then calculated the maximum CI (CImax), the peak signal intensity (SIpeak), the peak CI (CIpeak), the time of the SIpeak (Tpeak), slope, and washout rate (WR; Figs. 1, 2).

F1
FIGURE 1:
The PET/MRI in HSCC patient with good prognosis. A 53-year-old male patient with left pyrifom sinus carcinoma (arrow). A, Precontrast T1-weighted image. B, Precontrast T2-weighted image. C, Fused PET/T2-weighted image shows high FDG uptake of the tumor (arrow). D–F, PET image: (D) axial PET image, (E) coronal PET image, (F) sagittal PET image. SUVmax, SUVavg, and TLG were obtained by placing a VOI to cover the entire tumor. (G) ADC map. H, Contrast T1-weighted MR. I, Time-intensity curve. J–L, DCE-MRI color maps: (J) K trans, (K) K ep, and (L) V e. The patient overall survival was 34.6 months.
F2
FIGURE 2:
The PET/MRI in HSCC patient with poor prognosis. A 62-year-old male patient with left pyriform sinus carcinoma and lymph node metastasis (arrow). A, Precontrast T1-weighted image. B, Precontrast T2-weighted image. C, Fused PET/T2-weighted image shows high FDG uptake of the tumor (arrow). D–F, PET: (D) axial PET image, (E) coronal PET image, and (F) sagittal PET image. SUVmax, SUVavg, and TLG were obtained by placing a VOI to cover the entire tumor. G, ADC map. H, Contrast T1-weighted MR. I, Time-intensity curve. J–L, DCE-MRI color maps: (J) K trans, (K) K ep, and (L) V e. The patient overall survival was 10 months.

CImax = ((SImax − SIpre) / SIpre);

SIpeak: the first signal intensity point required by >0.9 (SImax − SIpre) + SIpre;

CIpeak = ((SIpeak − SIpre)/SIpre);

slope = ([(SImax − SIpre) / (SIpre × Tpeak)] × 100%);

WR = ([(SImax − SIend) / (SImax − SIpre)] × 100%)

Clinical Follow-up

Clinical examination and radiographic follow-up were performed for each patient as follows: every 3 months in the first year, every 6 months in the second year, and then annually. Imaging follow-up included neck ultrasound, CT, MRI, or PET/CT. No patients were excluded because of loss of follow-up.

The imaging data were evaluated using the revised Response Evaluation Criteria in Solid Tumors 1.1 criteria. Disease progression was defined as an increase in tumor diameter of 20% or greater or the presence of new metastases. Recurrence was defined as the disappearance of the original lesion by CT, MRI, or PET/CT review at 3 months after completion of radiotherapy or chemotherapy followed by a progressively enlarging mass in the hypopharynx detected by CT, MRI, or PET/CT review of greater than or equal to 6 months. All recurrent tumors were biopsy proven. Progression-free survival (PFS) was measured as the period from the date of the first PET/MRI examination to the date of tumor progression or study completion (July 3, 2020). Overall survival (OS) was defined as the period from the first PET/MRI examination to the time of death or study end.

Statistical Analysis

Data were analyzed using SPSS software (SPSS 22.0). Interreader correlation was calculated using intraclass correlation coefficient (ICC). The Kaplan-Meier method was used to draw survival curves, and the 2-sided log rank test was used to evaluate differences in OS and PFS between patient groups. Variables with a P value less than 0.05 were included for multivariate analysis using the Cox proportional hazards model. A P value less than 0.05 was considered to indicate statistical significance.

RESULTS

Patient Characteristics and Patient Outcome

A total of 21 HSCC patients were enrolled in the study; the mean patient age was 55.3 ± 6.3 years, and all patients were male. All patients received the appropriate treatment within 2 weeks of the imaging examination in accordance with the institutional guidelines. Therapy options included surgery, surgery + radiotherapy ± chemotherapy, or radiotherapy ± chemotherapy. During follow-up (mean, 20.3 months; range, 4.2–37.6), 2 patients (9.5%) showed local recurrences, 2 patients (9.5%) showed distant metastases, and 8 patients (38.1%) died from cancer-related death.

Interreader Correlation

The ICCs (95% confidence interval) for assessing the interreader correlation of measuring were 0.732 to 0.999 (P < 0.001; Table 1), indicating excellent agreement between the 2 radiologists.

TABLE 1 - The Interreader Correlation Between the Radiologists
Variable ICC 95% CI
SUVmax 0.989 0.974–0.995
SUVavg 0.998 0.997–0.999
TLG 0.999 0.998–1.000
MTV 0.997 0.992–0.999
ADCmean 0.851 0.663–0.938
ADCmin 0.844 0.659–0.933
K trans 0.895 0.763–0.956
K ep 0.906 0.786–0.961
V e 0.881 0.730–0.950
T max 0.863 0.679–0.945
T peak 0.860 0.676–0.943
CImax 0.818 0.594–0.925
CIpeak 0.821 0.596–0.927
Slope 0.732 0.423–0.888
WR 0.760 0.478–0.900
95% CI indicates 95% confidence interval.

Relationships Between Imaging Biomarkers and PFS/OS in HSCC Patients

The PET/MRI parameters in the overall patient group are presented in Table 2. The median value for each variable was used to divide HSCC patients into high or low groups for survival analyses.

TABLE 2 - Positron Emission Tomography/Magnetic Resonance Imaging Parameters of the Overall Patient Group
Variable Mean ± SD Range
SUVmax 17.23 ± 6.32 4.83–27.45
SUVavg 10.57 ± 4.16 2.28–17.19
TLG, g 96.19 ± 87.29 3.99–338.14
MTV, mL 8.45 ± 7.07 1.66–22.40
ADCmean, ×10−3 mm2/s 1.20 ± 0.328 0.615–1.62
ADCmin, ×10−3 mm2/s 0.65 ± 0.27 0.2–1.02
K trans, min−1 0.516 ± 0.19 0.231–0.951
K ep, min−1 1.53 ± 0.84 0.45–4.422
V e 0.420 ± 0.166 0.078–0.747
T max, s 180.372 ± 95.53 69.350–400.865
T peak, s 116.628 ± 79.198 35.291–327.638
CImax 1.456 ± 0.342 0.962–2.249
CIpeak 1.405 ± 0.354 0.875–2.249
Slope 0.017 ± 0.0098 0.0052–0.0426
WR 0.299 ± 0.184 0.025–0.747

In univariate analysis, PFS was significantly decreased in patients with high T stage and clinical stage (P < 0.05; Table 3). Overall survival was significantly better in patients with low T stage and low clinical stage (P < 0.05; Table 3). The survival curves plotted by Kaplan-Meier method are shown in Figures 3 and 4.

TABLE 3 - Univariate Analysis of Patient/Tumor Characteristics and PFS/OS
P
Variable No. Patients (%) PFS OS
Age, y 0.275 0.077
 <60 16 (76)
 ≥76 5 (24)
Tumor subsite 0.566 0.464
 Pyriform sinus 14 (67)
 Others* 7 (33)
T stage 0.015 0.006
 T1-2 10 (48)
 T3-4 11 (52)
N stage 0.191 0.090
 N0 9 (43)
 N1-2 12 (57)
M stage 0.437 0.203
 M0 17 (81)
 M1 4 (19)
Clinical stage 0.031 0.041
 I-II 7 (33)
 III-IV 14 (67)
*Others include posterior hypopharyngeal and post cricoid region.

F3
FIGURE 3:
Kaplan-Meier progression-free survival curves according to T stage (A) and clinical stage (B) in HSCC patients (P<0.05). (Term “*censored” in the charts indicates that survival time for the subjects could not be accurately determined as the event of interest had not occurred during the term of the study.
F4
FIGURE 4:
Kaplan-Meier overall survival curves according to T stage (A) and clinical stage (B) in HSCC patients (P<0.05).

Univariate analyses showed that high TLG and high MTV were associated with poor PFS (P < 0.05; Table 4). In addition, high TLG, high MTV, low ADCmean, and low ADCmin indicated poor OS (P < 0.05; Table 4). Survival curves are shown in Figures 5 and 6.

TABLE 4 - Univariate Analysis for the Association of PET/MRI Parameters With PFS/OS
P
Variable No. Patients (%) PFS OS
SUVmax 0.168 0.091
 ≥17.57 11 (52)
 <17.57 10 (48)
SUVavg 0.168 0.091
 ≥9.93 11 (52)
 <9.93 10 (48)
TLG, g 0.015 0.004
 ≥61.20 11 (52)
 <61.20 10 (48)
MTV, mL 0.004 0.026
 ≥5.30 11 (52)
 <5.30 10 (48)
ADCmean, ×10−3 mm2/s 0.050 0.021
 ≥1.26 11 (52)
 <1.26 10 (48)
ADCmin, ×10−3 mm2/s 0.050 0.039
 ≥0.694 11 (52)
 <0.694 10 (48)
K trans, min−1 0.058 0.228
 ≥0.505 11 (52)
 <0.505 10 (48)
K ep, min−1 0.531 0.099
 ≥1.395 11 (52)
 <1.395 10 (48)
V e 0.687 0.795
 ≥0.378 11 (52)
 <0.378 10 (48)
T max, s 0.113 0.501
 ≥159.991 11 (52)
 <159.991 10 (48)
T peak, s 0.692 0.612
 ≥83.038 11 (52)
 <83.038 10 (48)
CImax 0.182 0.172
 ≥1.408 11 (52)
 <1.408 10 (48)
CIpeak 0.182 0.172
 ≥1.362 11 (52)
 <1.362 10 (48)
Slope 0.398 0.976
 ≥0.015 11 (52)
 <0.015 10 (48)
WR 0.944 0.276
 ≥0.283 11 (52)
 <0.283 10 (48)

F5
FIGURE 5:
Kaplan-Meier progression-free survival curves according to TLG (A) and MTV (B) in HSCC patients (P<0.05).
F6
FIGURE 6:
Kaplan-Meier overall survival curves according to TLG (A), MTV (B), ADCmean (C), and ADCmin (D) in HSCC patients (P<0.05).

Cox Regression Analysis

In Cox multivariate analysis, MTV was an independent predictor of PFS, while TLG was an independent predictor of OS (Table 5).

TABLE 5 - Multivariate Cox Analysis
PFS OS
Variable Hazard Ratio 95% CI P Hazard Ratio 95% CI P
T stage 0.292 0.377
Clinical stage 0.187 0.491
TLG 0.935 13.289 1.515–116.595 0.020
MTV 7.360 1.506–35.956 0.014 0.917
ADCmean 0.551
ADCmin 0.598

DISCUSSION

In this study, we evaluated the ability of PET/MRI parameters and other clinical factors to predict the PFS and OS in patients with HSCC. Our results showed that pretreatment MTV of the primary tumor was the only independent predictor of PFS, while TLG was the only independent predictor of OS. To the best of our knowledge, there are few studies have demonstrated that TLG and MTV are independent prognostic factors for hypopharyngeal cancer. Although some studies have also shown a predictive effect of MTV and TLG in patients with HSCC, many of these reports included patients with other head and neck cancers, such as oropharyngeal, which may have influenced the results.20,31–34 However, in oropharyngeal cancer, human papillomavirus infection greatly influences prognosis, and therefore, oropharyngeal cancer cannot be discussed together with hypopharyngeal cancer. Therefore, we believe that our findings demonstrating the significance of MTV and TLG in patients with HSCC are significant.

Tumor stage and cervical lymph node involvement are poor prognostic factors in advanced HNSCC. Ildstad et al35 showed through multivariate analysis that T staging was the most important independent prognostic factor for the survival of patients with HNSCC. Gupta et al36 reported that tumor T stage can affect the local control rate; the 3-year local control rate of T1-2 stage patients was 49.7% and that of T3-4 stage patients was 43.1%. Chu et al37 reported that the number of positive cervical lymph node areas involved is the most important factor affecting the postoperative survival of patients with hypopharyngeal cancer. Although the results of these studies were not identical, the studies were in agreement in showing a statistically significant difference in OS among patients with different TNM stages. Our study supports these findings and showed that TNM stage directly correlated with the short-term outcome of HSCC, only by univariate analyses. The survival time of patients with higher T stage and clinical stage was shorter than that of patients with lower T stage and clinical stage, respectively.

Suzuki et al38 reported that the survival of hypopharyngeal cancer patients with primary SUVmax > 15.2 and SUVmax > 8 were associated with a lower OS. A higher SUVmax was also associated with a greater likelihood of lung and distant metastasis, which contributed to the lower long-term survival rate.38 Ishilara et al39 showed that the SUVmax of the primary site (p SUVmax) was a significant prognostic predictor of disease-free survival (DFS) of hypopharyngeal cancer patients. However, while p SUVmax predicted local control of T1-2 stage tumors, p SUVmax showed no significant correlation with T3-4 stage tumors.39 Pak et al40 demonstrated that SUVmean of 2.5 was an independent prognostic factor for DFS.40 However, other studies showed that SUVmax is not significant in predicting the prognosis of patients with head and neck cancer.41,42 The use of SUVmax as a prognostic predictor of head and neck tumors thus remains controversial. We did not find a significant relationship between SUV and short-term outcome in our study. Some possible explanations for this discrepancy include the relatively small number of patients and short-term duration of follow-up. Another explanation could be that SUVmax only represented the metabolic status of the highest metabolic region, with certain limitations. Thus, in heterogeneous tumors, the individual voxel value may not represent the entire tumor uptake. The overall metabolic status of the tumor should also be considered.

Although SUVmax may not be representative of the total tumor uptake for the entire tumor, volume-based parameters, such as MTV and TLG, may represent the total volume and total activity of the metabolically active tumor cells. Recent studies have demonstrated the ability of MTV to predict DFS in patients with head and neck cancer.43,44 Seol et al31 found that high MTV, but not SUVmax, was associated with poor PFS and OS in 59 patients with advanced head and neck cancer. Chung et al32 also showed that MTV predicted the short-term outcome and 2-year DFS in 82 pharyngeal cancer patients. Park et al45 showed that the risk of locoregional recurrence and death was more than 3-fold higher in patients with MTV greater than 18 mL compared with patients with MTV less than or equal to 18 mL. La et al33 found that MTV was an independent predictor for DFS and OS in patients with head and neck cancers. Our multifactor analysis results showed that the MTV value was a prognostic factor for PFS independent of other metabolic parameters and ADC values, suggesting that MTV may be more valuable than many previously discussed prognostic factors. A higher MTV value is associated with a more metabolically active and aggressive tumor. Another parameter that represents both the uptake of 18F-FDG and volume of the metabolically active tumor is TLG. Several studies have shown the utility of TLG as a prognostic biomarker. Kuwabara et al34 demonstrated that early TLG was an independent prognostic factor of PFS. Suzuki et al46 found that TLG of 42 or greater was significantly associated with shorter OS and DFS times. Pace et al47 stated that pretreatment SULpeak was a predictor of OS in patients with locally advanced oropharyngeal and hypopharyngeal squamous cell carcinomas (HSCCs) at a mean of 31.4 ± 21-month follow-up. Neither MTV nor TLG demonstrated any significance in the univariate analysis. The discrepancy between these findings could be due to differences in the population studied, because in the Pace study, only locally advanced (T3 and T4) oropharyngeal and HSCCs patients were included in the study, whereas in the other studies, patients with different stage HNSCC patients were included. The results of our study are consistent with most of these initial findings showing that TLG was the only independent prognostic factor for HSCC and patients with tumors having higher TLG had a significantly higher mortality rate.

Diffusion-weighted imaging technology can noninvasively reflect the diffusion of water molecules in biological tissues, and this diffusion can be quantified by using the ADC value. A number of histopathological and microscopic feature, such as micronecrosis, low cellularity (lower proliferation), high stromal content, and inflammation affect water diffusivity in tissues, resulting in higher ADC. These characteristics are also associated with resistance to treatment and poor outcome in patients with squamous cell carcinoma of the head and neck. Therefore, it is reasonable to speculate that high ADC value before pretreatment is associated with poor prognosis in patients squamous cell carcinoma of the head and neck. However, the results regarding the prognostic value of ADC in HNSCC have been variable.8–13,18,48–52 Several studies in patients with HNSCC who received chemoradiotherapy or radiotherapy alone reported that local treatment failed in patients with high pretreatment ADC values.8–12,18,48,50 However, other studies reported that HNSCC patients with low ADC values showed a poor prognosis.51 In addition, other reports indicated that ADC values do not predict treatment outcome for patients with HNSCC.49,52 In our cohort, the ADC values for the primary tumor were significantly correlated with OS in univariate analysis; however, multivariate analysis failed to confirm the independent prognostic value, suggesting that DWI may be a method to reflect and predict the prognosis of HSCC patients.

Multiphase DCE-MRI evaluates the microvascular status of tumors using a paramagnetic contrast agent. Chawla et al16 reported that Ktrans values were higher in HNSCC patients who respond to chemoradiation than in patients who did not respond to chemoradiation. Some reports showed that HNSCC patients with higher pretreatment nodal Ktrans values have a longer DFS (P = 0.029).15,16 Other studies indicated that Ktrans is the strongest predictor for PFS and OS in patients with HNSCC in lymph node metastases IV stage, which has important clinical value.53 Ng et al14 reported Kep tumor less than 3.79 min−1 and Ve node less than 0.23 as independent risk factors for both PFS and OS. However, our study did not reveal any significant result in DCE parameters, indicating that DCE parameters do not seem to be predictive of patient outcome for HSCC.

This study has several limitations. First, there was heterogeneity in the pathologic tumor grade, which may have confounded the determination of prognostic values. The patients enrolled in the study received a variety of treatment modalities, which may affect clinical outcome. However, this range of treatment reflects the daily practice at our cancer centers. The positive results of our initial investigation warrant further validation with multicenter prospective trials.

CONCLUSIONS

Our study demonstrated that MTV was an independent predictor of PFS in HSCC patients, while TLG was an independent predictor of OS. These results suggest that multiparametric PET/MRI may contribute to the selection of personalized treatment regimens. Our findings may help change the management and improve the prognosis of patients with HSCC.

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Keywords:

hypopharyngeal squamous cell carcinoma; positron emission tomography; magnetic resonance imaging; prognosis

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