- Email: [email protected]
Does volumetric measurement of cervical lymph nodes serve as an imaging biomarker for locoregional recurrence of oral squamous cell carcinoma?
Accepted Manuscript Does volumetric measurement of cervical lymph nodes serve as an imaging biomarker for locoregional recurrence of oral squamous cell carcinoma? Ali-Farid Safi, MD, DMD, Martin Kauke, MD, Hendrik Jung, DMD, Marco Timmer, MD, Jan Borggrefe, MD, Thorsten Persigehl, MD, Hans-Joachim Nickenig, MD, DMD, Max Zinser, MD, DMD, David Maintz, MD, Matthias Kreppel, MD, DMD, Joachim Zöller, MD, DMD PII:
S1010-5182(18)30101-X
DOI:
10.1016/j.jcms.2018.04.001
Reference:
YJCMS 2943
To appear in:
Journal of Cranio-Maxillo-Facial Surgery
Received Date: 17 December 2017 Revised Date:
13 March 2018
Accepted Date: 3 April 2018
Please cite this article as: Safi A-F, Kauke M, Jung H, Timmer M, Borggrefe J, Persigehl T, Nickenig H-J, Zinser M, Maintz D, Kreppel M, Zöller J, Does volumetric measurement of cervical lymph nodes serve as an imaging biomarker for locoregional recurrence of oral squamous cell carcinoma?, Journal of Cranio-Maxillofacial Surgery (2018), doi: 10.1016/j.jcms.2018.04.001. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
Does volumetric measurement of cervical lymph nodes serve as an imaging biomarker for locoregional recurrence of oral squamous cell carcinoma?
RI PT
Ali-Farid Safi (MD, DMD)1, Martin Kauke (MD)2, Hendrik Jung (DMD) 1, Marco Timmer (MD)2, Jan Borggrefe (MD) 3, Thorsten Persigehl (MD) 4, Hans-Joachim Nickenig (MD,
DMD)1, Max Zinser (MD, DMD) 1, David Maintz (MD) 4, Matthias Kreppel (MD, DMD)1,
Department for Oral and Craniomaxillofacial Plastic Surgery, University Hospital of
Cologne, Cologne, Germany
M AN U
1
SC
Joachim Zöller (MD, DMD)1
Department for General Neurosurgery, University Hospital of Cologne, Cologne, Germany
3
Department of Neuroradiology, University Hospital Cologne, Cologne, Germany
4
Department of Radiology, University Hospital Cologne, Cologne, Germany
Corresponding author
TE D
2
EP
Dr. med. Dr. med. dent. Ali-Farid Safi
Department for Oral and Craniomaxillofacial Plastic Surgery
AC C
University of Cologne Kerpener Straße 62 50931 Cologne Germany
e-mail: [email protected] Phone: +49 221 478 96594 Fax: +49 221 478 7360
ACCEPTED MANUSCRIPT Summary
INTRODUCTION Oral squamous cell carcinoma (OSCC) is the sixth most common malignancy worldwide
RI PT
(Jemal et al. 2009). It occurs at an annual incidence of approximately 263,000, with a
mortality rate of approximately 128,000 per year, and is accompanied by a 5-year survival rate of less than 50% (Jemal et al. 2009) (Vormittag et al. 2009). Despite significant
SC
diagnostic and therapeutic advances, the prognosis of patients with OSCC has not improved in the past three decades (Jemal et al. 2009). A major prognostic factor is locoregional
M AN U
relapse, as its diagnosis worsens survival to less than 30% (González García et al. 2009). Hence, it is of the utmost importance to identify parameters that can specifically predict locoregional recurrence and thus allow timely, adequate diagnosis and accurate therapeutic regimens (Patel et al. 2013). One such parameter is cervical lymph node status, as it has major
TE D
implications for treatment decision making and assessment of prognosis in daily clinical routine (Safi et al. 2017c). Accordingly, a preoperative clinical staging is necessary to sufficiently evaluate neck lymph node status (Kreppel et al. 2013). Computed tomography
EP
(CT) plays a pivotal role in the perioperative identification of lymph node metastasis and enables an exact nodal staging based on the TNM Classification of the Union Internationale
AC C
Contre le Cancer (UICC)/American Joint Committee on Cancer (AJCC) (Kreppel et al. 2013). This classification system considers the number and location of pathologically altered lymph nodes and their maximum diameter (Wittekind 2010). It differentiates between lymph nodes that are < 3 cm, between 3 and 6 cm, and > 6 cm (Wittekind 2010). Multiple studies have found these cutoff sizes to be significantly correlated with biological aggressiveness, the tendency to further metastasize, and the potential to reoccur (Wittekind 2010). Nonetheless, numerous investigators have demonstrated that these benchmark diameters of cervical lymph nodes are not able to sufficiently stratify the risk of patients with positive lymph nodes
ACCEPTED MANUSCRIPT (Lodder et al. 2012) (Ljumanovic et al. 2006) (Vergeer et al. 2006). Therefore, to overcome the shortcomings of the TNM classification, modifications of the nodal classification system are required. One such significant step forward might be the implementation of the volume of lymph nodes instead of the diameter, as recent studies have reported very promising results
RI PT
with the prognostic superiority of lymph node volumes (Lodder et al. 2012) (Yuan et al.
2017). However, two major problems need to be addressed: on one hand, studies considering the neck lymph node volume as a prognostic parameter specifically for patients with OSCC
SC
are rare; on the other hand, volumetric analysis frequently has been performed by multiplying the areas in each slice of a CT or by approximation with a cuboid or ellipsoid formula instead
M AN U
of automatic image processing, although this technique allows a relatively time-sparing and precise measurement of the volume (Lodder et al. 2012) (Yushkevich and Gerig 2017b) (Hadjiiski et al. 2010). To the best of our knowledge, data on the importance of neck lymph node volume, obtained by semiautomatic segmentation of CT images, are not available for
TE D
locoregional recurrence in patients with OSCC. Hence, we aimed to investigate whether lymph node volume would serve as an imaging biomarker that would allow a better risk
EP
stratification of locoregional failure than the conventional N Classification.
MATERIALS AND METHODS
AC C
Patients and data collection Our retrospective study followed the guidelines of the Declaration of Helsinki and consisted of 100 patients who were diagnosed and treated between 2006 and 2014 at our Department for Oral and Craniomaxillofacial Plastic Surgery. Inclusion criteria were patients with treatment-naive oral squamous cell carcinoma and primarily curative intended surgery with negative resection margins, in whom preoperative CT of the head and neck region was performed. Comprehensive neck dissection (level I to V) due to ipsilateral lymph node metastasis was chosen as an inclusion criterion. Exclusion criteria were neoadjuvant
ACCEPTED MANUSCRIPT chemoradiotherapy, T4b classification, perioperative death, unresectable disease, synchronous malignancy, follow-up < 3 months, and inadequate information to correctly determine clinicopathological characteristics. Surgery in combination with postoperative radiotherapy
days per week for a total dose of 60 to 65 Gy.
RI PT
was chosen for locally advanced disease. Radiotherapy included daily doses of 1.8 to 2.0 Gy 5
In accordance with existing literature, recurrence was defined as a tumor of similar histology appearing after 6 weeks of treatment and within the first 3 years after therapy of the primary
SC
tumor (González García et al. 2009). Regional recurrences were defined as recurrences
within the lymph neck nodes, and distant recurrences as metastasis outside the head and neck
M AN U
region.
Due to the retrospective nature of this study, it was granted an exemption in writing by the University Hospital institutional review board.
Clinicopathologic data were collected from medical records as well as from pathology and
TE D
surgery reports. Parameters were carefully reviewed and included gender, age, clinical N classification, extracapsular spread, central necrosis, diameter, grading, number of positive lymph nodes, and nodal volume. All cases were staged histopathologically according to the
EP
Union Internationale Contre le Cancer (UICC) tumor, node, metastasis (TNM) Classification, 7th edition. The staging was updated retrospectively to the 7th edition by using the
AC C
histopathological reports.
Lymph node assessment
We evaluated the clinical lymph node status with the planning-CT scan and assessed lymph nodes as pathologically altered, when central necrosis, extracapsular spread, and/or a shortaxis diameter of > 10 mm was observed. We identified 219 pathologically altered cervical lymph nodes within our study group of 100 patients. According to Vergeer et al., central necrosis was defined as a hypo-dense center or
ACCEPTED MANUSCRIPT an inhomogeneous aspect (Vergeer et al. 2006). Extranodal extension was assessed as unclearly differentiated borders of the nodes (Vergeer et al. 2006). Nodal volume was defined as the total volume of all neck nodes that were considered to be
RI PT
pathologically altered (Lodder et al. 2012).
Volumetric analysis with the means of semiautomatic segmentation
To measure the volume of the cervical lymph nodes, we used the open-source software
SC
ITK-SNAP (Penn Image Computing and Science Laboratory) (Yushkevich et al. 2006c). The CT DICOM datasets were imported into ITK-Snap and were demonstrated in sagittal,
M AN U
coronal, and axial slices. The neck lymph nodes were identified and delineated with the means of semiautomatic segmentation. Afterward, manual segmentation was performed to ensure correct segmentation. The volume of the cervical lymph nodes was computed automatically in cubic millimeters by the program.
TE D
A validated method to perform morphometry and volume analysis based upon CT imaging is tissue segmentation (Vallaeys et al. 2015). This technique is based upon manual, semiautomatic, and automatic methods (Dastidar et al. 1999). Commonly, semiautomatic
EP
segmentation is performed, as it combines the efficiency and repeatability of automatic segmentation and the correct delineation of manual segmentation (Dastidar et al. 1999).
AC C
The open-source medical imaging program ITK-SNAP (Penn Image Computing and Science Laboratory) is based upon geodesic active contour and region competition methods and thus offers manual and semiautomatic tools to analyze the volumes of anatomical regions of interest (Yushkevich et al. 2006c). The program was initially validated for volumetric and morphometric analysis of the caudate nucleus of the brain. Multiple consecutive studies confirmed these results for head and neck medicine (Safi et al. 2017a) (Kauke et al. 2017).
ACCEPTED MANUSCRIPT Statistical analysis Contingency tables and χ2 test were performed to analyze the associations between clinicopathological features and recurrence. A p value < 0.05 was considered to be significant. The dependent variable was the presence of recurrence, and the independent variables the
RI PT
clinicopathological parameters. Kaplan-Meier analysis was performed to estimate the events of interest for locoregional recurrence, and the log-rank test was used to determine
differences. In the multivariate analysis, the Cox proportional hazard model was used to
SC
estimate the impact of significant patient and tumor-related factors from the univariate
analysis on locoregional recurrence. Cutoff values were obtained from receiver operating
M AN U
characteristic curves and the Youden index (Youden index = sensitivity + specificity − 1) (Fluss et al. 2005). For internal validation of our values, we performed B = 150 bootstrap replications to investigate the importance of different nodal staging systems for head and neck cancer also (Yildiz et al. 2016). All statistical analyses were performed using SPSS Statistics
TE D
24.0 (IBM Corporation, Armonk, NY, USA).
EP
RESULTS
Patient characteristics and clinicopathologic data
AC C
At the time of diagnosis, patients had a mean age of 62.9 years and a median age of 63 years (standard deviation 13.69 years). Ages ranged from 30 to 92 years. Clinical characteristics are listed in Tables 1 and 2. The mean volume was 6.62 cm³ and the median volume 5.41 cm³ (standard deviation 3.09 cm³), with a range between 1.05 cm³ and 16.21 cm³.
Univariate and multivariate analysis Pathological N classification was significantly associated with locoregional recurrence (p = 0.001), as the more pathologically altered lymph nodes were detected, the higher the risk for
ACCEPTED MANUSCRIPT locoregional recurrence (Table 2). Central necrosis was also found to be a significant predictor variable for locoregional recurrence (p = 0.008; Table 1). Interestingly, the maximum diameter was not significantly associated with locoregional recurrence (p = 0.47). However, locoregional recurrence was significantly affected by lymph node volume (p <
RI PT
0.001; Table 1).
To evaluate the importance of the aforementioned significant parameters for locoregional recurrence, we performed a multivariate analysis. Here, N classification (p = 0.06) and
SC
volume (p < 0.001) were demonstrated as independent risk factors for locoregional recurrence.
M AN U
By means of the Youden index and receiver operating characteristic curve analysis, the cutoff point for lymph node volume was determined as 6.86 cm³. The results indicated that patients with lymph node volumes > 6.86 cm³ had a 20.9-times higher risk for locoregional recurrence
TE D
than patients with a lymph node volume below this cutoff value.
DISCUSSION
Preoperative staging of oral squamous cell carcinoma (OSCC) is based on clinicoradiological
EP
characteristics of the tumor, including the cervical lymph node status and assessment of distant metastasis sites (Kreppel et al. 2013). Although outstanding diagnostic and therapeutic
AC C
advances have been achieved in recent decades, the 5-year survival rate of patients with OSCC still remains below 50% (Vormittag et al. 2009). Therefore, identification of clinicoradiological parameters predicting accurately the prognosis and supporting the treatment decisions should be high priority. In daily clinical routine, one of the most important prognostic factors is the assessment of the cervical lymph node status by considering the TNM classification of the UICC/AJCC (Safi et al. 2017d). Computed tomography allows a precise appraisal of the anatomic extension and morphological assessment of cervical lymph nodes, as well as diagnosis of central necrosis and/or
ACCEPTED MANUSCRIPT extracapsular spread (Vallaeys et al. 2015). In addition to the location and the number of lymph nodes, their maximum diameter is regularly measured, as this parameter is assumed to be significantly associated with the biological aggressiveness of OSCC (Wittekind 2010). Yet, in 2012 Lodder et al. reported, in a systematic review, that volumetric analysis of
RI PT
pathologically altered cervical lymph nodes presents a superior prognostic parameter than the mere measurement of the maximum diameter (Lodder et al. 2012). Nevertheless, the
prognostic impact of the volume of lymph nodes has been scarcely addressed for patients with
SC
OSCC (Vergeer et al. 2006) (Tsou et al. 2006) (Ljumanovic et al. 2006). In addition, the few studies investigating the importance of the lymph node volume for patients with head and
M AN U
neck malignancies approximated the volume by multiplying the areas of each slice in the CT or by applying a cuboid or ellipsoid formula (Vergeer et al. 2006) (Tsou et al. 2006) (Ljumanovic et al. 2006). Therefore, published average lymph node volumes for patients with head and neck cancer have a wide range and differ between 7.8 cm³ and 56.9 cm³ (Lodder et
TE D
al. 2012) (Vergeer et al. 2006) (Tsou et al. 2006) (Ljumanovic et al. 2006). However, through the rapid development of digital diagnostic tools in the past decade, the technique of image segmentation has been widely refined and nowadays enables a meticulous and reliable
EP
volumetric size characterization (Yushkevich et al. 2006c, Yushkevich et al. 2016a). Furthermore, Ljumanovic et al. and Lodder et al. demonstrated that volumetric measurement
AC C
of neck lymph nodes with the aforementioned cuboid or ellipsoid formula frequently overestimates the real dimensions (Lodder et al. 2012). Hence, they called for standardization of volumetric analysis, and recommended an automatic image processing method to assess lymph node volumes (Lodder et al. 2012). Generally, the technique of segmentation fulfills these necessary criteria (Dastidar et al. 1999). It is based upon manual, semiautomatic, and fully automatic methods. Manual segmentation is performed by outlining the region of interest slice by slice on a three-dimensional image (Dastidar et al. 1999) (Vallaeys et al. 2015). This approach is, on one hand, very exact, but on the other hand, it is user dependent
ACCEPTED MANUSCRIPT and very time-consuming (Vallaeys et al. 2015). The automatic segmentation method is the fastest technique, but is also associated with the highest rates of inaccuracies (Vallaeys et al. 2015). Semiautomatic segmentation combines the efficiency and repeatability of automatic segmentation with the option of manually outlining the region of interest (Vallaeys et al.
RI PT
2015). Bearing these clear advantages of semiautomatic segmentation in mind, we chose the open-source imaging program ITK-SNAP, which has been validated for medical volume
SC
measurement in a number of studies (Vallaeys et al. 2015) (Yushkevich et al. 2006c).
The results from our univariate and multivariate analyses confirm the majority of published
M AN U
literature on the importance of lymph node volume for patients with head and neck malignancies, who highlighted the prognostic superiority of the neck lymph node volume towards the conventional N classification (Vergeer et al. 2006) (Tsou et al. 2006) (Ljumanovic et al. 2006). Yet, to the best of our knowledge, this work first demonstrates
TE D
lymph node volume as an independent risk factor for locoregional recurrence specifically for patients with OSCC (Table 2, Figure 1).
EP
To calculate the cutoff volume of pathologically altered lymph nodes, we performed a receiver operating characteristic curve analysis and considered the Youden index. The cutoff
AC C
value for patients with a significantly higher risk for locoregional recurrence was calculated as 6.86 cm³. In 2006, Ljumanovic et al. reported a cutoff value of 10.5 cm³, but considered not only patients with OSCC but generally with head and neck cancer (Ljumanovic et al. 2006). Another study from 2006, which was performed by Vergeer et al., also investigated the influence of the neck lymph node volume for patients with head and neck cancer, but published a notably higher volume, in fact, a benchmark value of 14 cm³ (Vergeer et al. 2006). We assume that this reported higher cutoff volume is based mainly on the inclusion criteria of their study, as they primarily considered patients, who were treated with
ACCEPTED MANUSCRIPT neoadjuvant radio- and/or chemotherapy and hence were at more advanced stages than our patients (Vergeer et al. 2006). In all, 46% of their study cohort had an N2b/N2c or N3 cervical lymph node status, whereas in our study N2c and N3 patients were excluded in order to minimize the number of confounding variables obtained by either different surgical neck
RI PT
dissection techniques or noncurative treatment protocols (Vergeer et al. 2006).
Our multivariate analysis indicated that patients with a cervical lymph node volume > 6.86 cm³ had a 20-fold higher risk of developing locoregional recurrences than patients with lymph
SC
node volumes < 6.86 cm³. Interestingly, assessment of the lymph node volume had a higher impact on locoregional recurrence than the conventional N classification and the maximum
M AN U
diameter of cervical lymph node metastasis. In recently published studies, a number of significant prognostic drawbacks of the conventional N classification were described (Safi et al. 2017b) (Safi et al. 2017c) (Safi et al. 2017d). Consequently, new concepts of nodal staging are needed and have been presented in the past years, such as consideration of the number of
TE D
dissected lymph nodes, lymph node ratio, or the log odds of positive lymph nodes (Safi et al. 2017b) (Safi et al. 2017c) (Safi et al. 2017d). Implementation of these parameters into nodal staging were shown to better differentiate the prognosis of patients with OSCC than the
EP
conventional N classification (Patel et al. 2013) (Divi et al. 2016) (Ebrahimi et al. 2014) (Gil et al. 2009) (Safi et al. 2017b) (Safi et al. 2017c) (Safi et al. 2017d). Taking these findings
AC C
into account, we assume that lymph node volume represents an additional promising new parameter, which represents the anatomic characteristics of a tumor more precisely than the diameter and therefore, now with the technique of semiautomatic segmentation, should be incorporated into the clinical staging of patients with OSCC.
CONCLUSION
ACCEPTED MANUSCRIPT Volumetric measurement serves as a better risk stratification tool than the conventional N classification for oral squamous cell carcinoma (OSCC). A lymph node volume of > 6.86 cm³ is associated with a 20-fold higher risk for locoregional failure. Therefore, a detailed assessment of the volume of cervical lymph nodes, based on semiautomatic segmentation, is
RI PT
of the utmost importance to improve therapeutic decision making and to assess prognosis, as it serves as an imaging biomarker for locoregional recurrence in patients with OSCC.
Nevertheless, further studies, especially those conducted in larger cohorts, are necessary to
SC
confirm our results and to improve the understanding of the prognostic influence of the
M AN U
volume of cervical lymph nodes.
Conflict of interest
AC C
EP
TE D
None
ACCEPTED MANUSCRIPT REFERENCES Dastidar P, T Heinonen, J Numminen, M Rautiainen and E Laasonen: Semi-automatic segmentation of computed tomographic images in volumetric estimation of nasal airway. Eur
RI PT
Arch Otorhinolaryngol 256 4: 192-198,1999.
Divi V, MM Chen, B Nussenbaum, KF Rhoads, DB Sirjani, FC Holsinger, JL Shah and W Hara: Lymph Node Count From Neck Dissection Predicts Mortality in Head and Neck
SC
Cancer. J Clin Oncol,2016.
M AN U
Ebrahimi A, JR Clark, M Amit, TC Yen, CT Liao, LP Kowalski, M Kreppel, CR Cernea, G Bachar, AB Villaret, D Fliss, E Fridman, KT Robbins, JP Shah, SG Patel and Z Gil: Minimum nodal yield in oral squamous cell carcinoma: defining the standard of care in a
TE D
multicenter international pooled validation study. Ann Surg Oncol 21 9: 3049-3055,2014.
Fluss R, D Faraggi and B Reiser: Estimation of the Youden index and its associated cutoff
EP
point. Biom J 47 4: 458-472,2005.
Gil Z, DL Carlson, JO Boyle, DH Kraus, JP Shah, AR Shaha, B Singh, RJ Wong and SG
AC C
Patel: Lymph node density is a significant predictor of outcome in patients with oral cancer. Cancer 115 24: 5700-5710,2009.
González García R, L Naval Gías, L Román Romero, J Sastre Pérez and FJ Rodríguez Campo: Local recurrences and second primary tumors from squamous cell carcinoma of the oral cavity: a retrospective analytic study of 500 patients. Head Neck 31 9: 1168-1180,2009.
ACCEPTED MANUSCRIPT Hadjiiski L, SK Mukherji, M Ibrahim, B Sahiner, SK Gujar, J Moyer and HP Chan: Head and neck cancers on CT: preliminary study of treatment response assessment based on computerized volume analysis. AJR Am J Roentgenol 194 4: 1083-1089,2010.
RI PT
Jemal A, R Siegel, E Ward, Y Hao, J Xu and MJ Thun: Cancer statistics, 2009. CA Cancer J Clin 59 4: 225-249,2009.
SC
Kauke M, AF Safi, M Kreppel, A Grandoch, HJ Nickenig, JE Zoller and T Dreiseidler: Size distribution and clinicoradiological signs of aggressiveness in odontogenic myxoma-three-
M AN U
dimensional analysis and systematic review. Dentomaxillofac Radiol 20170262,2017.
Kreppel M, T Dreiseidler, D Rothamel, HT Eich, U Drebber, JE Zoller and M Scheer: The role of clinical versus histopathological staging in patients with advanced oral squamous cell
TE D
carcinoma treated with neoadjuvant radiochemotherapy followed by radical surgery. J Craniomaxillofac Surg 41 1: 22-27,2013.
EP
Ljumanovic R, JA Langendijk, OS Hoekstra, CR Leemans and JA Castelijns: Distant metastases in head and neck carcinoma: identification of prognostic groups with MR imaging.
AC C
Eur J Radiol 60 1: 58-66,2006.
Lodder WL, FA Pameijer, CR Rasch, MW van den Brekel and AJ Balm: Prognostic significance of radiologically determined neck node volume in head and neck cancer: a systematic review. Oral Oncol 48 4: 298-302,2012.
Patel SG, M Amit, TC Yen, CT Liao, P Chaturvedi, JP Agarwal, LP Kowalski, A Ebrahimi, JR Clark, CR Cernea, SJ Brandao, M Kreppel, J Zoller, D Fliss, E Fridman, G Bachar, T
ACCEPTED MANUSCRIPT Shpitzer, VA Bolzoni, PR Patel, S Jonnalagadda, KT Robbins, JP Shah, Z Gil, H International Consortium for Outcome Research in and C Neck: Lymph node density in oral cavity cancer: results of the International Consortium for Outcomes Research. Br J Cancer 109 8: 2087-
RI PT
2095,2013.
Safi AF, A Grandoch, T Dreiseidler, HJ Nickenig, J Zoller and M Kreppel: Can cyst volume be used to stratify risk of complications following cyst defect reconstruction with iliac crest
SC
graft? J Craniomaxillofac Surg 45 8: 1165-1169,2017a.
M AN U
Safi AF, A Grandoch, HJ Nickenig, JE Zoller and M Kreppel: The importance of lymph node ratio for locoregional recurrence of squamous cell carcinoma of the tongue. J Craniomaxillofac Surg 45 7: 1058-1061,2017b.
TE D
Safi AF, M Kauke, A Grandoch, HJ Nickenig, U Drebber, J Zoller and M Kreppel: Clinicopathological parameters affecting nodal yields in patients with oral squamous cell
EP
carcinoma receiving selective neck dissection. J Craniomaxillofac Surg,2017c.
Safi AF, M Kauke, A Grandoch, HJ Nickenig, U Drebber, J Zoller and M Kreppel: The
AC C
importance of log odds of positive lymph nodes for locoregional recurrence in oral squamous cell carcinoma. Oral Oncol 72: 48-55,2017d.
Tsou YA, JH Hua, MH Lin and MH Tsai: Analysis of prognostic factors of chemoradiation therapy for advanced hypopharyngeal cancer─does tumor volume correlate with central necrosis and tumor pathology? ORL J Otorhinolaryngol Relat Spec 68 4: 206-212,2006.
ACCEPTED MANUSCRIPT Vallaeys K, A Kacem, H Legoux, M Le Tenier, C Hamitouche and R Arbab-Chirani: 3D dento-maxillary osteolytic lesion and active contour segmentation pilot study in CBCT: semiautomatic vs manual methods. Dentomaxillofac Radiol 44 8: 20150079,2015.
RI PT
Vergeer MR, P Doornaert, CR Leemans, J Buter, BJ Slotman and JA Langendijk: Control of nodal metastases in squamous cell head and neck cancer treated by radiation therapy or
SC
chemoradiation. Radiother Oncol 79 1: 39-44,2006.
Vormittag L, D Thurnher, S Geleff, J Pammer, G Heiduschka, M Brunner, M Grasl and BM
M AN U
Erovic: Co-expression of Bmi-1 and podoplanin predicts overall survival in patients with squamous cell carcinoma of the head and neck treated with radio(chemo)therapy. Int J Radiat Oncol Biol Phys 73 3: 913-918,2009.
TE D
Wittekind C: [TNM 2010. What's new?]. Pathologe 31 (Suppl 2): 153-160,2010.
Yildiz MM, I Petersen, E Eigendorff, P Schlattmann and O Guntinas-Lichius: Which is the
EP
most suitable lymph node predictor for overall survival after primary surgery of head and neck cancer: pN, the number or the ratio of positive lymph nodes, or log odds? J Cancer Res
AC C
Clin Oncol 142 4: 885-893,2016.
Yuan H, QY Ai, DL Kwong, DY Fong, AD King, V Vardhanabhuti, VH Lee and PL Khong: Cervical nodal volume for prognostication and risk stratification of patients with nasopharyngeal carcinoma, and implications on the TNM-staging system. Sci Rep 7 1: 10387,2017.
ACCEPTED MANUSCRIPT Yushkevich PA, Y Gao and G Gerig. ITK-SNAP: An interactive tool for semi-automatic segmentation of multi-modality biomedical images. Engineering in Medicine and Biology Society (EMBC), 2016 IEEE 38th Annual International Conference of the, IEEE, 2016a
RI PT
Yushkevich PA and G Gerig: ITK-SNAP: An intractive medical image segmentation tool to meet the need for expert-guided segmentation of complex medical images. IEEE Pulse 8 4:
SC
54-57,2017b.
Yushkevich PA, J Piven, HC Hazlett, RG Smith, S Ho, JC Gee and G Gerig: User-guided 3D
M AN U
active contour segmentation of anatomical structures: significantly improved efficiency and
AC C
EP
TE D
reliability. Neuroimage 31 3: 1116-1128,2006c.
ACCEPTED MANUSCRIPT Figure 1. Kaplan-Meier analysis of lymph node volume.
Figure 2. Kaplan-Meier analysis of N classification.
AC C
EP
TE D
M AN U
Figure 5. Segmentation of lymph node in coronal plane.
SC
Figure 4. Segmentation of lymph node in sagittal plane.
RI PT
Figure 3. Segmentation of lymph node in axial plane.
ACCEPTED MANUSCRIPT Table 1. Patient characteristics and univariate analysis Number of patients
p Value 0.014
61 39
17 3
50 50
13 7
RI PT
0.134
37 14 49
3 5 11
SC
0.001
0.52
16 4
M AN U
84 16
0.008
61 39
7 13
0.47
81 19
13 7
0.275
30 70
5 86 9
AC C
EP
Gender Male Female Age < Median > Median Pathologic N classification N1 N2a N2b Extracapsular spread No Yes Central necrosis No Yes Diameter <3 cm 3-6 cm Number of positive lymph nodes <2 >2 Histological grading Well Moderate Poor Nodal volume <6.86 cm³ >6.86 cm³
Number of recurrences
TE D
Variable
35 65
4 16 0.141 0 14 5 <0.001 4 16
ACCEPTED MANUSCRIPT Table 2. Multivariate analysis of significant parameters Standard error
p Value
95% Confidence interval
0.332
0.397
0.06
0.152-0.723
2.345
0.848
0.181
0.673-8.176
20.926
0.749
<0.001
4.824 - 90.774
AC C
EP
TE D
M AN U
SC
N classification (N1/N2a vs. N2b) Central necrosis (yes vs. no) Volume (<6.86 vs. >6.86)
Hazard ratio
RI PT
Variable
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
Figure 1: Kaplan-Meier analysis of lymph node volume
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
Figure 2: Kaplan-Meier analysis of N Classification
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
Figure 3: Segmentation of lymph node in axial plane
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
Figure 4: Segmentation of lymph node in coronal plane
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
Figure 5: Segmentation of lymph node in sagittal plane
S1010-5182(18)30101-X
DOI:
10.1016/j.jcms.2018.04.001
Reference:
YJCMS 2943
To appear in:
Journal of Cranio-Maxillo-Facial Surgery
Received Date: 17 December 2017 Revised Date:
13 March 2018
Accepted Date: 3 April 2018
Please cite this article as: Safi A-F, Kauke M, Jung H, Timmer M, Borggrefe J, Persigehl T, Nickenig H-J, Zinser M, Maintz D, Kreppel M, Zöller J, Does volumetric measurement of cervical lymph nodes serve as an imaging biomarker for locoregional recurrence of oral squamous cell carcinoma?, Journal of Cranio-Maxillofacial Surgery (2018), doi: 10.1016/j.jcms.2018.04.001. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
Does volumetric measurement of cervical lymph nodes serve as an imaging biomarker for locoregional recurrence of oral squamous cell carcinoma?
RI PT
Ali-Farid Safi (MD, DMD)1, Martin Kauke (MD)2, Hendrik Jung (DMD) 1, Marco Timmer (MD)2, Jan Borggrefe (MD) 3, Thorsten Persigehl (MD) 4, Hans-Joachim Nickenig (MD,
DMD)1, Max Zinser (MD, DMD) 1, David Maintz (MD) 4, Matthias Kreppel (MD, DMD)1,
Department for Oral and Craniomaxillofacial Plastic Surgery, University Hospital of
Cologne, Cologne, Germany
M AN U
1
SC
Joachim Zöller (MD, DMD)1
Department for General Neurosurgery, University Hospital of Cologne, Cologne, Germany
3
Department of Neuroradiology, University Hospital Cologne, Cologne, Germany
4
Department of Radiology, University Hospital Cologne, Cologne, Germany
Corresponding author
TE D
2
EP
Dr. med. Dr. med. dent. Ali-Farid Safi
Department for Oral and Craniomaxillofacial Plastic Surgery
AC C
University of Cologne Kerpener Straße 62 50931 Cologne Germany
e-mail: [email protected] Phone: +49 221 478 96594 Fax: +49 221 478 7360
ACCEPTED MANUSCRIPT Summary
INTRODUCTION Oral squamous cell carcinoma (OSCC) is the sixth most common malignancy worldwide
RI PT
(Jemal et al. 2009). It occurs at an annual incidence of approximately 263,000, with a
mortality rate of approximately 128,000 per year, and is accompanied by a 5-year survival rate of less than 50% (Jemal et al. 2009) (Vormittag et al. 2009). Despite significant
SC
diagnostic and therapeutic advances, the prognosis of patients with OSCC has not improved in the past three decades (Jemal et al. 2009). A major prognostic factor is locoregional
M AN U
relapse, as its diagnosis worsens survival to less than 30% (González García et al. 2009). Hence, it is of the utmost importance to identify parameters that can specifically predict locoregional recurrence and thus allow timely, adequate diagnosis and accurate therapeutic regimens (Patel et al. 2013). One such parameter is cervical lymph node status, as it has major
TE D
implications for treatment decision making and assessment of prognosis in daily clinical routine (Safi et al. 2017c). Accordingly, a preoperative clinical staging is necessary to sufficiently evaluate neck lymph node status (Kreppel et al. 2013). Computed tomography
EP
(CT) plays a pivotal role in the perioperative identification of lymph node metastasis and enables an exact nodal staging based on the TNM Classification of the Union Internationale
AC C
Contre le Cancer (UICC)/American Joint Committee on Cancer (AJCC) (Kreppel et al. 2013). This classification system considers the number and location of pathologically altered lymph nodes and their maximum diameter (Wittekind 2010). It differentiates between lymph nodes that are < 3 cm, between 3 and 6 cm, and > 6 cm (Wittekind 2010). Multiple studies have found these cutoff sizes to be significantly correlated with biological aggressiveness, the tendency to further metastasize, and the potential to reoccur (Wittekind 2010). Nonetheless, numerous investigators have demonstrated that these benchmark diameters of cervical lymph nodes are not able to sufficiently stratify the risk of patients with positive lymph nodes
ACCEPTED MANUSCRIPT (Lodder et al. 2012) (Ljumanovic et al. 2006) (Vergeer et al. 2006). Therefore, to overcome the shortcomings of the TNM classification, modifications of the nodal classification system are required. One such significant step forward might be the implementation of the volume of lymph nodes instead of the diameter, as recent studies have reported very promising results
RI PT
with the prognostic superiority of lymph node volumes (Lodder et al. 2012) (Yuan et al.
2017). However, two major problems need to be addressed: on one hand, studies considering the neck lymph node volume as a prognostic parameter specifically for patients with OSCC
SC
are rare; on the other hand, volumetric analysis frequently has been performed by multiplying the areas in each slice of a CT or by approximation with a cuboid or ellipsoid formula instead
M AN U
of automatic image processing, although this technique allows a relatively time-sparing and precise measurement of the volume (Lodder et al. 2012) (Yushkevich and Gerig 2017b) (Hadjiiski et al. 2010). To the best of our knowledge, data on the importance of neck lymph node volume, obtained by semiautomatic segmentation of CT images, are not available for
TE D
locoregional recurrence in patients with OSCC. Hence, we aimed to investigate whether lymph node volume would serve as an imaging biomarker that would allow a better risk
EP
stratification of locoregional failure than the conventional N Classification.
MATERIALS AND METHODS
AC C
Patients and data collection Our retrospective study followed the guidelines of the Declaration of Helsinki and consisted of 100 patients who were diagnosed and treated between 2006 and 2014 at our Department for Oral and Craniomaxillofacial Plastic Surgery. Inclusion criteria were patients with treatment-naive oral squamous cell carcinoma and primarily curative intended surgery with negative resection margins, in whom preoperative CT of the head and neck region was performed. Comprehensive neck dissection (level I to V) due to ipsilateral lymph node metastasis was chosen as an inclusion criterion. Exclusion criteria were neoadjuvant
ACCEPTED MANUSCRIPT chemoradiotherapy, T4b classification, perioperative death, unresectable disease, synchronous malignancy, follow-up < 3 months, and inadequate information to correctly determine clinicopathological characteristics. Surgery in combination with postoperative radiotherapy
days per week for a total dose of 60 to 65 Gy.
RI PT
was chosen for locally advanced disease. Radiotherapy included daily doses of 1.8 to 2.0 Gy 5
In accordance with existing literature, recurrence was defined as a tumor of similar histology appearing after 6 weeks of treatment and within the first 3 years after therapy of the primary
SC
tumor (González García et al. 2009). Regional recurrences were defined as recurrences
within the lymph neck nodes, and distant recurrences as metastasis outside the head and neck
M AN U
region.
Due to the retrospective nature of this study, it was granted an exemption in writing by the University Hospital institutional review board.
Clinicopathologic data were collected from medical records as well as from pathology and
TE D
surgery reports. Parameters were carefully reviewed and included gender, age, clinical N classification, extracapsular spread, central necrosis, diameter, grading, number of positive lymph nodes, and nodal volume. All cases were staged histopathologically according to the
EP
Union Internationale Contre le Cancer (UICC) tumor, node, metastasis (TNM) Classification, 7th edition. The staging was updated retrospectively to the 7th edition by using the
AC C
histopathological reports.
Lymph node assessment
We evaluated the clinical lymph node status with the planning-CT scan and assessed lymph nodes as pathologically altered, when central necrosis, extracapsular spread, and/or a shortaxis diameter of > 10 mm was observed. We identified 219 pathologically altered cervical lymph nodes within our study group of 100 patients. According to Vergeer et al., central necrosis was defined as a hypo-dense center or
ACCEPTED MANUSCRIPT an inhomogeneous aspect (Vergeer et al. 2006). Extranodal extension was assessed as unclearly differentiated borders of the nodes (Vergeer et al. 2006). Nodal volume was defined as the total volume of all neck nodes that were considered to be
RI PT
pathologically altered (Lodder et al. 2012).
Volumetric analysis with the means of semiautomatic segmentation
To measure the volume of the cervical lymph nodes, we used the open-source software
SC
ITK-SNAP (Penn Image Computing and Science Laboratory) (Yushkevich et al. 2006c). The CT DICOM datasets were imported into ITK-Snap and were demonstrated in sagittal,
M AN U
coronal, and axial slices. The neck lymph nodes were identified and delineated with the means of semiautomatic segmentation. Afterward, manual segmentation was performed to ensure correct segmentation. The volume of the cervical lymph nodes was computed automatically in cubic millimeters by the program.
TE D
A validated method to perform morphometry and volume analysis based upon CT imaging is tissue segmentation (Vallaeys et al. 2015). This technique is based upon manual, semiautomatic, and automatic methods (Dastidar et al. 1999). Commonly, semiautomatic
EP
segmentation is performed, as it combines the efficiency and repeatability of automatic segmentation and the correct delineation of manual segmentation (Dastidar et al. 1999).
AC C
The open-source medical imaging program ITK-SNAP (Penn Image Computing and Science Laboratory) is based upon geodesic active contour and region competition methods and thus offers manual and semiautomatic tools to analyze the volumes of anatomical regions of interest (Yushkevich et al. 2006c). The program was initially validated for volumetric and morphometric analysis of the caudate nucleus of the brain. Multiple consecutive studies confirmed these results for head and neck medicine (Safi et al. 2017a) (Kauke et al. 2017).
ACCEPTED MANUSCRIPT Statistical analysis Contingency tables and χ2 test were performed to analyze the associations between clinicopathological features and recurrence. A p value < 0.05 was considered to be significant. The dependent variable was the presence of recurrence, and the independent variables the
RI PT
clinicopathological parameters. Kaplan-Meier analysis was performed to estimate the events of interest for locoregional recurrence, and the log-rank test was used to determine
differences. In the multivariate analysis, the Cox proportional hazard model was used to
SC
estimate the impact of significant patient and tumor-related factors from the univariate
analysis on locoregional recurrence. Cutoff values were obtained from receiver operating
M AN U
characteristic curves and the Youden index (Youden index = sensitivity + specificity − 1) (Fluss et al. 2005). For internal validation of our values, we performed B = 150 bootstrap replications to investigate the importance of different nodal staging systems for head and neck cancer also (Yildiz et al. 2016). All statistical analyses were performed using SPSS Statistics
TE D
24.0 (IBM Corporation, Armonk, NY, USA).
EP
RESULTS
Patient characteristics and clinicopathologic data
AC C
At the time of diagnosis, patients had a mean age of 62.9 years and a median age of 63 years (standard deviation 13.69 years). Ages ranged from 30 to 92 years. Clinical characteristics are listed in Tables 1 and 2. The mean volume was 6.62 cm³ and the median volume 5.41 cm³ (standard deviation 3.09 cm³), with a range between 1.05 cm³ and 16.21 cm³.
Univariate and multivariate analysis Pathological N classification was significantly associated with locoregional recurrence (p = 0.001), as the more pathologically altered lymph nodes were detected, the higher the risk for
ACCEPTED MANUSCRIPT locoregional recurrence (Table 2). Central necrosis was also found to be a significant predictor variable for locoregional recurrence (p = 0.008; Table 1). Interestingly, the maximum diameter was not significantly associated with locoregional recurrence (p = 0.47). However, locoregional recurrence was significantly affected by lymph node volume (p <
RI PT
0.001; Table 1).
To evaluate the importance of the aforementioned significant parameters for locoregional recurrence, we performed a multivariate analysis. Here, N classification (p = 0.06) and
SC
volume (p < 0.001) were demonstrated as independent risk factors for locoregional recurrence.
M AN U
By means of the Youden index and receiver operating characteristic curve analysis, the cutoff point for lymph node volume was determined as 6.86 cm³. The results indicated that patients with lymph node volumes > 6.86 cm³ had a 20.9-times higher risk for locoregional recurrence
TE D
than patients with a lymph node volume below this cutoff value.
DISCUSSION
Preoperative staging of oral squamous cell carcinoma (OSCC) is based on clinicoradiological
EP
characteristics of the tumor, including the cervical lymph node status and assessment of distant metastasis sites (Kreppel et al. 2013). Although outstanding diagnostic and therapeutic
AC C
advances have been achieved in recent decades, the 5-year survival rate of patients with OSCC still remains below 50% (Vormittag et al. 2009). Therefore, identification of clinicoradiological parameters predicting accurately the prognosis and supporting the treatment decisions should be high priority. In daily clinical routine, one of the most important prognostic factors is the assessment of the cervical lymph node status by considering the TNM classification of the UICC/AJCC (Safi et al. 2017d). Computed tomography allows a precise appraisal of the anatomic extension and morphological assessment of cervical lymph nodes, as well as diagnosis of central necrosis and/or
ACCEPTED MANUSCRIPT extracapsular spread (Vallaeys et al. 2015). In addition to the location and the number of lymph nodes, their maximum diameter is regularly measured, as this parameter is assumed to be significantly associated with the biological aggressiveness of OSCC (Wittekind 2010). Yet, in 2012 Lodder et al. reported, in a systematic review, that volumetric analysis of
RI PT
pathologically altered cervical lymph nodes presents a superior prognostic parameter than the mere measurement of the maximum diameter (Lodder et al. 2012). Nevertheless, the
prognostic impact of the volume of lymph nodes has been scarcely addressed for patients with
SC
OSCC (Vergeer et al. 2006) (Tsou et al. 2006) (Ljumanovic et al. 2006). In addition, the few studies investigating the importance of the lymph node volume for patients with head and
M AN U
neck malignancies approximated the volume by multiplying the areas of each slice in the CT or by applying a cuboid or ellipsoid formula (Vergeer et al. 2006) (Tsou et al. 2006) (Ljumanovic et al. 2006). Therefore, published average lymph node volumes for patients with head and neck cancer have a wide range and differ between 7.8 cm³ and 56.9 cm³ (Lodder et
TE D
al. 2012) (Vergeer et al. 2006) (Tsou et al. 2006) (Ljumanovic et al. 2006). However, through the rapid development of digital diagnostic tools in the past decade, the technique of image segmentation has been widely refined and nowadays enables a meticulous and reliable
EP
volumetric size characterization (Yushkevich et al. 2006c, Yushkevich et al. 2016a). Furthermore, Ljumanovic et al. and Lodder et al. demonstrated that volumetric measurement
AC C
of neck lymph nodes with the aforementioned cuboid or ellipsoid formula frequently overestimates the real dimensions (Lodder et al. 2012). Hence, they called for standardization of volumetric analysis, and recommended an automatic image processing method to assess lymph node volumes (Lodder et al. 2012). Generally, the technique of segmentation fulfills these necessary criteria (Dastidar et al. 1999). It is based upon manual, semiautomatic, and fully automatic methods. Manual segmentation is performed by outlining the region of interest slice by slice on a three-dimensional image (Dastidar et al. 1999) (Vallaeys et al. 2015). This approach is, on one hand, very exact, but on the other hand, it is user dependent
ACCEPTED MANUSCRIPT and very time-consuming (Vallaeys et al. 2015). The automatic segmentation method is the fastest technique, but is also associated with the highest rates of inaccuracies (Vallaeys et al. 2015). Semiautomatic segmentation combines the efficiency and repeatability of automatic segmentation with the option of manually outlining the region of interest (Vallaeys et al.
RI PT
2015). Bearing these clear advantages of semiautomatic segmentation in mind, we chose the open-source imaging program ITK-SNAP, which has been validated for medical volume
SC
measurement in a number of studies (Vallaeys et al. 2015) (Yushkevich et al. 2006c).
The results from our univariate and multivariate analyses confirm the majority of published
M AN U
literature on the importance of lymph node volume for patients with head and neck malignancies, who highlighted the prognostic superiority of the neck lymph node volume towards the conventional N classification (Vergeer et al. 2006) (Tsou et al. 2006) (Ljumanovic et al. 2006). Yet, to the best of our knowledge, this work first demonstrates
TE D
lymph node volume as an independent risk factor for locoregional recurrence specifically for patients with OSCC (Table 2, Figure 1).
EP
To calculate the cutoff volume of pathologically altered lymph nodes, we performed a receiver operating characteristic curve analysis and considered the Youden index. The cutoff
AC C
value for patients with a significantly higher risk for locoregional recurrence was calculated as 6.86 cm³. In 2006, Ljumanovic et al. reported a cutoff value of 10.5 cm³, but considered not only patients with OSCC but generally with head and neck cancer (Ljumanovic et al. 2006). Another study from 2006, which was performed by Vergeer et al., also investigated the influence of the neck lymph node volume for patients with head and neck cancer, but published a notably higher volume, in fact, a benchmark value of 14 cm³ (Vergeer et al. 2006). We assume that this reported higher cutoff volume is based mainly on the inclusion criteria of their study, as they primarily considered patients, who were treated with
ACCEPTED MANUSCRIPT neoadjuvant radio- and/or chemotherapy and hence were at more advanced stages than our patients (Vergeer et al. 2006). In all, 46% of their study cohort had an N2b/N2c or N3 cervical lymph node status, whereas in our study N2c and N3 patients were excluded in order to minimize the number of confounding variables obtained by either different surgical neck
RI PT
dissection techniques or noncurative treatment protocols (Vergeer et al. 2006).
Our multivariate analysis indicated that patients with a cervical lymph node volume > 6.86 cm³ had a 20-fold higher risk of developing locoregional recurrences than patients with lymph
SC
node volumes < 6.86 cm³. Interestingly, assessment of the lymph node volume had a higher impact on locoregional recurrence than the conventional N classification and the maximum
M AN U
diameter of cervical lymph node metastasis. In recently published studies, a number of significant prognostic drawbacks of the conventional N classification were described (Safi et al. 2017b) (Safi et al. 2017c) (Safi et al. 2017d). Consequently, new concepts of nodal staging are needed and have been presented in the past years, such as consideration of the number of
TE D
dissected lymph nodes, lymph node ratio, or the log odds of positive lymph nodes (Safi et al. 2017b) (Safi et al. 2017c) (Safi et al. 2017d). Implementation of these parameters into nodal staging were shown to better differentiate the prognosis of patients with OSCC than the
EP
conventional N classification (Patel et al. 2013) (Divi et al. 2016) (Ebrahimi et al. 2014) (Gil et al. 2009) (Safi et al. 2017b) (Safi et al. 2017c) (Safi et al. 2017d). Taking these findings
AC C
into account, we assume that lymph node volume represents an additional promising new parameter, which represents the anatomic characteristics of a tumor more precisely than the diameter and therefore, now with the technique of semiautomatic segmentation, should be incorporated into the clinical staging of patients with OSCC.
CONCLUSION
ACCEPTED MANUSCRIPT Volumetric measurement serves as a better risk stratification tool than the conventional N classification for oral squamous cell carcinoma (OSCC). A lymph node volume of > 6.86 cm³ is associated with a 20-fold higher risk for locoregional failure. Therefore, a detailed assessment of the volume of cervical lymph nodes, based on semiautomatic segmentation, is
RI PT
of the utmost importance to improve therapeutic decision making and to assess prognosis, as it serves as an imaging biomarker for locoregional recurrence in patients with OSCC.
Nevertheless, further studies, especially those conducted in larger cohorts, are necessary to
SC
confirm our results and to improve the understanding of the prognostic influence of the
M AN U
volume of cervical lymph nodes.
Conflict of interest
AC C
EP
TE D
None
ACCEPTED MANUSCRIPT REFERENCES Dastidar P, T Heinonen, J Numminen, M Rautiainen and E Laasonen: Semi-automatic segmentation of computed tomographic images in volumetric estimation of nasal airway. Eur
RI PT
Arch Otorhinolaryngol 256 4: 192-198,1999.
Divi V, MM Chen, B Nussenbaum, KF Rhoads, DB Sirjani, FC Holsinger, JL Shah and W Hara: Lymph Node Count From Neck Dissection Predicts Mortality in Head and Neck
SC
Cancer. J Clin Oncol,2016.
M AN U
Ebrahimi A, JR Clark, M Amit, TC Yen, CT Liao, LP Kowalski, M Kreppel, CR Cernea, G Bachar, AB Villaret, D Fliss, E Fridman, KT Robbins, JP Shah, SG Patel and Z Gil: Minimum nodal yield in oral squamous cell carcinoma: defining the standard of care in a
TE D
multicenter international pooled validation study. Ann Surg Oncol 21 9: 3049-3055,2014.
Fluss R, D Faraggi and B Reiser: Estimation of the Youden index and its associated cutoff
EP
point. Biom J 47 4: 458-472,2005.
Gil Z, DL Carlson, JO Boyle, DH Kraus, JP Shah, AR Shaha, B Singh, RJ Wong and SG
AC C
Patel: Lymph node density is a significant predictor of outcome in patients with oral cancer. Cancer 115 24: 5700-5710,2009.
González García R, L Naval Gías, L Román Romero, J Sastre Pérez and FJ Rodríguez Campo: Local recurrences and second primary tumors from squamous cell carcinoma of the oral cavity: a retrospective analytic study of 500 patients. Head Neck 31 9: 1168-1180,2009.
ACCEPTED MANUSCRIPT Hadjiiski L, SK Mukherji, M Ibrahim, B Sahiner, SK Gujar, J Moyer and HP Chan: Head and neck cancers on CT: preliminary study of treatment response assessment based on computerized volume analysis. AJR Am J Roentgenol 194 4: 1083-1089,2010.
RI PT
Jemal A, R Siegel, E Ward, Y Hao, J Xu and MJ Thun: Cancer statistics, 2009. CA Cancer J Clin 59 4: 225-249,2009.
SC
Kauke M, AF Safi, M Kreppel, A Grandoch, HJ Nickenig, JE Zoller and T Dreiseidler: Size distribution and clinicoradiological signs of aggressiveness in odontogenic myxoma-three-
M AN U
dimensional analysis and systematic review. Dentomaxillofac Radiol 20170262,2017.
Kreppel M, T Dreiseidler, D Rothamel, HT Eich, U Drebber, JE Zoller and M Scheer: The role of clinical versus histopathological staging in patients with advanced oral squamous cell
TE D
carcinoma treated with neoadjuvant radiochemotherapy followed by radical surgery. J Craniomaxillofac Surg 41 1: 22-27,2013.
EP
Ljumanovic R, JA Langendijk, OS Hoekstra, CR Leemans and JA Castelijns: Distant metastases in head and neck carcinoma: identification of prognostic groups with MR imaging.
AC C
Eur J Radiol 60 1: 58-66,2006.
Lodder WL, FA Pameijer, CR Rasch, MW van den Brekel and AJ Balm: Prognostic significance of radiologically determined neck node volume in head and neck cancer: a systematic review. Oral Oncol 48 4: 298-302,2012.
Patel SG, M Amit, TC Yen, CT Liao, P Chaturvedi, JP Agarwal, LP Kowalski, A Ebrahimi, JR Clark, CR Cernea, SJ Brandao, M Kreppel, J Zoller, D Fliss, E Fridman, G Bachar, T
ACCEPTED MANUSCRIPT Shpitzer, VA Bolzoni, PR Patel, S Jonnalagadda, KT Robbins, JP Shah, Z Gil, H International Consortium for Outcome Research in and C Neck: Lymph node density in oral cavity cancer: results of the International Consortium for Outcomes Research. Br J Cancer 109 8: 2087-
RI PT
2095,2013.
Safi AF, A Grandoch, T Dreiseidler, HJ Nickenig, J Zoller and M Kreppel: Can cyst volume be used to stratify risk of complications following cyst defect reconstruction with iliac crest
SC
graft? J Craniomaxillofac Surg 45 8: 1165-1169,2017a.
M AN U
Safi AF, A Grandoch, HJ Nickenig, JE Zoller and M Kreppel: The importance of lymph node ratio for locoregional recurrence of squamous cell carcinoma of the tongue. J Craniomaxillofac Surg 45 7: 1058-1061,2017b.
TE D
Safi AF, M Kauke, A Grandoch, HJ Nickenig, U Drebber, J Zoller and M Kreppel: Clinicopathological parameters affecting nodal yields in patients with oral squamous cell
EP
carcinoma receiving selective neck dissection. J Craniomaxillofac Surg,2017c.
Safi AF, M Kauke, A Grandoch, HJ Nickenig, U Drebber, J Zoller and M Kreppel: The
AC C
importance of log odds of positive lymph nodes for locoregional recurrence in oral squamous cell carcinoma. Oral Oncol 72: 48-55,2017d.
Tsou YA, JH Hua, MH Lin and MH Tsai: Analysis of prognostic factors of chemoradiation therapy for advanced hypopharyngeal cancer─does tumor volume correlate with central necrosis and tumor pathology? ORL J Otorhinolaryngol Relat Spec 68 4: 206-212,2006.
ACCEPTED MANUSCRIPT Vallaeys K, A Kacem, H Legoux, M Le Tenier, C Hamitouche and R Arbab-Chirani: 3D dento-maxillary osteolytic lesion and active contour segmentation pilot study in CBCT: semiautomatic vs manual methods. Dentomaxillofac Radiol 44 8: 20150079,2015.
RI PT
Vergeer MR, P Doornaert, CR Leemans, J Buter, BJ Slotman and JA Langendijk: Control of nodal metastases in squamous cell head and neck cancer treated by radiation therapy or
SC
chemoradiation. Radiother Oncol 79 1: 39-44,2006.
Vormittag L, D Thurnher, S Geleff, J Pammer, G Heiduschka, M Brunner, M Grasl and BM
M AN U
Erovic: Co-expression of Bmi-1 and podoplanin predicts overall survival in patients with squamous cell carcinoma of the head and neck treated with radio(chemo)therapy. Int J Radiat Oncol Biol Phys 73 3: 913-918,2009.
TE D
Wittekind C: [TNM 2010. What's new?]. Pathologe 31 (Suppl 2): 153-160,2010.
Yildiz MM, I Petersen, E Eigendorff, P Schlattmann and O Guntinas-Lichius: Which is the
EP
most suitable lymph node predictor for overall survival after primary surgery of head and neck cancer: pN, the number or the ratio of positive lymph nodes, or log odds? J Cancer Res
AC C
Clin Oncol 142 4: 885-893,2016.
Yuan H, QY Ai, DL Kwong, DY Fong, AD King, V Vardhanabhuti, VH Lee and PL Khong: Cervical nodal volume for prognostication and risk stratification of patients with nasopharyngeal carcinoma, and implications on the TNM-staging system. Sci Rep 7 1: 10387,2017.
ACCEPTED MANUSCRIPT Yushkevich PA, Y Gao and G Gerig. ITK-SNAP: An interactive tool for semi-automatic segmentation of multi-modality biomedical images. Engineering in Medicine and Biology Society (EMBC), 2016 IEEE 38th Annual International Conference of the, IEEE, 2016a
RI PT
Yushkevich PA and G Gerig: ITK-SNAP: An intractive medical image segmentation tool to meet the need for expert-guided segmentation of complex medical images. IEEE Pulse 8 4:
SC
54-57,2017b.
Yushkevich PA, J Piven, HC Hazlett, RG Smith, S Ho, JC Gee and G Gerig: User-guided 3D
M AN U
active contour segmentation of anatomical structures: significantly improved efficiency and
AC C
EP
TE D
reliability. Neuroimage 31 3: 1116-1128,2006c.
ACCEPTED MANUSCRIPT Figure 1. Kaplan-Meier analysis of lymph node volume.
Figure 2. Kaplan-Meier analysis of N classification.
AC C
EP
TE D
M AN U
Figure 5. Segmentation of lymph node in coronal plane.
SC
Figure 4. Segmentation of lymph node in sagittal plane.
RI PT
Figure 3. Segmentation of lymph node in axial plane.
ACCEPTED MANUSCRIPT Table 1. Patient characteristics and univariate analysis Number of patients
p Value 0.014
61 39
17 3
50 50
13 7
RI PT
0.134
37 14 49
3 5 11
SC
0.001
0.52
16 4
M AN U
84 16
0.008
61 39
7 13
0.47
81 19
13 7
0.275
30 70
5 86 9
AC C
EP
Gender Male Female Age < Median > Median Pathologic N classification N1 N2a N2b Extracapsular spread No Yes Central necrosis No Yes Diameter <3 cm 3-6 cm Number of positive lymph nodes <2 >2 Histological grading Well Moderate Poor Nodal volume <6.86 cm³ >6.86 cm³
Number of recurrences
TE D
Variable
35 65
4 16 0.141 0 14 5 <0.001 4 16
ACCEPTED MANUSCRIPT Table 2. Multivariate analysis of significant parameters Standard error
p Value
95% Confidence interval
0.332
0.397
0.06
0.152-0.723
2.345
0.848
0.181
0.673-8.176
20.926
0.749
<0.001
4.824 - 90.774
AC C
EP
TE D
M AN U
SC
N classification (N1/N2a vs. N2b) Central necrosis (yes vs. no) Volume (<6.86 vs. >6.86)
Hazard ratio
RI PT
Variable
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
Figure 1: Kaplan-Meier analysis of lymph node volume
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
Figure 2: Kaplan-Meier analysis of N Classification
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
Figure 3: Segmentation of lymph node in axial plane
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
Figure 4: Segmentation of lymph node in coronal plane
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
Figure 5: Segmentation of lymph node in sagittal plane