Difference between HPV positive and negative non-oropharyngeal cancer; texture analysis features on CT Akifumi Fujita, MD 1,4, Karen Buch, MD 1, Baojun Li, PhD 1, Yusuke Kawashima, DDS 1,5, Muhammad M. Qureshi, MBBS 1,3 Osamu Sakai, MD, PhD 1,2,3 Departments of 1 Radiology, 2 Otolaryngology – Head and Neck Surgery, and 3 Radiation Oncology Boston Medical Center, Boston University School of Medicine 4 Departments of Radiology, Jichi Medical University School of Medicine 5 Departments of Radiology, Nihon University School of Dentistry at Matsudo

Background Although the prevalence of humanpapilloma virus (HPV) infection is not as high as oropharyngeal cancer (OPC), non-oropharyngeal cancer (non-OPC) has reported association with HPV infection in % (6-9).6-9 –non-OPC; oral cavity (tongue, floor of mouth, and buccal mucosa), larynx, and hypopharynx Several articles shows that HPV positive (HPV+) non- OPC also tends to show better clinical outcomes than HPV negative (HPV-) non-OPC (2, 9).29 However, the influence on treatment options and impact on prognosis of HPV is not established among non-OPC patients (7, 8, 10).7810

Background Texture analysis is a quantitative means for extracting image features for comparative analysis –Post-processing step –Evaluated in prior studies: liver, cartilage, brain, myocardium Texture features –Histogram features: spatially invariant –Gray level co-occurrence matrix (GLCM) features: highly spatially dependent, # times a given gray tone i is adjacent to gray tone j –Gray level run-length matrix (GLRL) features: spatially dependent, # pixel line segments in a given run-length and tone –Gray level gradient matrix (GLGM) features: mathematical summary of gradient values of pixels in the ROI

Purpose We hypothesized that there may also be underlying morphologic difference in the texture of non-OPC between HPV+ and HPV- patients. The purpose of this study is to investigate and identify if there is any specific texture parameter that may distinguish between HPV+ and HPV- patients in non-OPC.

Materials & Methods –110 patients with non-OPC SCC and known HPV status who had contrast enhanced CT (CECT) for initial staging between December 2009-August 2014 –CECT examinations were performed either independently or combined with FDG-PET examination, acquired by 64- or 16-detector row CT scanners Lightspeed VCT Discovery STE-16 PET/CT (GE Healthcare, Milwaukee, Wisconsin) –Exclusion criteria: Severely motion limited studies Significant artifact generated from dental hardware patients with very small primary tumors (less than 5 mm)

Materials & Methods Electronic Medical Record Review: Age and gender HPV status Tumor site Primary Tumor Segmentation and Texture Analysis –Segmentation was performed on a dedicated AW workstation (GE Healthcare, Milwaukee, WI) with a semi- automated graphical-user-interface (GUI) –In-house developed, MATLAB-based texture analysis program was employed to extract 42 texture features from each segmented volume Statistical Analysis –t-test to compare differences in texture parameters between HPV+ and HPV- non-OPC SCC

Materials & Methods 47 yo male with right lateral tongue Ca HPV + 63 yo male with left lateral tongue Ca HPV -

Results Patient characteristics –64 patients were excluded fro the analysis, and ultimately 46 CECT exams and corresponding medical records were reviewed –31 males, 15 females –Age range: 39 to 86 years (59.6±7.9) HPV Status –10 patients with HPV+ non-OPC 5 oral cavity, 5 larynx –36 patients with HPV- non-OPC 19 oral cavity, 12 larynx, 5 hypopharynx

Table 1: Texture parameters differentiating between HPV+ and HPV- non-OPC Texture Feature HPV+ (N=10) HPV- (N=36) nMeanSDnMeanSDP-valueQ-value Histogram Mean Median STD Entropy nd STD Range Geometric mean Harmonic mean IQR th moment e101.48e e101.28e Test STD STD GLCM Entropy Contrast < Correlation Energy Homogeneity GLRL SRE LRE GLN RLN RP Continues to the next slide Abbreviations: HPV= human papillomavirus; HPV+= HPV positive; HPV-= HPV negative; non-OPC= non-oropharyngeal cancer; N= number of patients; n= number of measurements; SD,STD= standard deviation, IQR= inter quartile range; GLCM = gray level co- occurrence matrix, GLRL = gray level run length, SRE= short run emphasis; LRE= long run emphasis; GLN= gray-level non- uniformity; RLN= run-length non-uniformity; RP= run percentage;

Texture Feature HPV+ (N=10) HPV– (N=36) nMeanSDnMeanSDP-valueQ-value GLRL, continued. LGRE HGRE SRLGE SRHGE LRLGE LRHGE Law's features L e52.99e e103.74e L e44.59e e48.33e L e41.42e e42.21e L e58.08e e51.20e L e41.10e e41.99e L L e37.39e e41.15e L e35.10e e L e43.54e e45.10e GLGM MGR VGR Skewness Kurtosis Abbreviations: HPV= human papillomavirus; HPV+= HPV positive; HPV-= HPV negative; N= number of patients; n= number of measurements; SD= standard deviation; GLRL = gray level run length; GRE= low gray-level run emphasis; HGRE= high gray-level run emphasis; SRLGE= short run low gray-level emphasis; SRHGE= short run high gray-level emphasis; LRLGE= long run low gray-level emphasis; LRHGE= long run high gray-level emphasis; GLGM= gray level gradient matrix; MGR= mean gradient; VGR= variance of gradients

Results Texture features of all non-OPCs A total of 16 texture features; –5 histogram (Mean, Median, Entropy, Geometric mean, IQR) –3 GLCM (Contrast, Correlation, Energy) –1 GLRL (LRHGE) –2 GLGM (skewness, kurtosis) –5 Law’s features (L2, L5, L6, L7, L8) Significant difference between HPV+ and HPV- (P ≤ 0.05).

Results Texture features of Oral Cavity Cancer A total of 10 texture features; –2 histogram (Median; entropy) –4 GLCM (entropy; correlation; energy; homogeneity) –4 GLRL (RP; LGRE; HGRE; SRLGE) Texture features of Laryngeal Cancer A total of 24 texture features; –1 histogram (IQR) –3 GLCM (contrast; correlation; energy) –9 GLRL (SRE; LRE; GLN; RLN; RP; HGRE; SRHGE; LRLGE; LRHGE) –9 Law’s (L1; L2; L3; L4; L5; L6; L7; L8; L9) –2 GLGM (skewness; kurtosis) Significant differences between HPV+ and HPV- (P ≤ 0.05).

Discussion A prior study showed significant differences in some texture features of OPC on CT (17), however, different classes of texture features distinguish non-OPCs. Potentially morphologic differences exist between HPV+ and HPV- non-OPC compared to OPC. Our findings may have a possibility to suggest HPV status does not affect prognosis of non-OPC patients, unlike those OPC patients. May be the reason HPV+ non-OPC is still not established as a distinct subtype of non-OPC, unlike in OPC.

Limitations No direct comparison between the underlying tumor histopathology and mathematical significance of the texture analysis The sample size is relatively small, totaling 46 patients. Few patients were eliminated due to motion artifact and streak artifact from dental hardware Did not include areas of ulceration in the contoured volumes

Conclusions Numerous texture features demonstrated a statistically significant difference between HPV+ and HPV- non-OPC Non-OPC may have different morphologic features based on the HPV status of the primary tumors Texture analysis may have the potential to explain differences between OPCs and non-OPCs based on HPV status –Different types of texture features found to be significant in OPCs compared to non-OPCs –Potentially related to differences in clinical features and prognosis

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