Difference between HPV positive and negative non-oropharyngeal cancer;

texture analysis features on CT

Akifumi Fujita, MD1,4, Karen Buch, MD1, Baojun Li, PhD1, Yusuke Kawashima, DDS1,5, Muhammad M. Qureshi, MBBS1,3

　 Osamu Sakai, MD, PhD1,2,3

Departments of 1Radiology, 2Otolaryngology – Head and Neck Surgery, and 3Radiation OncologyBoston Medical Center, Boston University School of Medicine

4Departments of Radiology, Jichi Medical University School of Medicine5Departments 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 4.1-23.7% (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).

• However, the influence on treatment options and impact on prognosis of HPV is not established among non-OPC patients (7, 8, 10).

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-OPCTexture Feature   HPV+ (N=10)   HPV- (N=36)    

n Mean SD n Mean SD P-value Q-value

Histogram                 Mean 86 1055.13 78.90 294 1074.66 51.89 0.033 0.092 Median 86 1121.34 23.89 294 1128.60 24.69 0.016 0.076 STD 86 325.21 67.45 294 323.06 49.10 0.784 0.871 Entropy 86 5.36 0.45 294 5.23 0.44 0.013 0.076 2nd STD 86 37.03 27.47 294 36.62 27.50 0.902 0.927 Range 86 105.27 75.71 294 104.16 75.88 0.905 0.927 Geometric mean 86 786.89 146.17 294 812.71 90.22 0.032 0.092 Harmonic mean 86 152.16 63.97 294 158.14 52.10 0.429 0.541 IQR 86 159.40 236.01 294 91.45 114.23 0.011 0.076 4th moment 86 6.43e10 1.48e10 294 6.57e10 1.28e10 0.410 0.538 Test 86 0.52 0.31 294 0.51 0.29 0.682 0.818 STD5 86 39.50 33.90 294 33.23 24.00 0.112 0.214 STD9 86 38.48 31.48 294 33.09 25.35 0.149 0.240GLCM                 Entropy 86 0.44 0.17 294 0.40 0.14 0.178 0.276 Contrast 86 47.63 17.99 294 57.57 23.34 <.0001 0.004 Correlation 86 0.68 0.10 294 0.64 0.06 0.0003 0.006 Energy 86 0.14 0.06 294 0.16 0.06 0.022 0.078 Homogeneity 86 0.69 0.07 294 0.70 0.08 0.192 0.289GLRL                 SRE 86 0.05 0.03 294 0.04 0.01 0.054 0.127 LRE 86 0.04 0.02 294 0.04 0.01 0.063 0.133 GLN 86 0.05 0.03 294 0.05 0.02 0.063 0.133 RLN 86 0.04 0.02 294 0.04 0.01 0.079 0.158 RP 86 437.20 50.73 294 436.46 25.21 0.896 0.927

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)      n Mean SD n Mean SD P-value Q-value  

GLRL, continued.                   LGRE 86 444.95 46.00 294 444.80 24.97 0.977 0.977  

HGRE 86 422.97 41.21 294 427.34 23.32 0.348 0.472  

SRLGE 86 446.82 46.96 294 445.40 25.23 0.788 0.871  

SRHGE 86 479.71 160.32 294 447.94 184.17 0.121 0.216  

LRLGE 86 553.41 181.72 294 504.54 209.79 0.051 0.127   LRHGE 86 455.80 138.98 294 408.28 169.26 0.009 0.075  

Law's features                  

L1 86 5.03e5 2.99e5 288 5.45e10 3.74e10 0.290 0.406  

L2 86 6.52e4 4.59e4 288 7.97e4 8.33e4 0.039 0.102  

L3 86 2.05e4 1.42e4 288 2.35e4 2.21e4 0.140 0.236  

L4 86 1.31e5 8.08e4 288 1.45e5 1.20e5 0.229 0.331  

L5 86 1.43e4 1.10e4 288 1.84e4 1.99e4 0.015 0.076  

L6 86 6824.89 6224.61 288 9185.68 9793.39 0.008 0.075  

L7 86 8.80e3 7.39e3 288 1.11e4 1.15e4 0.029 0.092  

L8 86 7.82e3 5.10e3 288 1.01e4 8323.35 0.002 0.034  

L9 86 5.92e4 3.54e4 288 6.30e4 5.10e4 0.438 0.541  

GLGM                

MGR 86 2.10 0.81 294 1.97 0.82 0.123 0.216

VGR 86 5761.59 2401.89 294 5677.36 2177.72 0.758 0.871

Skewness 86 46.49 9.02 294 49.35 10.23 0.019 0.078 Kurtosis 86 2363.60 953.14 294 2668.40 1110.14 0.022 0.078

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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