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Relationships between apparent diffusion coefficient (ADC) histogram analysis parameters and PD-L 1-expression in head and neck squamous cell carcinomas: a preliminary study Cover

Relationships between apparent diffusion coefficient (ADC) histogram analysis parameters and PD-L 1-expression in head and neck squamous cell carcinomas: a preliminary study

Radiology and Oncology
Volume 55 (2021): Issue 2 (June 2021)
By: Hans-Jonas Meyer,  Anne Kathrin Höhn and  Alexey Surov  
Open Access
|Jan 2021

Figures & Tables

Figure 1

Representative case with a negative programmed cell death ligand 1 (PD-L1) score. (A) Postcontrast T1-weighted image shows a large enhancing tumor of the right tongue base (arrow). A large lymph node metastasis on the right side can also be appreciated. (B) Apparent diffusion coefficient (ADC) map of the same slide. Both lesions show a marked hypointensity consistent with a diffusion restriction. The tumor (arrow) is surrounded with a region of interest, which is drawn on every tumor showing slide within the margins of the tumor in accordance to the corresponding T1-weighted images. (C) The resulting ADC histogram of the tumor. The histogram analysis parameters (× 10-3 mm2/s) are as follows: ADCmin = 0.79, ADCmean = 1.38, ADCmax = 2.05, P10 = 1.05, P25 = 1.19, P75 = 1.53, P90 = 1.78, median = 1.35,mode = 1.27, kurtosis = 2.61, skewness = 0.41 and entropy = 2.44. (D) The corresponding PD-L1 stained specimen. No staining can be appreciated resulting in a value of 0 in all calculated scores.

Figure 2

Representative case with a positive programmed cell death ligand 1 (PD-L1) score. (A) On the postcontrast T1-weighted image a large enhancing tumor of the side within the right palatine tonsil (arrow). Susceptibility artifacts due to dental material can also be appreciated. (B) Apparent diffusion coefficient (ADC) map on the corresponding slide. A marked hypointensity can be seen consistent with a diffusion restriction. (C) The resulting ADC histogram of the tumor. The histogram analysis parameters (× 10-3 mm2/s) are as follows: ADCmin = 0.51, ADCmean = 0.78, ADCmax = 1.36, P10 = 0.63, P25 = 0.69, P75 = 0.87, P90 = 0.94, median = 0.76, mode = 0.69, kurtosis = 4.57, skewness = 0.72, and entropy = 2.41. (D) The corresponding PD-L1 stained specimen. A weak staining of PD-L1 for tumor cells and associating immune cells can be appreciated. The resulting score values are 5 for the combined positive score and 3 for the immune cell score.

Figure 3

Correlation analysis between skewness derived from apparent diffusion coefficient (ADC) and the immune cell score (ICS). The resulting Spearman’s correlation coefficient is r = -0.38, p = 0.04.

Overview of the included patients

Localizationn (%)
          Tonsil7 (24.1)
          Tongue7 (24.1)
          Hypopharynx6 (20.7)
          Oropharynx5 (17.2)
          Larynx4 (13.9)
Grading
          Moderate (G2)12 (37.5)
          Poor (G3)17 (62.5)
Stage
          T26 (20.7)
          T310 (34.5)
          T413 (44.8)
Nodal status
          Nodal positive25 (86.2)
          Nodal negative4 (13.8)

Overview of the investigated apparent diffusion coefficient (ADC) histogram parameters

ParameterMean ± standard deviation, x10-3 mm2/sRange, x10-3 mm2/s
Mean1.14 ± 0.220.78-1.68
Min0.70 ± 0.250.17-1.24
Max1.78 ± 0.321.35-2.39
P100.90 ± 0.210.54-1.41
P251.0 ± 0.210.64-1.50
P751.27 ± 0.240.87-1.82
P901.41 ± 0.260.94-2.03
Median1.12 ± 0.220.76-1.64
Mode0.97 ± 0.280.78-1.55
Kurtosis3.74 ± 1.402.23-7.93
Skewness0.49 ± 0.49-0.54-1.49
Entropy2.44 ± 0.491.67-3.75
DOI: https://doi.org/10.2478/raon-2021-0005 | Journal eISSN: 1581-3207 | Journal ISSN: 1318-2099
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Language: English
Page range: 150 - 157
Submitted on: Oct 22, 2020
|
Accepted on: Dec 13, 2020
|
Published on: Jan 20, 2021
Published by: Association of Radiology and Oncology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
head and neck squamous cell cancer,
apparent diffusion coefficient,
diffusion weighted imaging,
programmed cell death ligand 1
Related subjects:
Medicine,
Clinical medicine,
Internal medicine,
Haematology, oncology,
Radiology

© 2021 Hans-Jonas Meyer, Anne Kathrin Höhn, Alexey Surov, published by Association of Radiology and Oncology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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