BACKGROUND AND PURPOSE: Head and neck squamous cell carcinoma associated with human papillomavirus infection represents a distinct tumor entity. We hypothesized that diffusion phenotypes based on the histogram analysis of ADC values reflect distinct degrees of tumor heterogeneity in human papillomavirus–positive and human papillomavirus–negative head and neck squamous cell carcinomas. MATERIALS AND METHODS: One hundred five consecutive patients (mean age, 64 years; range, 45–87 years) with primary oropharyngeal (n = 52) and oral cavity (n = 53) head and neck squamous cell carcinoma underwent MR imaging with anatomic and diffusion-weighted sequences (b = 0, b = 1000 s/mm², monoexponential ADC calculation). The collected tumor voxels from the contoured ROIs provided histograms from which position, dispersion, and form parameters were computed. Histogram data were correlated with histopathology, p16-immunohistochemistry, and polymerase chain reaction for human papillomavirus DNA. RESULTS: There were 21 human papillomavirus–positive and 84 human papillomavirus–negative head and neck squamous cell carcinomas. At histopathology, human papillomavirus–positive cancers were more often nonkeratinizing (13/21, 62%) than human papillomavirus–negative cancers (19/84, 23%; P = .001), and their mitotic index was higher (71% versus 49%; P = .005). ROI-based mean and median ADCs were significantly lower in human papillomavirus–positive (1014 ± 178 × 10⁻⁶ mm²/s and 970 ± 187 × 10⁻⁶ mm²/s, respectively) than in human papillomavirus–negative tumors (1184 ± 168 × 10⁻⁶ mm²/s and 1161 ± 175 × 10⁻⁶ mm²/s, respectively; P < .001), whereas excess kurtosis and skewness were significantly higher in human papillomavirus–positive (1.934 ± 1.386 and 0.923 ± 0.510, respectively) than in human papillomavirus–negative tumors (0.643 ± 0.982 and 0.399 ± 0.516, respectively; P < .001). Human papillomavirus–negative head and neck squamous cell carcinoma had symmetric normally distributed ADC histograms, which corresponded histologically to heterogeneous tumors with variable cellularity, high stromal component, keratin pearls, and necrosis. Human papillomavirus–positive head and neck squamous cell carcinomas had leptokurtic skewed right histograms, which corresponded to homogeneous tumors with back-to-back densely packed cells, scant stromal component, and scattered comedonecrosis. CONCLUSIONS: Diffusion phenotypes of human papillomavirus–positive and human papillomavirus–negative head and neck squamous cell carcinomas show significant differences, which reflect their distinct degree of tumor heterogeneity.

BACKGROUND AND PURPOSE: Although diffusion-weighted imaging combined with morphologic MRI (DWIMRI) is used to detect posttreatment recurrent and second primary head and neck squamous cell carcinoma, the diagnostic criteria used so far have not been clarified. We hypothesized that precise MRI criteria based on signal intensity patterns on T2 and contrast-enhanced T1 complement DWI and therefore improve the diagnostic performance of DWIMRI. MATERIALS AND METHODS: We analyzed 1.5T MRI examinations of 100 consecutive patients treated with radiation therapy with or without additional surgery for head and neck squamous cell carcinoma. MRI examinations included morphologic sequences and DWI (b=0 and b=1000 s/mm²). Histology and follow-up served as the standard of reference. Two experienced readers, blinded to clinical/histologic/follow-up data, evaluated images according to clearly defined criteria for the diagnosis of recurrent head and neck squamous cell carcinoma/second primary head and neck squamous cell carcinoma occurring after treatment, post-radiation therapy inflammatory edema, and late fibrosis. DWI analysis included qualitative (visual) and quantitative evaluation with an ADC threshold. RESULTS: Recurrent head and neck squamous cell carcinoma/second primary head and neck squamous cell carcinoma occurring after treatment was present in 36 patients, whereas 64 patients had post-radiation therapy lesions only. The Cohen κ for differentiating tumor from post-radiation therapy lesions with MRI and qualitative DWIMRI was 0.822 and 0.881, respectively. Mean ADCmean in recurrent head and neck squamous cell carcinoma/second primary head and neck squamous cell carcinoma occurring after treatment (1.097 ± 0.295 × 10⁻³ mm²/s) was significantly lower (P < .05) than in post-radiation therapy inflammatory edema (1.754 ± 0.343 × 10⁻³ mm²/s); however, it was similar to that in late fibrosis (0.987 ± 0.264 × 10⁻³ mm²/s, P > .05). Although ADCs were similar in tumors and late fibrosis, morphologic MRI criteria facilitated distinction between the 2 conditions. The sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios (95% CI) of DWIMRI with ADCmean < 1.22 × 10⁻³ mm²/s and precise MRI criteria were 92.1% (83.5–100.0), 95.4% (90.3–100.0), 92.1% (83.5–100.0), 95.4% (90.2–100.0), 19.9 (6.58–60.5), and 0.08 (0.03–0.24), respectively, indicating a good diagnostic performance to rule in and rule out disease. CONCLUSIONS: Adding precise morphologic MRI criteria to quantitative DWI enables reproducible and accurate detection of recurrent head and neck squamous cell carcinoma/second primary head and neck squamous cell carcinoma occurring after treatment.

Diffusion weighted imaging (DWI) constitutes a major functional parameter performed in Magnetic Resonance Imaging (MRI). The DW sequence is performed by acquiring a set of native images described by their b-values, each b-value representing the strength of the diffusion MR gradients specific to that sequence. By fitting the data with models describing the motion of water in tissue, an apparent diffusion coefficient (ADC) map is built and allows the assessment of water mobility inside the tissue. The high cellularity of tumors restricts the water diffusion and decreases the value of ADC within tumors, which makes them appear hypointense on ADC maps. The role of this sequence now largely exceeds its first clinical apparitions in neuroimaging, whereby the method helped diagnose the early phases of cerebral ischemic stroke. The applications extend to whole-body imaging for both neoplastic and non-neoplastic diseases. This review emphasizes the integration of DWI in the genitourinary system imaging by outlining the sequence’s usage in female pelvis, prostate, bladder, penis, testis and kidney MRI. In gynecologic imaging, DWI is an essential sequence for the characterization of cervix tumors and endometrial carcinomas, as well as to differentiate between leiomyosarcoma and benign leiomyoma of the uterus. In ovarian epithelial neoplasms, DWI provides key information for the characterization of solid components in heterogeneous complex ovarian masses. In prostate imaging, DWI became an essential part of multi-parametric Magnetic Resonance Imaging (mpMRI) to detect prostate cancer. The Prostate Imaging–Reporting and Data System (PI-RADS) scoring the probability of significant prostate tumors has significantly contributed to this success. Its contribution has established mpMRI as a mandatory examination for the planning of prostate biopsies and radical prostatectomy. Following a similar approach, DWI was included in multiparametric protocols for the bladder and the testis. In renal imaging, DWI is not able to robustly differentiate between malignant and benign renal tumors but may be helpful to characterize tumor subtypes, including clear-cell and non-clear-cell renal carcinomas or low-fat angiomyolipomas. One of the most promising developments of renal DWI is the estimation of renal fibrosis in chronic kidney disease (CKD) patients. In conclusion, DWI constitutes a major advancement in genitourinary imaging with a central role in decision algorithms in the female pelvis and prostate cancer, now allowing promising applications in renal imaging or in the bladder and testicular mpMRI.

BACKGROUND AND PURPOSE: Controversy exists as to whether ADC histograms are capable to distinguish human papillomavirus–positive (HPV+) from human papillomavirus–negative (HPV–) oropharyngeal squamous cell carcinoma. We investigated how the choice of b-values influences the capability of ADC histograms to distinguish between the two tumor types. MATERIALS AND METHODS: Thirty-four consecutive patients with histologically proved primary oropharyngeal squamous cell carcinoma (11 HPV+ and 23 HPV–) underwent 3T MR imaging with a single-shot EPI DWI sequence with 6 b-values (0, 50, 100, 500, 750, 1000 s/mm²). Monoexponentially calculated perfusion-sensitive (including b=0 s/mm²) and perfusion-insensitive/true diffusion ADC maps (with b ≥ 100 s/mm² as the lowest b-value) were generated using Matlab. The choice of b-values included 2 b-values (ADC_b0–1000, ADC_b100–1000, ADC_b500–1000, ADC_b750–1000) and 3–6 b-values (ADC_{b0–750–1000}, ADC_{b0–500–750–1000}, ADC_{b0–50–100–1000}, ADC_{b0–50–100–750–1000}, ADC_{b0–50–100–500–750–1000}). Readers blinded to the HPV– status contoured all tumors. ROIs were then copied onto ADC maps, and their histograms were compared. RESULTS: ADC histogram metrics in HPV+ and HPV– oropharyngeal squamous cell carcinoma changed significantly depending on the b-values. The mean ADC was lower, and skewness was higher in HPV+ than in HPV– oropharyngeal squamous cell carcinoma only for ADC_b0–1000, ADC_{b0–750–1000}, and ADC_{b0–500–750–1000} (P < .05), allowing distinction between the 2 tumor types. Kurtosis was significantly higher in HPV+ versus HPV– oropharyngeal squamous cell carcinoma for all b-value combinations except 2 perfusion-insensitive maps (ADC_b500–1000 and ADC_b750–1000). Among all b-value combinations, kurtosis on ADC_b0–1000 had the highest diagnostic performance to distinguish HPV+ from HPV– oropharyngeal squamous cell carcinoma (area under the curve = 0.893; sensitivity = 100%, specificity = 82.6%). Acquiring multiple b-values for ADC calculation did not improve the distinction between HPV+ and HPV– oropharyngeal squamous cell carcinoma. CONCLUSIONS: The choice of b-values significantly affects ADC histogram metrics in oropharyngeal squamous cell carcinoma. Distinguishing HPV+ from HPV– oropharyngeal squamous cell carcinoma is best possible on the ADC_b0–1000 map.