Background and purpose
Morphologic magnetic resonance imaging (MRI) for characterization of salivary gland tumors has limited utility, and the use of perfusion MRI data in the clinical setting is ...controversial. We examined the potential of tissue-normalized dynamic contrast-enhanced (DCE) MRI pharmacokinetic parameters of salivary gland tumors as imaging biomarkers for characterization and differentiation between benign and malignant lesions.
Materials and methods
DCE-MR images acquired from 60 patients with parotid and submandibular gland tumors were retrospectively reviewed. Pharmacokinetic parameters as transfer constant (
Ktrans)
, rate constant (
Kep)
, extracellular space volume
(Ve)
, fractional plasma volume (
Vp),
and
AEC
(area of all times enhancement curve) were measured on both the lesion and the normal contralateral salivary gland parenchyma. Lesion/parenchyma ratio (L/P) for each parameter was calculated.
Results
Five groups of lesions were identified (reference: histopathology): pleomorphic adenomas(
n
= 20), Warthin tumors(
n
= 16), other benign entities(
n
= 4), non-Hodgkin lymphomas(
n
= 4), and malignancies(
n
= 16). Significant differences were seen for mean values of L/P
Ktrans
(higher in malignancies), L/P
Kep
(lower in adenomas than Warthin tumors), L/P
Ve
(lower in Warthin tumors and lymphomas), L/P
Vp
(higher in Warthin tumors and malignancies than adenomas), and L/P
AEC
(higher in malignancies). Significant differences were found between benign and malignant (non-lymphoproliferative) lesions in mean value of L/P
Ktrans
(0.485 and 1.581), L/P
Vp
(1.288 and 2.834), and L/P
AEC
(0.682 and 1.910). ROC analysis demonstrated the highest AUC (0.96) for L/P
AEC
, with sensitivity and specificity for malignancy of 93.8% and 97.5% (cutoff value = 1.038).
Conclusion
Lesion/parenchyma ratio of DCE-MRI pharmacokinetic data could be helpful for recognizing the principal types of salivary gland tumors; L/P
AEC
seems a valuable biomarker for differentiating benign from malignant tumors.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Objectives
To evaluate the association of magnetic resonance diffusion-weighted imaging (DwI) and dynamic contrast-enhanced perfusion-weighted imaging (DCE-PwI) with a temporal resolution of 5 s, ...wash-in < 120 s, and wash-out ratio > 30% in the evaluation of salivary glands neoplasms.
Methods
DwI and DCE-PwI of 92 salivary glands neoplasms were assessed. The apparent diffusion coefficient (ADC) was calculated by drawing three regions of interest with an average area of 0.30–0.40 cm
2
on three contiguous axial sections. The time/intensity curve was generated from DCE-PwI images by drawing a region of interest that included at least 50% of the largest lesion section. Vessels, calcifications, and necrotic/haemorrhagic or cystic areas within solid components were excluded. The association of ADC ≥ 1.4 × 10
−3
mm
2
/s with type A curves (progressive wash-in) and ADC 0.9–1.4 × 10
−3
mm
2
/s with type C curves (rapid wash-in/slow wash-out) were tested as parameters of benignity and malignancy, respectively. Type B curve (rapid wash-in/rapid wash-out) was not used as a reference parameter.
Results
ADC ≥ 1.4 × 10
−3
mm
2
/s and type A curves were observed only in benign neoplasms. ADC of 0.9–1.4 × 10
−3
mm
2
/s and type C curves association showed specificity of 94.9% and positive predictive value of 81.8% for epithelial malignancies. The association of ADC < 0.9 × 10
−3
mm
2
/s with type B and C curves showed diagnostic accuracy of 94.6% and 100% for Warthin tumour and lymphoma, respectively.
Conclusions
ADC ≥ 1.4 × 10
−3
mm
2
/s and type A curves association was indicative of benignity. Lymphomas exhibited ADC < 0.7 × 10
−3
mm
2
/s and type C curves. The association of ADC < 0.9 × 10
−3
mm
2
/s and type B and C curves had accuracy 94.6% and 88.5% for Warthin tumour and epithelial malignancies, respectively.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
•Overlaps of morphological findings, ADC, and types of time/intensity curve on MRI are found among different parotid lesions.•Texture analysis provides a quantitative assessment of tumor ...heterogeneity by adding precise structural information.•LZE and LRE represent the texture parameters that enable the differentiation between malignant and benign lesions.
Parotid lesions show overlaps of morphological findings, apparent diffusion coefficient (ADC) values and types of time/intensity curve. This research aimed to evaluate the role of diffusion weighted imaging texture analysis in differentiating between benign and malignant parotid lesions and in characterizing pleomorphic adenoma (PA), Warthin tumor (WT), epithelial malignancy (EM), and lymphoma (LY).
Texture analysis of 54 parotid lesions (19 PA, 14 WT, 14 EM, and 7 LY) was performed on ADC map images. An ANOVA test was used to estimate both the difference between benign and malignant lesions and the texture feature differences among PA, WT, EM, and LY. A P-value≤0.01 was considered to be statistically significant. A cut-off value defined by ROC curve analysis was found for each statistically significant texture parameter. The diagnostic accuracy was obtained for each texture parameter with AUC ≥ 0.5. The agreement between each texture parameter and histology was calculated using the Cohen's kappa coefficient.
The mean kappa values were 0.61, 0.34, 0.26, 0.17, and 0.48 for LY, EM, WT, PA, and benign vs. malignant lesions respectively. Long zone emphasis cut-off values >1.870 indicated EM with an accuracy of 81 % and values >2.630 revealed LY with an accuracy of 93 %. Long run emphasis values >1.050 and >1.070 indicated EM and LY with a diagnostic accuracy of 79% and 93% respectively.
Long zone emphasis and long run emphasis texture parameters allowed the identification of LY and the differentiation between benign and malignant lesions. WT and PA were not accurately recognized.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The aim of this study is to find a correlation between tumoral heterogeneity of squamous cell carcinoma of the oropharynx and human papillomavirus (HPV) status and to determine whether analysis of ...texture features of primary lesion on contrast-enhanced CT (CECT) images can be useful in predicting the HPV positivity. Fifty patients with diagnosis of oropharyngeal carcinoma and pre-treatment CECT were included; tumoral heterogeneity of each lesion was evaluated by extracting quantitative texture parameters of first and higher orders.
T
test and logistic regression were conducted to evaluate the effects of different textural characteristics. There were 35 HPV+ and 15 HPV− lesions. Statistically significant (
p
< 0.05) differences were seen in multiple higher-order extracted parameters. The logistic regression model correctly classified lesions with an accuracy of 95.2%. CT texture analysis of primary oropharyngeal cancer may be used as a tool for predicting the HPV status.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Objectives:
Laryngeal squamous cell carcinoma (LSCC) can involve different anatomic subunits with peculiar surgical and prognostic implications. Despite conflicting outcomes for the same stage of ...disease, the current staging system considers different lesions in a single cluster. The aim of this study was to critically discuss clinical and pathologic staging of primary and recurrent advanced LSCC in order to define current staging pitfalls that impede a precise and tailored treatment strategy.
Methods:
Thirty patients who underwent total laryngectomy in the past 3 years for primary and recurrent advanced squamous cell LSCC were analyzed, comparing endoscopic, imaging, and pathologic findings. Involvement of the different laryngeal subunits, vocal-fold motility, and spreading pattern of the tumor were blindly analyzed. The diagnostic accuracy and differences between clinicoradiologic and pathologic findings were studied with standard statistical analysis.
Results:
Discordant staging was performed in 10% of patients, and thyroid and arytenoid cartilage were the major diagnostic pitfalls. Microscopic arytenoid involvement was significantly more present in case of vocal-fold fixation (P = .028). Upstaging was influenced by paraglottic and pre-epiglottic space cancer involvement, posterior commissure, subglottic region, arytenoid cartilage, and penetration of thyroid cartilage; on the contrary, involvement of the inner cortex or extralaryngeal spread tended to be down-staged. Radiation-failed tumors less frequently involved the posterior third of the paraglottic space (P = .022) and showed a significantly worse pattern of invasion (P < .001).
Conclusions:
Even with the most recent technologies, 1 in 10 patients with advanced LSCC in this case series was differently staged on clinical examination, with cartilage involvement representing the main diagnostic pitfall.
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NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
•A standard measurement of radiological depth of invasion (rDOI) is lacking in the staging of oral cancer;•Computed Tomography-derived rDOI can be of great value in preoperative assessment of ...OSCC;•We have identified specific spatial planes where its measurement is most strongly related to the final pathological report;•We suggest that with a standardized imaging protocol, patients could be better classified and thus correctly treated.
Depth of invasion (DOI) has been introduced into the latest TNM classification of oral squamous cell carcinoma (OSCC). Despite its primarily pathological definition (pDOI), a preoperative evaluation of a radiological DOI (rDOI) would be useful but a standard and practical definition is lacking. The primary aim of this study is to measure the rDOI by computed tomography (CT) and compare it to the pDOI in a cohort of OSCC patients. Then, we analyze the utility and reliability of rDOI in the preoperative setting.
58 cases of OSCC operated at our Institution from 2016 to 2019 were included. After accounting for plane-specific shrinkage factors and for different oral subsites, we have compared pDOI and rDOI for each spatial plane by paired difference test and correlation coefficient. Radiological accuracy and survival analysis were also determined to identify rDOI’s clinical value.
For lateral tongue, pDOI was more strongly related with axial rDOI (P < 0.01); for hard palate, the best plane was the sagittal one (P < 0.01); in floor of mouth (FOM) lesions, the strongest correlation was with coronal rDOI (P < 0.01), as well as for cheek buccal mucosa; sagittal scans seem to be the best to evaluate dorsum of the tongue and retromolar trigone; gingiva (P < 0.01) was most correctly evaluated in the coronal plane. Overall accuracy of rDOI restaging was 75.41%. Disease-free survival seems to be worse as rDOI increases.
We suggest that with a standardized imaging protocol patients could be better classified according to CT-derived DOI.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Objective
Identifying MRI texture parameters able to distinguish inflammation, fibrosis, and residual cancer in patients with naso-oropharynx carcinoma after radiochemotherapy (RT-CHT).
Material and ...methods
In this single-centre, observational, retrospective study, texture analysis was performed on ADC maps and post-gadolinium T1 images of patients with histological diagnosis of naso-oropharyngeal carcinoma treated with RT-CHT. An initial cohort of 99 patients was selected; 57 of them were later excluded. The final cohort of 42 patients was divided into 3 groups (inflammation, fibrosis, and residual cancer) according to MRI, 18F-FDG-PET/CT performed 3–4 months after RT-CHT, and biopsy. Pre-RT-CHT lesions and the corresponding anatomic area post-RT-CHT were segmented with 3D slicer software from which 107 textural features were derived. T-Student and Wilcoxon signed-rank tests were performed, and features with
p
-value < 0.01 were considered statistically significant. Cut-off values—obtained by ROC curves—to discriminate post-RT-CHT non-tumoural changes from residual cancer were calculated for the parameters statistically associated to the diseased status at follow-up.
Results
Two features—Energy and Grey Level Non-Uniformity—were statistically significant on T1 images in the comparison between ‘positive’ (residual cancer) and ‘negative’ patients (inflammation and fibrosis). Energy was also found to be statistically significant in both patients with fibrosis and residual cancer. Grey Level Non-Uniformity was significant in the differentiation between residual cancer and inflammation. Five features were statistically significant on ADC maps in the differentiation between ‘positive’ and ‘negative’ patients. The reduction in values of such features between pre- and post-RT-CHT was correlated with a good response to therapy.
Conclusions
Texture analysis on post-gadolinium T1 images and ADC maps can differentiate residual cancer from fibrosis and inflammation in early follow-up of naso-oropharyngeal carcinoma treated with RT-CHT.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Human papilloma virus infection (HPV) is associated with the development of lingual and palatine tonsil carcinomas. Diagnosing, differentiating HPV-positive from HPV-negative cancers, and assessing ...the presence of lymph node metastases or recurrences by the visual interpretation of images is not easy. Texture analysis can provide structural information not perceptible to human eyes. A systematic literature search was performed on 16 February 2022 for studies with a focus on texture analysis in oropharyngeal cancers. We conducted the research on PubMed, Scopus, and Web of Science platforms. Studies were screened for inclusion according to the preferred reporting items for systematic reviews. Twenty-six studies were included in our review. Nineteen articles related specifically to the oropharynx and seven articles analysed the head and neck area with sections dedicated to the oropharynx. Six, thirteen, and seven articles used MRI, CT, and PET, respectively, as the imaging techniques by which texture analysis was performed. Regarding oropharyngeal tumours, this review delineates the applications of texture analysis in (1) the diagnosis, prognosis, and assessment of disease recurrence or persistence after therapy, (2) early differentiation of HPV-positive versus HPV-negative cancers, (3) the detection of cancers not visualised by imaging alone, and (4) the assessment of lymph node metastases from unknown primary carcinomas.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The tumours of head and neck district are around 3% of all malignancies and squamous cell carcinoma is the most frequent histotype, with rapid increase during the last two decades because of the ...increment of the infection due to human papilloma virus (HPV). Even if the gold standard for the diagnosis is histological examination, including the detection of viral DNA and transcription products, imaging plays a fundamental role in the detection and staging of HPV + tumours, in order to assess the primary tumour, to establish the extent of disease and for follow-up. The main diagnostic tools are Computed Tomography (CT), Positron Emission Tomography-Computed Tomography (PET-CT) and Magnetic Resonance Imaging (MRI), but also Ultrasound (US) and the use of innovative techniques such as Radiomics have an important role. Aim of our review is to illustrate the main imaging features of HPV + tumours of the oropharynx, in US, CT and MRI imaging. In particular, we will outline the main limitations and strengths of the various imaging techniques, the main uses in the diagnosis, staging and follow-up of disease and the fundamental differential diagnoses of this type of tumour. Finally, we will focus on the innovative technique of texture analysis, which is increasingly gaining importance as a diagnostic tool in aid of the radiologist.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Objectives
To evaluate thyroid, arytenoid, and cricoid cartilage invasion on computed tomography (CT) imaging in patients undergoing total laryngectomy for both primary and recurrent laryngeal ...carcinoma. Secondary endpoint was to compare laryngeal cartilage invasion between primary and recurrent tumours.
Methods
Pre-treatment CT of 40 patients who had undergone total laryngectomy was retrospectively evaluated and compared with histology. Focal erosions of thyroid cartilage were accounted for neoplastic invasion of the inner cortex. Full-thickness thyroid cartilage invasion was defined as a tumour-like tissue replacing thyroid cartilage or extended in extra-laryngeal soft tissues. Sclerosis and erosion of arytenoid and cricoid cartilages were assessed as signs of neoplastic invasion.
Results
CT erosion showed perfect agreement for thyroid inner cortex and cricoid cartilage invasion and almost perfect agreement (87%) for arytenoid cartilage invasion. For tumours in contact with thyroid cartilages, the absence of CT erosion underestimated inner cortex infiltration. CT showed perfect agreement in predicting full-thickness thyroid cartilage invasion only in the case of extra-laryngeal neoplastic extension. Arytenoid sclerosis showed poor correlation with neoplastic invasion. For primary tumours, CT demonstrated good (inner cortex 75%; full-thickness 85%), substantial (67.5%), and perfect (100%) accuracy in thyroid, arytenoid, and cricoid cartilage invasion, respectively. No CT differences were observed between primary and recurrent laryngeal tumours.
Conclusion
Tumour-like tissue extension in the extra-laryngeal soft tissues was accurate in predicting thyroid cartilage full-thickness invasion. Erosions of arytenoid, cricoid, and thyroid cartilages’ inner cortex on CT were highly indicative of neoplastic infiltration. No CT difference in cartilage infiltration between primary and recurrent tumours was observed.
Full text
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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