This study aimed to evaluate the diagnostic accuracy of panoramic radiography (PAN) for the detection of clinically/surgically confirmed apical periodontitis (AP) in root canal–treated teeth using ...cone-beam computed tomographic (CBCT) imaging as the reference standard.
Two hundred forty patients with endodontically treated AP (diseased group) were detected via CBCT imaging using the periapical index system. They were divided into groups of 20 each according to lesion size (2–4.5 mm and 4.6–7 mm) and anatomic area (incisor, canine/premolar, and molar) in both the upper and lower arches. Another 240 patients with root filling and a healthy periapex (healthy group) were selected. All diseased and healthy patients underwent PAN first and a CBCT scan within 40 days. The periapical index system was also used to assess AP using PAN. Sensitivity, specificity, diagnostic accuracy, positive predictive value, and negative predictive value for PAN images with respect to CBCT imaging were analyzed. The k value was calculated to assess both the interobserver reliability for PAN and the agreement between PAN and CBCT.
PAN showed low sensitivity (48.8), mediocre negative predictive value (64.7), good diagnostic accuracy (71.3), and high positive predictive value (88.6) and specificity (93.8). Both interobserver reliability for PAN and agreement between PAN and CBCT were moderate (k = 0.58 and 0.42, respectively). The best identified AP was located in the lower canine/premolar and molar areas, whereas the worst identified AP was located in the upper/lower incisor area and upper molar area.
PAN showed good diagnostic accuracy, high specificity, and low sensitivity for the detection of endodontically treated AP.
•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.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Sex and gender disparities have been reported for different types of non-reproductive cancers. Males are two times more likely to develop kidney cancer than females and have a higher death rate. ...These differences can be explained by looking at genetics and genomics, as well as other risk factors such as hypertension and obesity, lifestyle, and female sex hormones. Examination of the hormonal signaling pathways bring further insights into sex-related differences. Sex and gender-based disparities can be observed at the diagnostic, histological and treatment levels, leading to significant outcome difference. This review summarizes the current knowledge about sex and gender-related differences in the clinical presentation of patients with kidney cancer and the possible biological mechanisms that could explain these observations. Underlying sex-based differences may contribute to the development of sex-specific prognostic and diagnostic tools and the improvement of personalized therapies.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Purpose
(1) To investigate correlations between different types of FAI and the ratio of acetabular volume (AV) to femoral head volume (FV) on MR arthrography. (2) To assess 2D/3D measurements in ...identifying different types of FAI by means of cut-off values of AV/FV ratio (AFR).
Materials and methods
Alpha angle, cranial acetabular version, acetabular depth, lateral center edge angle, AV, and FV of 52 hip MR arthrography were measured. ANOVA test correlated different types of FAI with AFR. ROC curves classified FAI by cut-off values of AFR. Accuracy of 2D/3D measurements was calculated.
Results
ANOVA test showed a significant difference of AFR (
p
value < 0.001) among the three types of FAI. The mean values of AFR were 0.64, 0.74, and 0.89 in cam, mixed, and pincer types, respectively. Cut-off values of AFR were 0.70 to distinguish cam types from mixed and pincer types, and 0.79 to distinguish pincer types from cam and mixed types. Cut-off values identified 100%, 73.9%, and 55.6% of pincer, cam, and mixed types. 2D and 3D classifications of FAI showed accuracy of 40.4% and 73.0%.
Conclusions
3D measurements were clearly more accurate than 2D measurements. Distinct cut-off values of AFR discriminated cam types from pincer types and identified pincer types in all cases. Cam and mixed types were not accurately recognized.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, VSZLJ, ZAGLJ
The oral cavity constitutes a complex anatomical area that can be affected by many developmental, inflammatory, and tumoural diseases. MultiSlice Computed Tomography (MSCT) and Magnetic Resonance ...Imaging (MRI) currently represent the essential and complementary imaging techniques for detecting oral cavity abnormalities. Advanced MRI with diffusion-weighted imaging (DWI) and dynamic contrast-enhanced perfusion-weighted imaging (DCE-PWI) has recently increased the ability to characterise oral lesions and distinguish disease recurrences from post therapy changes. The analysis of the oral cavity area via imaging techniques is also complicated both by mutual close appositions of different mucosal surfaces and metal artifacts from dental materials. Nevertheless, an exact identification of oral lesions is made possible thanks to dynamic manoeuvres and specific stratagems applicable on MSCT and MRI acquisitions. This study summarises the currently available imaging techniques for oral diseases, with particular attention to the role of DWI, DCE-PWI, and dynamic manoeuvres. We also propose MSCT and MRI acquisition protocols for an accurate study of the oral cavity area.
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.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Abstract
Background
COVID-19 is a pandemic disease affecting predominantly the respiratory apparatus with clinical manifestations ranging from asymptomatic to respiratory failure. Chest CT is a ...crucial tool in diagnosing and evaluating the severity of pulmonary involvement through dedicated scoring systems. Nonetheless, many questions regarding the relationship of radiologic and clinical features of the disease have emerged in multidisciplinary meetings. The aim of this retrospective study was to explore such relationship throughout an innovative and alternative approach.
Materials and methods
This study included 550 patients (range 25–98 years; 354 males, mean age 66.1; 196 females, mean age 70.9) hospitalized for COVID-19 with available radiological and clinical data between 1 March 2021 and 30 April 2022. Radiological data included CO-RADS, chest CT score, dominant pattern, and typical/atypical findings detected on CT examinations. Clinical data included clinical score and outcome. The relationship between such features was investigated through the development of the main four frequently asked questions summarizing the many issues arisen in multidisciplinary meetings, as follows 1) CO-RADS, chest CT score, clinical score, and outcomes; 2) the involvement of a specific lung lobe and outcomes; 3) dominant pattern/distribution and severity score for the same chest CT score; 4) additional factors and outcomes.
Results
1) If CT was suggestive for COVID, a strong correlation between CT/clinical score and prognosis was found; 2) Middle lobe CT involvement was an unfavorable prognostic criterion; 3) If CT score < 50%, the pattern was not influential, whereas if CT score > 50%, crazy paving as dominant pattern leaded to a 15% increased death rate, stacked up against other patterns, thus almost doubling it; 4) Additional factors usually did not matter, but lymph-nodes and pleural effusion worsened prognosis.
Conclusions
This study outlined those radiological features of COVID-19 most relevant towards disease severity and outcome with an innovative approach.
Mandibular fractures are among the most common maxillofacial fractures observed in emergency rooms and are mainly caused by road accidents. The clinical features of mandibular fractures include ...malocclusion and loss of mandibular function. Panoramic radiography is usually limited to isolated lesions, whereas computed tomography is the tool of choice for all other facial traumatic events. No reference standard classification system for the different types of mandibular fractures is defined. Therapeutic options include a conservative approach or surgical treatment based on the anatomic area and the severity of fracture. The main purpose of this pictorial review is to illustrate a practical description of the pathophysiology of mandibular fractures and describe both the imaging techniques to recognise them and the therapeutic indications.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The aim of this single-center, observational, retrospective study was to investigate magnetic resonance imaging (MRI) biomarkers for the assessment of radiotherapy (RT)-induced xerostomia. ...Twenty-seven patients who underwent radiation therapy for oropharyngeal cancer were divided into three groups according to the severity of their xerostomia—mild, moderate, and severe—clinically confirmed with the Common Terminology Criteria for Adverse Events (CTCAE). No severe xerostomia was found. Conventional and functional MRI (perfusion- and diffusion- weighted imaging) performed both pre- and post-RT were studied for signal intensity, mean apparent diffusion coefficient (ADC) values, k-trans, and area under the perfusion curves. Contrast-enhanced T1 images and ADC maps were imported into 3D slicer software, and salivary gland volumes were segmented. A total of 107 texture features were derived. T-Student and Wilcoxon signed-rank tests were performed on functional MRI parameters and texture analysis features to identify the differences between pre- and post-RT populations. A p-value < 0.01 was defined as acceptable. Receiver operating characteristic (ROC) curves were plotted for significant parameters to discriminate the severity of xerostomia in the pre-RT population. Conventional and functional MRI did not yield statistically significant results; on the contrary, five texture features showed significant variation between pre- and post-RT on the ADC maps, of which only informational measure of correlation 1 (IMC 1) was able to discriminate the severity of RT-induced xerostomia in the pre-RT population (area under the curve (AUC) > 0.7). Values lower than the cut-off of −1.473 × 10−11 were associated with moderate xerostomia, enabling the differentiation of mild xerostomia from moderate xerostomia with a 73% sensitivity, 75% specificity, and 75% diagnostic accuracy. Therefore, the texture feature IMC 1 on the ADC maps allowed the distinction between different degrees of severity of RT-induced xerostomia in the pre-RT population. Accordingly, texture analysis on ADC maps should be considered a useful tool to evaluate salivary gland radiosensitivity and help identify patients at risk of developing more serious xerostomia before radiation therapy is administered.
Although interstitial lung disease (ILD) is a major cause of morbidity and mortality in systemic sclerosis (SSc), its prognostication remains challenging. Given that CT represents the gold standard ...imaging technique in ILD assessment, a systematic review on chest CT findings as predictors of mortality or ILD progression in SSc-ILD was performed.
Three databases (Medline, Embase, and Web of Science) were searched to identify all studies analyzing CT mortality or ILD progression predictors in SSc-ILD, from inception to December 2020. ILD progression was defined by worsening of forced vital capacity and/or CT ILD findings. Manuscripts not written in English, with not available full-text, not focusing on SSc-ILD or with SSc-ILD not extrapolated, otherwise with overlap syndromes, pediatric patients, <10 cases or predictors other than CT features were excluded.
Out of 3,513 citations, 15 full-texts (2,332 patients with SSc-ILD) met the inclusion criteria. ILD extent and extensive ILD, ILD densitometric analysis parameters, fibrotic extent and reticulation extent resulted as independent mortality predictors. Extensive ILD is also an independent predictor of death, need for supplemental oxygen or lung transplantation. Honeycombing extent is an independent risk factor for respiratory mortality. Independent predictors of ILD progression were not identified.
ILD extent and extensive ILD independently predict mortality in SSc-ILD on CT, as well as ILD densitometric analysis, fibrotic extent and reticulation extent. Extensive ILD is also a predictor of death, need for supplemental oxygen, or lung transplantation. Honeycombing extent predicts respiratory mortality. CT predictors of ILD progression need to be further investigated.
https://www.crd.york.ac.uk/prospero/, PROSPERO, identifier: CRD420202005001.
PDF
