High-Resolution Ultrasound of Odontogenic Cutaneous Sinus Tract: An International Multicentric Experience and a Review of the Literature.

OBJECTIVES: To investigate the role of high-resolution ultrasound (HR-US) in the initial and differential diagnosis of the Odontogenic Cutaneous Sinus Tract (OCST) in a multicentric setting. METHODS: Skin HR-US examinations of OCSTs performed between January 2019 and June 2023 at different Institutions were retrospectively reviewed. Epidemiological and clinical data (age, gender, location of the skin lesion, causative tooth, and the clinical suspicion) as well as HR-US imaging findings (morphology and length of the sinus tract, Doppler signal, and cortical bone interruption of maxilla or mandible) were collected. US examinations were performed by expert radiologists using a high-performance US scanner, employing a high-frequency linear probe (15 MHz or higher frequencies). In only one patient the HR-US exam was integrated with strain elastography (SE). RESULTS: Sixteen patients were enrolled with a median age of 37.6 years (range 16-70 years). The most frequent clinical suspicion was epidermal cyst, while OCST was suspected in only two cases. In all cases, HR-US depicted the sinus tract as a nodular, triangular or "champignon-shaped" lesion in the subcutaneous layer, which continued with a slightly tortuous band structure, up to the focally interrupted cortical bone plate. Furthermore, color Doppler evaluation showed color signals around and/or within the lesion, expression of inflammation. On SE, the sinus tract showed a hard pattern, due to fibrous and granulomatous tissue. CONCLUSIONS: HR-US, thanks to its high spatial resolution, allows the evaluation of OCST, and play a crucial diagnostic role, mainly when the clinical suspicious is different.

Hepatobiliary-specific magnetic resonance contrast agents: role in biliary trauma.

Non-iatrogenic traumatic bile duct injuries (NI-TBIs) are a rare complication after abdominal trauma, with an estimated prevalence of 2.8-7.4% in patients underwent blunt liver injuries. They may be overlooked in patients with extensive multi-organ trauma, particularly hepatic, splenic and duodenal injuries, which have a prevalence of 91%, 54% and 54%, respectively. Whole body contrast-enhanced computed tomography (CE-CT) represents the examination of choice in polytraumatized hemodynamically stable patients, as it allows a comprehensive evaluation of vascular, parenchymal, bone and soft tissues injuries, but the diagnosis of any biliary leaks is limited to the evaluation of nonspecific imaging findings and on findings evolution in the follow-up, such as the progressive growth of fluid collections. Furthermore, biliary complications, such as the occurrence of biloma or biliary peritonitis, may become manifest several days after the initial trauma, often with unspecific progressive signs and symptoms. Although CT and ultrasonography can suggest bile leaks based on several nonspecific imaging findings (e.g., fluid collections), magnetic resonance imaging (MRI) using hepatobiliary contrast agents helps to identify the site and entity of post-traumatic biliary disruption. Indeed, MRI allows to obtain cholangiographic sequences that may show post-traumatic active bile leakage and cysto-biliary communications by direct visualisation of contrast material extravasation into fluid collections, increasing the preoperative accuracy of NI-TBIs. Few data are available about MRI use in the follow-up of trauma with NI-TBI management. So, in the present mini review, its role is reviewed and our preliminary experience in this field is reported.

Simultaneous 18F-FDG PET/MRI Radiomics and Machine Learning Analysis of the Primary Breast Tumor for the Preoperative Prediction of Axillary Lymph Node Status in Breast Cancer.

In this prospective study, 117 female patients (mean age = 53 years) with 127 histologically proven breast cancer lesions (lymph node (LN) positive = 85, LN negative = 42) underwent simultaneous 18F-FDG PET/MRI of the breast. Quantitative parameters were calculated from dynamic contrast-enhanced (DCE) imaging (tumor Mean Transit Time, Volume Distribution, Plasma Flow), diffusion-weighted imaging (DWI) (tumor ADCmean), and PET (tumor SUVmax, mean and minimum, SUVmean of ipsilateral breast parenchyma). Manual whole-lesion segmentation was also performed on DCE, T2-weighted, DWI, and PET images, and radiomic features were extracted. The dataset was divided into a training (70%) and a test set (30%). Multi-step feature selection was performed, and a support vector machine classifier was trained and tested for predicting axillary LN status. 13 radiomic features from DCE, DWI, T2-weighted, and PET images were selected for model building. The classifier obtained an accuracy of 79.8 (AUC = 0.798) in the training set and 78.6% (AUC = 0.839), with sensitivity and specificity of 67.9% and 100%, respectively, in the test set. A machine learning-based radiomics model comprising 18F-FDG PET/MRI radiomic features extracted from the primary breast cancer lesions allows high accuracy in non-invasive identification of axillary LN metastasis.

Abdominal compartment syndrome: what radiologist needs to know.

The intra-abdominal hypertension (IAH) and the abdominal compartment syndrome (ACS) are life-threatening conditions with a significant rate of mortality; therefore, early detection is paramount in their optimal management. IAH is diagnosed when the intra-abdominal pressure (IAP) is more than 12 mmHg. It can occur when the intra-abdominal volume increases (ileus, ascites, trauma, pancreatitis, etc.) and/or the abdominal wall compliance decreases. IAH can cause decreased venous flow, low cardiac output, renal impairment, and decreased respiratory compliance. Consequently, these complications can lead to multiple organ failure and induce the abdominal compartment syndrome (ACS) when IAP rises above 20 mmHg. The diagnosis is usually made with intravesical pressure measurement. However, this measurement was not always possible to obtain; therefore, alternative diagnostic techniques should be considered. In this setting, computed tomography (CT) may play a crucial role, allowing the detection and characterization of pathological conditions that may lead to IAH. This review is focused on the pathogenesis, clinical features, and radiological findings of ACS, because their presence allows radiologists to raise the suspicion of IAH/ACS in critically ill patients, guiding the most appropriate treatment.

MRI Radiomics and Machine Learning for the Prediction of Oncotype Dx Recurrence Score in Invasive Breast Cancer.

AIM: To non-invasively predict Oncotype DX recurrence scores (ODXRS) in patients with ER+ HER2- invasive breast cancer (IBC) using dynamic contrast-enhanced (DCE) MRI-derived radiomics features extracted from primary tumor lesions and a ML algorithm. MATERIALS AND METHODS: Pre-operative DCE-MRI of patients with IBC, no history of neoadjuvant therapy prior to MRI, and for which the ODXRS was available, were retrospectively selected from a public dataset. ODXRS was obtained on histological tumor samples and considered as positive if greater than 16 and 26 in patients aged under and over 50 years, respectively. Tumor lesions were manually annotated by three independent operators on DCE-MRI images through 3D ROIs positioning. Radiomic features were therefore extracted and selected using multistep feature selection process. A logistic regression ML classifier was then employed for the prediction of ODXRS. RESULTS: 248 patients were included, of which 87 with positive ODXRS. 166 (66%) patients were grouped in the training set, while 82 (33%) in the test set. A total of 1288 features was extracted. Of these, 1244 were excluded as 771, 82 and 391 were excluded as not stable (n = 771), not variant (n = 82), and highly intercorrelated (n = 391), respectively. After the use of recursive feature elimination with logistic regression estimator and polynomial transformation, 92 features were finally selected. In the training set, the logistic regression classifier obtained an overall mean accuracy of 60%. In the test set, the accuracy of the ML classifier was 63%, with a sensitivity of 80%, specificity of 43%, and AUC of 66%. CONCLUSIONS: Radiomics and ML applied to pre-operative DCE-MRI in patients with IBC showed promises for the non-invasive prediction of ODXRS, aiding in selecting patients who will benefit from NAC.

Role of advanced imaging techniques in the evaluation of oncological therapies in patients with colorectal liver metastases.

In patients with colorectal liver metastasis (CRLMs) unsuitable for surgery, oncological treatments, such as chemotherapy and targeted agents, can be performed. Cross-sectional imaging [computed tomography (CT), magnetic resonance imaging (MRI), 18-fluorodexoyglucose positron emission tomography with CT/MRI] evaluates the response of CRLMs to therapy, using post-treatment lesion shrinkage as a qualitative imaging parameter. This point is critical because the risk of toxicity induced by oncological treatments is not always balanced by an effective response to them. Consequently, there is a pressing need to define biomarkers that can predict treatment responses and estimate the likelihood of drug resistance in individual patients. Advanced quantitative imaging (diffusion-weighted imaging, perfusion imaging, molecular imaging) allows the in vivo evaluation of specific biological tissue features described as quantitative parameters. Furthermore, radiomics can represent large amounts of numerical and statistical information buried inside cross-sectional images as quantitative parameters. As a result, parametric analysis (PA) translates the numerical data contained in the voxels of each image into quantitative parameters representative of peculiar neoplastic features such as perfusion, structural heterogeneity, cellularity, oxygenation, and glucose consumption. PA could be a potentially useful imaging marker for predicting CRLMs treatment response. This review describes the role of PA applied to cross-sectional imaging in predicting the response to oncological therapies in patients with CRLMs.

Non-glandular findings on breast ultrasound. Part II: a pictorial review of chest wall lesions.

The breast ultrasound (US) field-of-view (FOV) includes glandular parenchyma as well as tissues located anterior to and posterior to it, up to pleural line. For that, it is possible to incidentally identify lesions unrelated to breast parenchyma during screening or diagnostic US; sometimes a palpable lump may be the reason of the imaging exam. Furthermore, abnormality related to chest wall are easier and more accurate detected after mastectomy. Hence, radiologists should know the US appearance of lesions which may develop from all tissues present in this region and displayed in the US FOV, without focusing only on glandular abnormalities while performing the exam. This is the second of a two-part series on non-glandular breast lesions; in detail, part two provide an overview of US appearance, differential diagnosis, and pitfalls of chest wall lesions. They may have an infectious, traumatic, inflammatory etiology or be benign or malignant neoplasms. The US role in the assessment of chest wall abnormalities is limited, usually computed tomography and/or magnetic resonance are requested as second-level imaging exams to characterize and to assess better their relationship with surrounding structures because of larger and panoramic view. Finally, US could be useful to guide biopsy.

An update on pyelonephritis: role of contrast enhancement ultrasound (CEUS).

Acute pyelonephritis (APN) is a bacterial infection causing inflammation of the kidneys. Diagnosis is usually based on clinical and laboratory findings. Imaging is required if a complication is suspected in acute pyelonephritis to assess the nature and extent of the lesions and to detect underlying causes. CT represents the current imaging modality of choice in clinical practice. CEUS is an alternative that has been proven to be equally accurate in the detection of acute pyelonephritis renal lesions. CEUS allows us to distinguish small simple nephritic involvement from abscess complications and to follow their evolution over time during antibiotic therapy. The absence of ionizing radiation and the lack of nephrotoxicity make CEUS an ideal tool in the study of pyelonephritis.

Non-glandular findings on breast ultrasound. Part I: a pictorial review of superficial lesions.

Ultrasound (US) represents the first-level imaging technique in the assessment of breast in young patients, whereas it is complementary to mammography in adult ones. It is not uncommon to encounter non-glandular mass during either screening or diagnostic breast US; sometimes the evaluation of palpable lump may be the reason of clinician's US request. The breast US field-of-view includes not only the glandular parenchyma, but also the tissues located anterior and posterior to it, from the skin to the ribs. In this setting, the radiologist must be familiar with the non-glandular breast diseases, which can occur in the superficial layers as well as in the chest wall. The differential diagnosis varies according to anatomic layer, so the anatomic origin is the first feature to assess and the correct localization is needed to avoid misdiagnosis and to choose, when requested, the second diagnostic step, imaging or histologic analysis. This paper is the first of two focused on non-glandular breast lesions; characterization, differential diagnosis, and pitfalls of superficial lesions are reviewed. They may be located in the dermis or hypodermis: the former are usually benign skin lesions, whereas the latter, although usually benign, may arise also from the anterior terminal lobular units, hence the papilloma, fibroadenomas, and breast cancers should be included in the differential diagnosis. US is more sensitive than CT and MRI in the assessment of superficial lesions due to higher spatial resolution.

Diagnostic imaging of parotid gland oncocytoma: a pictorial review with emphasis on ultrasound assessment.

Parotid gland oncocytoma (PGO) is a rare benign epithelial tumor that usually occurs in the elderly population. The most common clinical presentation is a painless, slow-growing, non-tender, lobulated, and mobile mass. Histologically, it is composed of monotonous sheets of epithelial cells (oncocytes) with a central scar. The cross-sectional appearance is not specific, and it overlaps with other parotid lesions. On ultrasound (US), oncocytoma appears as an ovoid, well-defined, homogeneous, and hypoechoic lesion. Cystic and hemorrhagic areas as well as intralesional fat may be observed. Doppler analysis shows intratumoral vessels, sometimes with a spoke-wheel pattern. The peak systolic flow is high (up to 100 cm/sec). Furthermore, oncocytoma is avid of FDG on a PET scan, as well as a malignant tumor. Thus, a combined clinical, imaging, and pathologic assessment is essential to establish the most accurate diagnosis and plan the best treatment. US, combined with Doppler techniques, can play an important role in suggesting the diagnosis and confirming it through percutaneous sampling. The purpose of this review is to show the imaging findings in PGO, with special emphasis on the US appearance.

Iliopsoas bursitis: The role of diagnostic imaging in detection, differential diagnosis and treatment.

Iliopsoas bursitis is characterized by distension of the iliopsoas muscle bursa due to synovial fluid and/or hypertrophic synovium. Hip disease is usually associated with it, however, isolated bursitis is also present. Clinically Diagnosing iliopsoas bursitis can be difficult, and imaging is usually required to differentiate iliopsoas bursitis from other inguinal masses such as lymphadenopathy, hernias, and tumors. We present the case of a 45-year-old athletic patient who underwent diagnostic examination for recurrent right hip pain and a recent development (last 3 months) of a bulky right inguinal mass.

Machine Learning in oncology: A clinical appraisal.

Machine learning (ML) is a branch of artificial intelligence centered on algorithms which do not need explicit prior programming to function but automatically learn from available data, creating decision models to complete tasks. ML-based tools have numerous promising applications in several fields of medicine. Its use has grown following the increased availability of patient data due to technological advances such as digital health records and high-volume information extraction from medical images. Multiple ML algorithms have been proposed for applications in oncology. For instance, they have been employed for oncological risk assessment, automated segmentation, lesion detection, characterization, grading and staging, prediction of prognosis and therapy response. In the near future, ML could become essential part of every step of oncological screening strategies and patients' management thus leading to precision medicine.

Ultrasound, shear-wave elastography, and magnetic resonance imaging in native liver survivor patients with biliary atresia after Kasai portoenterostomy: correlation with medical outcome after treatment.

BACKGROUND: Biliary atresia (BA) is a rare obliterative cholangiopathy and Kasai portoenterostomy (KP) represents its first-line treatment; clinical and laboratory parameters together with abdominal ultrasound (US) are usually performed during the follow-up. Shear-wave elastography (SWE) is able to evaluate liver parenchyma stiffness; magnetic resonance imaging (MRI) has also been proposed to study these patients. PURPOSE: To correlate US, SWE, and MRI imaging findings with medical outcome in patients with BA who are native liver survivors after KP. MATERIAL AND METHODS: We retrospectively enrolled 24 patients. They were divided in two groups based on "ideal" (n = 15) or "non-ideal" (n = 9) medical outcome. US, SWE, and MRI exams were analyzed qualitatively and quantitatively for imaging signs suggestive of chronic liver disease (CLD). RESULTS: Significant differences were found in terms of liver surface (P = 0.007) and morphology (P = 0.013), portal vein diameter (P = 0.012) and spleen size (P = 0.002) by US, liver signal intensity (P = 0.013), portal vein diameter (P = 0.010), presence of portosystemic collaterals (P = 0.042), and spleen size (P = 0.001) by MRI. The evaluation of portal vein diameter (moderate, κ = 0.44), of portosystemic collaterals (good, κ = 0.78), and spleen size (very good, κ = 0.92) showed the best agreement between US and MRI. A significant (P = 0.01) difference in liver parenchyma stiffness by SWE was also found between the two groups (cut-off = 9.6 kPa, sensitivity = 55.6%, specificity = 100%, area under the ROC curve = 0.82). CONCLUSION: US, SWE, and MRI findings correlate with the medical outcome in native liver survivor patients with BA treated with KP.