Diagnostic yield of FAP-guided positron emission tomography in thyroid cancer: a systematic review.

Background: Several recent studies have proposed the possible application of positron emission tomography/computed tomography (PET/CT) administering radiolabelled fibroblast-activation protein (FAP) inhibitors for various forms of thyroid cancer (TC), including differentiated TC (DTC), and medullary TC (MTC). Methods: The authors conducted an extensive literature search of original studies examining the effectiveness of FAP-guided PET/CT in patients with TC. The papers included were original publications exploring the use of FAP-targeted molecular imaging in restaging metastatic DTC and MTC patients. Results: A total of 6 studies concerning the diagnostic yield of FAP-targeted PET/CT in TC (274 patients, of which 247 DTC and 27 MTC) were included in this systematic review. The included articles reported high values of FAP-targeted PET/CT detection rates in TC, ranging from 81 to 100% in different anatomical sites and overall superior to the comparative imaging method. Conclusion: Although there are promising results, the existing literature on the diagnostic accuracy of FAP-guided PET in this context is still quite limited. To thoroughly evaluate its potential significance in TC patients, it is needed to conduct prospective randomized multicentric trials.

How young radiologists use contrast media and manage adverse reactions: an international survey.

OBJECTIVES: To collect real-world data about the knowledge and self-perception of young radiologists concerning the use of contrast media (CM) and the management of adverse drug reactions (ADR). METHODS: A survey (29 questions) was distributed to residents and board-certified radiologists younger than 40 years to investigate the current international situation in young radiology community regarding CM and ADRs. Descriptive statistics analysis was performed. RESULTS: Out of 454 respondents from 48 countries (mean age: 31.7 ± 4 years, range 25-39), 271 (59.7%) were radiology residents and 183 (40.3%) were board-certified radiologists. The majority (349, 76.5%) felt they were adequately informed regarding the use of CM. However, only 141 (31.1%) received specific training on the use of CM and 82 (18.1%) about management ADR during their residency. Although 266 (58.6%) knew safety protocols for handling ADR, 69.6% (316) lacked confidence in their ability to manage CM-induced ADRs and 95.8% (435) expressed a desire to enhance their understanding of CM use and handling of CM-induced ADRs. Nearly 300 respondents (297; 65.4%) were aware of the benefits of contrast-enhanced ultrasound, but 249 (54.8%) of participants did not perform it. The preferred CM injection strategy in CT parenchymal examination and CT angiography examination was based on patient's lean body weight in 318 (70.0%) and 160 (35.2%), a predeterminate fixed amount in 79 (17.4%) and 116 (25.6%), iodine delivery rate in 26 (5.7%) and 122 (26.9%), and scan time in 31 (6.8%) and 56 (12.3%), respectively. CONCLUSION: Training in CM use and management ADR should be implemented in the training of radiology residents. CRITICAL RELEVANCE STATEMENT: We highlight the need for improvement in the education of young radiologists regarding contrast media; more attention from residency programs and scientific societies should be focused on training about contrast media use and the management of adverse drug reactions. KEY POINTS: • This survey investigated training of young radiologists about use of contrast media and management adverse reactions. • Most young radiologists claimed they did not receive dedicated training. • An extreme heterogeneity of responses was observed about contrast media indications/contraindications and injection strategy.

CT Arthrography of the Elbow: What Radiologists Should Know.

Computed tomography (CT) arthrography is a quickly available imaging modality to investigate elbow disorders. Its excellent spatial resolution enables the detection of subtle pathologic changes of intra-articular structures, which makes this technique extremely valuable in a joint with very tiny chondral layers and complex anatomy of articular capsule and ligaments. Radiation exposure has been widely decreased with the novel CT scanners, thereby increasing the indications of this examination. The main applications of CT arthrography of the elbow are the evaluation of capsule, ligaments, and osteochondral lesions in both the settings of acute trauma, degenerative changes, and chronic injury due to repeated microtrauma and overuse. In this review, we discuss the normal anatomic findings, technical tips for injection and image acquisition, and pathologic findings that can be encountered in CT arthrography of the elbow, shedding light on its role in the diagnosis and management of different orthopedic conditions. We aspire to offer a roadmap for the integration of elbow CT arthrography into routine clinical practice, fostering improved patient outcomes and a deeper understanding of elbow pathologies.

The role of baseline 2-[18 F]-FDG-PET/CT metrics and radiomics features in predicting primary gastric lymphoma diagnosis.

Diffuse Large B-Cell Lymphomas (DLCBL) and mucosa-associated lymphoid tissue (MALT) are the two most common primary gastric lymphomas (PGLs), but have strongly different features. DLBCL is more aggressive, is frequently diagnosed at an advanced stage and has a poorer prognosis. The aim of this retrospective study was to explore the role of fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (2-[18 F]-FDG-PET/CT) and radiomics features (RFs) in predicting the final diagnosis of patients with PGLs. Ninety-one patients with newly diagnosed PGLs who underwent pre-treatment 2-[18 F]-FDG-PET/CT were included. PET images were qualitatively and semi-quantitatively analyzed by deriving maximum standardized uptake value body weight (SUVbw), maximum standardized uptake value lean body mass (SUVlbm), maximum standardized uptake value body surface area (SUVbsa), lesion to liver SUVmax ratio (L-L SUV R), lesion to blood-pool SUVmax ratio (L-BP SUV R), metabolic tumor volume (gMTV) and total lesion glycolysis of gastric lesion (gTLG), total MTV (tMTV), TLG, and first-order RFs (histogram-related and shape related). Receiver-operating characteristic (ROC) curve analyses were performed to determine the differential diagnostic values of PET parameters. The final diagnosis was DLBCL in 54 (59%) cases and MALT in 37 cases (41%). PGLs showed FDG avidity in 83 cases (90%), 54/54 of DLBCL and 29/37 of MALT. All PET/CT metabolic features, such as stage of disease and tumor size, were significantly higher in DLBCL than MALT; while the presence of H. Pylori infection was more common in MALT. At univariate analysis, all PET/CT metrics were significantly higher in DLBCL than MALT lymphomas, while among RFs only Shape volume_vx and Shape sphericity showed a significant difference between the two groups. In conclusion we demonstrated that 2-[18 F]-FDG-PET/CT parameters can potentially discriminate between DLBCL and MALT lymphomas with high accuracy. Among first-order RFs, only Shape volume_vx and Shape sphericity helped in the differential diagnosis.

Artificial intelligence for radiographic imaging detection of caries lesions: a systematic review.

BACKGROUND: The aim of this systematic review is to evaluate the diagnostic performance of Artificial Intelligence (AI) models designed for the detection of caries lesion (CL). MATERIALS AND METHODS: An electronic literature search was conducted on PubMed, Web of Science, SCOPUS, LILACS and Embase databases for retrospective, prospective and cross-sectional studies published until January 2023, using the following keywords: artificial intelligence (AI), machine learning (ML), deep learning (DL), artificial neural networks (ANN), convolutional neural networks (CNN), deep convolutional neural networks (DCNN), radiology, detection, diagnosis and dental caries (DC). The quality assessment was performed using the guidelines of QUADAS-2. RESULTS: Twenty articles that met the selection criteria were evaluated. Five studies were performed on periapical radiographs, nine on bitewings, and six on orthopantomography. The number of imaging examinations included ranged from 15 to 2900. Four studies investigated ANN models, fifteen CNN models, and two DCNN models. Twelve were retrospective studies, six cross-sectional and two prospective. The following diagnostic performance was achieved in detecting CL: sensitivity from 0.44 to 0.86, specificity from 0.85 to 0.98, precision from 0.50 to 0.94, PPV (Positive Predictive Value) 0.86, NPV (Negative Predictive Value) 0.95, accuracy from 0.73 to 0.98, area under the curve (AUC) from 0.84 to 0.98, intersection over union of 0.3-0.4 and 0.78, Dice coefficient 0.66 and 0.88, F1-score from 0.64 to 0.92. According to the QUADAS-2 evaluation, most studies exhibited a low risk of bias. CONCLUSION: AI-based models have demonstrated good diagnostic performance, potentially being an important aid in CL detection. Some limitations of these studies are related to the size and heterogeneity of the datasets. Future studies need to rely on comparable, large, and clinically meaningful datasets. PROTOCOL: PROSPERO identifier: CRD42023470708.

2-[18F]-FDG PET/CT Semiquantitative and Radiomics Predictive Parameters of Richter's Transformation in CLL Patients.

Background and Objectives: Chronic lymphocytic leukemia (CLL) is the most common type of leukemia in developed countries, which can evolve into aggressive lymphoma variants, a process called Richter transformation (RT). The aim of this retrospective study was to analyze the role of 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (2-[18F]-FDG PET/CT) and its semiquantitative and radiomics features in detecting RT and evaluate the impact on overall survival (OS). Materials and Methods: One hundred and thirty-seven patients with histologically proven CLL were retrospectively recruited. PET/CT images were qualitatively and semiquantitatively examined by estimating the main metabolic parameters (the maximum standardized uptake value body weight (SUVbw), lean body mass (SUVlbm), body surface area (SUVbsa), lesion-to-blood-pool SUV ratio (L-BP SUV R), lesion-to-liver SUV ratio (L-L SUV R), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) and radiomics first- and second- order variables of the lesion with highest uptake. The role of these parameters in predicting RT and OS was analyzed. Results: One hundred and thirty (95%) PET/CT scans were positive, showing an increased tracer uptake at the site of disease, whereas the remaining 7 (5%) scans were negative. SUVbw, SUVlbm, SUVbsa, L-L SUV ratio, and L-BP SUV ratio were significantly higher in the RT group (p < 0.001 in all cases). Radiomics first- and second-order features were not significantly associated with RT. After a median follow-up of 44 months, 56 patients died; OS was significantly shorter in patients with RT than patients without RT (28 vs. 34 months; p = 0.002). Binet-stage, RT, and L-BP SUV R were shown to be independent prognostic features. Conclusions: Semiquantitative PET/CT parameters such as SUVbw, SUVlbm, SUVbsa, L-L SUV ratio and L-BP SUV ratio may be useful in discriminating patients with a high risk of developing RT, whereas Binet-stage, RT, and L-BP SUV R are also significant in predicting OS.

X-rays radiomics-based machine learning classification of atypical cartilaginous tumour and high-grade chondrosarcoma of long bones.

BACKGROUND: Atypical cartilaginous tumour (ACT) and high-grade chondrosarcoma (CS) of long bones are respectively managed with active surveillance or curettage and wide resection. Our aim was to determine diagnostic performance of X-rays radiomics-based machine learning for classification of ACT and high-grade CS of long bones. METHODS: This retrospective, IRB-approved study included 150 patients with surgically treated and histology-proven lesions at two tertiary bone sarcoma centres. At centre 1, the dataset was split into training (n = 71 ACT, n = 24 high-grade CS) and internal test (n = 19 ACT, n = 6 high-grade CS) cohorts, respectively, based on the date of surgery. At centre 2, the dataset constituted the external test cohort (n = 12 ACT, n = 18 high-grade CS). Manual segmentation was performed on frontal view X-rays, using MRI or CT for preliminary identification of lesion margins. After image pre-processing, radiomic features were extracted. Dimensionality reduction included stability, coefficient of variation, and mutual information analyses. In the training cohort, after class balancing, a machine learning classifier (Support Vector Machine) was automatically tuned using nested 10-fold cross-validation. Then, it was tested on both the test cohorts and compared to two musculoskeletal radiologists' performance using McNemar's test. FINDINGS: Five radiomic features (3 morphology, 2 texture) passed dimensionality reduction. After tuning on the training cohort (AUC = 0.75), the classifier had 80%, 83%, 79% and 80%, 89%, 67% accuracy, sensitivity, and specificity in the internal (temporally independent) and external (geographically independent) test cohorts, respectively, with no difference compared to the radiologists (p ≥ 0.617). INTERPRETATION: X-rays radiomics-based machine learning accurately differentiates between ACT and high-grade CS of long bones. FUNDING: AIRC Investigator Grant.

Effects of Interobserver Segmentation Variability and Intensity Discretization on MRI-Based Radiomic Feature Reproducibility of Lipoma and Atypical Lipomatous Tumor.

Segmentation and image intensity discretization impact on radiomics workflow. The aim of this study is to investigate the influence of interobserver segmentation variability and intensity discretization methods on the reproducibility of MRI-based radiomic features in lipoma and atypical lipomatous tumor (ALT). Thirty patients with lipoma or ALT were retrospectively included. Three readers independently performed manual contour-focused segmentation on T1-weighted and T2-weighted sequences, including the whole tumor volume. Additionally, a marginal erosion was applied to segmentations to evaluate its influence on feature reproducibility. After image pre-processing, with included intensity discretization employing both fixed bin number and width approaches, 1106 radiomic features were extracted from each sequence. Intraclass correlation coefficient (ICC) 95% confidence interval lower bound ≥ 0.75 defined feature stability. In contour-focused vs. margin shrinkage segmentation, the rates of stable features extracted from T1-weighted and T2-weighted images ranged from 92.68 to 95.21% vs. 90.69 to 95.66% after fixed bin number discretization and from 95.75 to 97.65% vs. 95.39 to 96.47% after fixed bin width discretization, respectively, with no difference between the two segmentation approaches (p ≥ 0.175). Higher stable feature rates and higher feature ICC values were found when implementing discretization with fixed bin width compared to fixed bin number, regardless of the segmentation approach (p < 0.001). In conclusion, MRI radiomic features of lipoma and ALT are reproducible regardless of the segmentation approach and intensity discretization method, although a certain degree of interobserver variability highlights the need for a preliminary reliability analysis in future studies.

CT and MRI radiomics of bone and soft-tissue sarcomas: an updated systematic review of reproducibility and validation strategies.

OBJECTIVE: To systematically review radiomic feature reproducibility and model validation strategies in recent studies dealing with CT and MRI radiomics of bone and soft-tissue sarcomas, thus updating a previous version of this review which included studies published up to 2020. METHODS: A literature search was conducted on EMBASE and PubMed databases for papers published between January 2021 and March 2023. Data regarding radiomic feature reproducibility and model validation strategies were extracted and analyzed. RESULTS: Out of 201 identified papers, 55 were included. They dealt with radiomics of bone (n = 23) or soft-tissue (n = 32) tumors. Thirty-two (out of 54 employing manual or semiautomatic segmentation, 59%) studies included a feature reproducibility analysis. Reproducibility was assessed based on intra/interobserver segmentation variability in 30 (55%) and geometrical transformations of the region of interest in 2 (4%) studies. At least one machine learning validation technique was used for model development in 34 (62%) papers, and K-fold cross-validation was employed most frequently. A clinical validation of the model was reported in 38 (69%) papers. It was performed using a separate dataset from the primary institution (internal test) in 22 (40%), an independent dataset from another institution (external test) in 14 (25%) and both in 2 (4%) studies. CONCLUSIONS: Compared to papers published up to 2020, a clear improvement was noted with almost double publications reporting methodological aspects related to reproducibility and validation. Larger multicenter investigations including external clinical validation and the publication of databases in open-access repositories could further improve methodology and bring radiomics from a research area to the clinical stage. CRITICAL RELEVANCE STATEMENT: An improvement in feature reproducibility and model validation strategies has been shown in this updated systematic review on radiomics of bone and soft-tissue sarcomas, highlighting efforts to enhance methodology and bring radiomics from a research area to the clinical stage. KEY POINTS: • 2021-2023 radiomic studies on CT and MRI of musculoskeletal sarcomas were reviewed. • Feature reproducibility was assessed in more than half (59%) of the studies. • Model clinical validation was performed in 69% of the studies. • Internal (44%) and/or external (29%) test datasets were employed for clinical validation.

2-[18]F FDG PET/CT dissemination features in adult burkitt lymphoma Are predictive of outcome.

This retrospective study investigated the prognostic role of disease dissemination features (Dmax and Dmaxbsa) measured by 2-[18F]FDG PET/CT in newly diagnosed Burkitt Lymphoma (BL) patients, comparing their performance with other metabolic parameters. We included 78 patients diagnosed with BL between 2010 and 2022 with an available baseline PET, interim PET/CT (iPET) and end of treatment PET/CT (eotPET) and with a minimum of two 2-[18F]FDG avid lesions present at the baseline scan. Dmax was calculated from the three-dimensional coordinates of the baseline metabolic tumor volume (MTV) by using LIFEx software; Dmaxbsa was calculated as Dmax normalized for body surface area according to the Du Bois method. We evaluated their effect on metabolic treatment response evaluated by PET, on progression free survival (PFS) and on overall survival (OS). Dmaxbsa was significantly associated with tumor stage, bulky and extranodal disease, MTV and TLG. At a median follow-up of 49 months, the median PFS and OS were 45 and 48 months. Dmax and Dmaxbsa were significantly higher in not complete metabolic response than complete metabolic response group at iPET and eotPET.As far as PFS, parameters including iPET/CT, eotPET/CT outcomes, MTV and TLG showed to be independent prognostic factors while Dmax and Dmaxbsa were not significantly associated with the outcome. Dissemination features, together with eotPET/CT results, MTV and TLG, demonstrated to be significantly correlated with OS. In conclusion, in this study we demonstrated that dissemination features derived by 2[18F]-FDG PET/CT were significantly correlated with response to treatment and long-term outcome, independently from other PET features.

AI applications in musculoskeletal imaging: a narrative review.

This narrative review focuses on clinical applications of artificial intelligence (AI) in musculoskeletal imaging. A range of musculoskeletal disorders are discussed using a clinical-based approach, including trauma, bone age estimation, osteoarthritis, bone and soft-tissue tumors, and orthopedic implant-related pathology. Several AI algorithms have been applied to fracture detection and classification, which are potentially helpful tools for radiologists and clinicians. In bone age assessment, AI methods have been applied to assist radiologists by automatizing workflow, thus reducing workload and inter-observer variability. AI may potentially aid radiologists in identifying and grading abnormal findings of osteoarthritis as well as predicting the onset or progression of this disease. Either alone or combined with radiomics, AI algorithms may potentially improve diagnosis and outcome prediction of bone and soft-tissue tumors. Finally, information regarding appropriate positioning of orthopedic implants and related complications may be obtained using AI algorithms. In conclusion, rather than replacing radiologists, the use of AI should instead help them to optimize workflow, augment diagnostic performance, and keep up with ever-increasing workload.Relevance statement This narrative review provides an overview of AI applications in musculoskeletal imaging. As the number of AI technologies continues to increase, it will be crucial for radiologists to play a role in their selection and application as well as to fully understand their potential value in clinical practice. Key points • AI may potentially assist musculoskeletal radiologists in several interpretative tasks.• AI applications to trauma, age estimation, osteoarthritis, tumors, and orthopedic implants are discussed.• AI should help radiologists to optimize workflow and augment diagnostic performance.

US-guided percutaneous irrigation of extra-shoulder calcific tendinitis.

OBJECTIVES: To investigate the efficacy and safety of ultrasound-guided percutaneous irrigation of calcific tendinopathy (US-PICT) applied out of the shoulder, comparing its effectiveness to US-PICT of the rotator cuff. METHODS: Patients subjected to US-PICT for extra-shoulder calcific tendinitis (Case Group) were compared to those subjected to US-PICT of the rotator cuff (Control Group). We had pre-procedure Visual Analogue Scale (VAS) pain score, 1- and 3-month VAS of patients of the Case Group, pre-procedure and 3-month VAS of patients of the Control Group. RESULTS: The Case Group consisted of 41 patients (27 women; mean age: 45 ± 9years): 26 gluteus medius, 5 patellar tendon, 3 rectus femoris, 2 gluteus maximus, 2 common extensor tendon, 1 extensor carpi radialis longus, 1 pes anserinus, and 1 peroneus longus. The Control Group included 41 patients (27 women; mean age: 47 ± 11 years). The mean pre-procedure VAS of the Case Group was 8.8 ± 0.7 with a significant (P < .001) drop at 1 month (4.5 ± 0.6) and 3 months (3.6 ± 0.6). The mean pre-procedure VAS of the Control Group was 8 ± 1.4 and dropped to 3.1 ± 1.6 after 3 months (P < .001). Post-treatment VAS at 3 months was not significantly different between two Groups (P = 0.134). Similarly, the decrease of VAS from baseline to 3 months was not significantly different between the two Groups (P = 0.264). CONCLUSIONS: US-PICT is a safe and effective procedure that can be used out of the shoulder. ADVANCES IN KNOWLEDGE: This study demonstrated the safety and effectiveness of US-PICT as a valuable therapeutic option for extra-shoulder calcific tendinitis, with similar clinical outcome to the same procedure performed in the rotator cuff. The technique must be adapted in some deeply located calcifications by means of the use of different needles and by thoroughly planning the access point for the procedure.

Diagnostic performance of high-resolution ultrasound in the evaluation of intrinsic and extrinsic wrist ligaments after trauma.

PURPOSE: To investigate the role of ultrasound (US) in the evaluation of intrinsic and extrinsic ligaments of the wrist with magnetic resonance arthrography (MRA) as the reference standard. MATERIALS AND METHODS: This prospective study included patients referred for MRA after wrist trauma. US examination was performed just before MRA. On the dorsal and palmar sides of the wrist, the intrinsic interosseus and midcarpal, extrinsic, and collateral ligaments were evaluated. MRA was performed on a 1.5-T unit. In the first 20 patients included, ligament thickness was independently assessed using US and MRA and thickness reproducibility was calculated. Ligament integrity was evaluated in all patients. RESULTS: 38 patients (22 men, 16 women; mean age: 38 years) were included. Ligament thickness reproducibility ranged between 44% for the palmar ulnocapitate ligament and 71% for the palmar scaphotriquetral ligament. US had a sensitivity, specificity, positive and negative predictive values, and accuracy of 100% in the identification of tears of the palmar (n=8) and dorsal (n=3) bands of the scapholunate ligament and the ulnar collateral ligament (n=3). It had a sensitivity of 100%, specificity of 97%, positive predictive value of 50%, negative predictive value of 100%, and accuracy of 97% in the identification of tears of the palmar ulnolunate ligament (n=1). CONCLUSION: Compared to MRA, US showed good reproducibility in the assessment of wrist ligament thickness and similar accuracy with respect to identifying tears of the scapholunate, palmar ulnolunate, and ulnar collateral ligaments.

Shear-wave elastography for the evaluation of tendinopathies: a systematic review and meta-analysis.

PURPOSE: To compare pathologic and healthy tendons using shear-wave elastography (SWE). METHODS: A systematic review with meta-analysis was done searching Pubmed and EMBASE up to September 2022. Prospective, retrospective and cross-sectional studies that used SWE in the assessment of pathologic tendons versus control were included. Our primary outcome were SWE velocity (m/s) and stiffness (kPa). Methodological quality was assessed by the methodological index for non-randomized studies (MINORS). We used the mean difference (MD) with corresponding 95% confidence intervals (CIs) to quantify effects between groups. We performed sensitivity analysis in case of high heterogeneity, after excluding poor quality studies according to MINORS assessment. We used Grades of Recommendation, Assessment, Development and Evaluation to evaluate the certainty of evidence (CoE). RESULTS: Overall, 16 studies with 676 pathologic tendons (188 Achilles, 142 patellar, 96 supraspinatus, 250 mixed) and 723 control tendons (484 healthy; 239 contralateral tendon) were included. Five studies (31.3%) were judged as poor methodological quality. Shear-wave velocity and stiffness meta-analyses showed high heterogeneity. According to a sensitivity analysis, pathologic tendons had a lower shear wave velocity (MD of - 1.69 m/s; 95% CI 1.85; - 1.52; n = 274; I2 50%) compared to healthy tendons with very low CoE. Sensitivity analysis on stiffness still showed high heterogeneity. CONCLUSION: Pathological tendons may have reduced SWE velocity compared to controls, but the evidence is very uncertain. Future robust high-quality longitudinal studies and clear technical indications on the use of this tool are needed. PROTOCOL: PROSPERO identifier: CRD42023405410 CLINICAL RELEVANCE STATEMENT: SWE is a relatively recent modality that may increase sensitivity and diagnostic accuracy of conventional ultrasound imaging promoting early detection of tendinopathy. Non-negligible heterogeneity has been observed in included studies, so our findings may encourage the conduct of future high-quality longitudinal studies which can provide clear technical indications on the use of this promising tool in tendon imaging.

Bone mineral density differences between femurs of scoliotic patients undergoing quantitative computed tomography analysis.

PURPOSE: Scoliosis is a cause of loading imbalance between the lower limbs, which can result in BMD differences between the two femurs. We investigated the discrepancy in BMD values assessed by quantitative computed tomography (QCT) between femurs in patients with and without scoliosis, also assessing if this difference can be related to spine convexity. METHODS: Abdominal CT examinations were retrospectively reviewed. An ''asynchronous'' calibration of CT images was performed to obtain BMD values from QCT. Scoliosis was evaluated on the antero-posterior CT localizer to calculate the Cobb angle. Differences between aBMD and vBMD of femurs were assessed in both scoliotic and non-scoliotic subjects. RESULTS: Final study cohort consisted of 263 subjects, 225 of them without scoliosis (85.6%) and 38 with scoliosis (14.4%). No significant differences were found in the general population without scoliosis, except for vBMD at the neck. Comparison of femurs in scoliotic patients showed statistically significant differences at neck aBMD -0.028 g/cm2, p = 0.004), total femur aBMD (--0.032 g/cm2, p = 0.008) and total femur vBMD (--8.9 mg/cm3, p = 0.011), with lower BMD values on the convexity side. In 10 cases (26%) a change in the final T-score diagnosis was observed. CONCLUSION: QCT analysis demonstrated a difference in both areal and volumetric BMD between the two femurs of scoliotic patients, in relation to the side of the scoliotic curve. If these data will be confirmed by larger studies, bilateral femoral DXA acquisition may be proposed for these patients.

Application of radiomics and machine learning to thyroid diseases in nuclear medicine: a systematic review.

BACKGROUND: In the last years growing evidences on the role of radiomics and machine learning (ML) applied to different nuclear medicine imaging modalities for the assessment of thyroid diseases are starting to emerge. The aim of this systematic review was therefore to analyze the diagnostic performances of these technologies in this setting. METHODS: A wide literature search of the PubMed/MEDLINE, Scopus and Web of Science databases was made in order to find relevant published articles about the role of radiomics or ML on nuclear medicine imaging for the evaluation of different thyroid diseases. RESULTS: Seventeen studies were included in the systematic review. Radiomics and ML were applied for assessment of thyroid incidentalomas at 18 F-FDG PET, evaluation of cytologically indeterminate thyroid nodules, assessment of thyroid cancer and classification of thyroid diseases using nuclear medicine techniques. CONCLUSION: Despite some intrinsic limitations of radiomics and ML may have affect the results of this review, these technologies seem to have a promising role in the assessment of thyroid diseases. Validation of preliminary findings in multicentric studies is needed to translate radiomics and ML approaches in the clinical setting.

The evolution of PET imaging in renal, bladder, upper urinary tract urothelial, testicular and penile carcinoma - Today's impact, tomorrow's potential.

INTRODUCTION: The advancement of hybrid PET/CT or PET/MRI imaging for non-prostate genitourinary cancers has not experienced the rapid progress of prostate cancer. Nevertheless, these neoplasms are aggressive and reliable imaging plays a pivotal role in enhancing patients' quality of life and prognosis. AREAS COVERED: the main evidence regarding [18F]FDG and non-[18F]FDG PET/CT or PET/MRI in non-prostate uro-oncological malignancies are summarized and discussed. Moreover, potential future directions concerning PET imaging in these neoplasms are debated, with the aim to stimulate future research projects covering these fields. EXPERT OPINION: In Renal Cell Carcinoma (RCC), [18F]FDG PET/CT demonstrates varying efficacy in staging, restaging, and prognostic stratification, but PSMA PET/CT is emerging as a potential game-changer, particularly in advanced, high-grade aggressive clear cell RCC. [18F]FDG PET/CT may see an increased use in N and M-staging of bladder cancer, as well as for detecting recurrence and response to neoadjuvant chemotherapy. Preliminary data regarding [68Ga]-FAPI also looks promising in this context. [18F]FDG PET/MRI could be useful for the T-staging of bladder cancer, while upper tract urothelial carcinoma still lacks of molecular imaging literature reports. In testicular and penile cancer [18F]FDG PET/CT has demonstrated its usefulness in several clinical settings, although experiences with non-[18F]FDG radiotracers are lacking.

Does it work in childhood and adolescence? The predictive role of postoperative/preablative stimulated thyroglobulin levels in paediatric thyroid cancer. A systematic review of the literature.

BACKGROUND: Thyroglobulin is a well-established disease marker during follow-up in paediatric differentiated thyroid cancer. However, no conclusive data on the role of endogenously stimulated thyroglobulin after thyroidectomy (ptTg) in predicting disease-specific outcomes are available. This review aims to establish the prognostic value of ptTg in children with DTC. METHODS: Online medical databases were searched for studies evaluating the association between ptTg and disease-specific outcomes in DTC-affected children. Documents not in English, preclinical studies, other review articles, case reports, and small case series were excluded. The risk of bias was assessed with the QUADAS-2 tool. RESULTS: Twelve studies, analysing 1043 children in total, were included in the review. They all had a retrospective design and were published between 2016 and 2022. Of all patients, 1008 (97%) and 849 (81%) had undergone thyroidectomy and RAI, respectively. Eight studies (756 children) evaluated the correlation between ptTg and disease persistence/relapse: six reported a significant association between these parameters; a specific ptTg cut-off (10-14 ng/ml) was identified at the multivariate analysis in three studies. The remaining four studies assessed the link between ptTg levels and disease extension, with three reporting a correlation between ptTg and lung/nodal metastases. DISCUSSION: ptTg is a readily available and inexpensive parameter, bearing a strong prognostic power in identifying disease persistence, relapse, and the presence of metastases in children affected by DTC.

Dual Energy X-ray Absorptiometry: Radiographer'S Role in Assessing Fracture Risk Assessment Tool (FRAX) Questionnaire Variables.

BACKGROUND: The FRAX® algorithm is a tool used to calculate the 10-year probability of fracture in patients with osteoporosis and is based the assessment of several risk factors. We assessed the performance and accuracy of the completion of the FRAX® anamnestic questionnaire by the radiographer without impact on the clinical workflow. METHODOLOGY: We evaluated the accuracy of fracture risk calculation by the radiographer using the FRAX® algorithm before and after specific training. A total of 100 women were enrolled in the study. The radiographer preliminarily administered the FRAX® questionnaire to all subjects before the execution of the DXA examination. After the end of the examination, a radiologist administered the questionnaire to the patient. Women were divided into two groups: group A (pre-training) and group B (post-training). The radiographer in group A completed the FRAX® questionnaire for the patients before training. For group B, the same radiographer completed the FRAX® questionnaire after training. The results of the FRAX® questionnaire completed by radiographer were compared with that completed by the referring physician. RESULTS: Before training, radiographer's accuracy ranged from 92% (question 7, alcohol consumption) to 36% (question 6, secondary osteoporosis). After training, accuracy values improved substantially, ranging from 100% to 92%. Analysis of the absolute values of FRAX® showed that in the pre-training group data tended to be overestimated by the radiographer, with both major and fractures probabilities being significantly higher when assessed by the radiographer (12% and 5.8%, respectively). After the training, there was a marked decrease in the variation between the FRAX® data calculated by the radiographer and the radiologist. CONCLUSIONS: The accuracy of fracture risk calculation by the radiographer using the FRAX® algorithm is significantly improved after a specific training period. This study demonstrates the importance of dedicated training radiographers on the FRAX® algorithm.