Posteromedial Corner Injuries of the Knee: Imaging Findings

The posteromedial corner (PMC) of the knee is an anatomical region formed by ligamentous structures (medial collateral ligament, posterior oblique ligament, oblique popliteal ligament), the semimembranosus tendon and its expansions, the posteromedial joint capsule, and the posterior horn of the medial meniscus. Injuries to the structures of the PMC frequently occur in acute knee trauma in association with other ligamentous or meniscal tears. The correct assessment of PMC injuries is crucial because the deficiency of these supporting structures can lead to anteromedial rotation instability or the failure of cruciate ligaments grafts. This article reviews the anatomy and biomechanics of the PMC to aid radiologists in identifying injuries potentially involving PMC components.

Dual-energy CT in musculoskeletal imaging: technical considerations and clinical applications

Dual-energy CT stands out as a robust and innovative imaging modality, which has shown impressive advancements and increasing applications in musculoskeletal imaging. It allows to obtain detailed images with novel insights that were once the exclusive prerogative of magnetic resonance imaging. Attenuation data obtained by using different energy spectra enable to provide unique information about tissue characterization in addition to the well-established strengths of CT in the evaluation of bony structures. To understand clearly the potential of this imaging modality, radiologists must be aware of the technical complexity of this imaging tool, the different ways to acquire images and the several algorithms that can be applied in daily clinical practice and for research. Concerning musculoskeletal imaging, dual-energy CT has gained more and more space for evaluating crystal arthropathy, bone marrow edema, and soft tissue structures, including tendons and ligaments. This article aims to analyze and discuss the role of dual-energy CT in musculoskeletal imaging, exploring technical aspects, applications and clinical implications and possible perspectives of this technique.

Artificial intelligence in interventional radiology: state of the art

Artificial intelligence (AI) has demonstrated great potential in a wide variety of applications in interventional radiology (IR). Support for decision-making and outcome prediction, new functions and improvements in fluoroscopy, ultrasound, computed tomography, and magnetic resonance imaging, specifically in the field of IR, have all been investigated. Furthermore, AI represents a significant boost for fusion imaging and simulated reality, robotics, touchless software interactions, and virtual biopsy. The procedural nature, heterogeneity, and lack of standardisation slow down the process of adoption of AI in IR. Research in AI is in its early stages as current literature is based on pilot or proof of concept studies. The full range of possibilities is yet to be explored.Relevance statement Exploring AI's transformative potential, this article assesses its current applications and challenges in IR, offering insights into decision support and outcome prediction, imaging enhancements, robotics, and touchless interactions, shaping the future of patient care.Key points• AI adoption in IR is more complex compared to diagnostic radiology.• Current literature about AI in IR is in its early stages.• AI has the potential to revolutionise every aspect of IR.

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.

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.

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.

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.

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.

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.

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.

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.

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.

US/CT fusion imaging and virtual navigation to guide lumbar intradiscal oxygen-ozone therapy: a pilot study

PURPOSE

To test the feasibility of US/CT fusion imaging to guide lumbar intradiscal O2/O3 therapy to treat discogenic degenerative low back pain due to lumbar disc herniation (LDH).

METHODS

We retrospectively included consecutive patients affected by low back pain and/or sciatica due to LDH resistant to conservative therapies, who underwent to lumbar intradiscal O2/O3 injection under CT/US fusion imaging guidance (Fusion Group) and standard CT guidance (Control Group). For each procedure, we collected procedure operative time, room utilization time, number of CT passes, complications, and O2/O3 intradiscal diffusion adequacy. Technical success was defined as the ability to complete the procedure as initially planned to reach the disc. Technical efficacy was based on O2/O3 intradiscal diffusion adequacy, as demonstrated by the last CT scan.

RESULTS

Six patients (4 males; mean age: 68 ± 15 years) were included in the Fusion group, six (4 males; mean age: 66 ± 12 years) in Control group. No complications were observed in both groups. In Fusion group we found significantly lower room utilization time (30 ± 6 min vs. 46 ± 10 min, p = 0.008), procedure operative time (14 ± 3 min vs. 24 ± 6 min, p = 0.008), and number of CT passes (2 [2,2] vs. 3 [3,3], p = 0.006) than in Control Group, respectively. Technical success and efficacy were 100% in both Groups.

CONCLUSION

CT/US fusion imaging seems to be a feasible and safe guidance for intradiscal O2/O3 injections, allowing decrease of procedure time and number of CT passes.

Bone biopsies guided by augmented reality: a pilot study

PURPOSE

To test the technical feasibility of an augmented reality (AR) navigation system to guide bone biopsies.

METHODS

We enrolled patients subjected to percutaneous computed tomography (CT)-guided bone biopsy using a novel AR navigation system. Data from prospectively enrolled patients (AR group) were compared with data obtained retrospectively from previous standard CT-guided bone biopsies (control group). We evaluated the following: procedure duration, number of CT passes, patient's radiation dose (dose-length product), complications, and specimen adequacy. Technical success was defined as the ability to complete the procedure as planned, reaching the target center. Technical efficacy was assessed evaluating specimen adequacy.

RESULTS

Eight patients (4 males) aged 58 ± 24 years (mean ± standard deviation) were enrolled in the AR group and compared with 8 controls (4 males) aged 60 ± 15 years. No complications were observed. Procedure duration, number of CT passes, and radiation dose were 22 ± 5 min, 4 (median) [4, 6 interquartile range] and 1,034 ± 672 mGy*cm for the AR group and 23 ± 5 min, 9 [7.75, 11.25], and 1,954 ± 993 mGy*cm for controls, respectively. No significant differences were observed for procedure duration (p = 0.878). Conversely, number of CT passes and radiation doses were significantly lower for the AR group (p < 0.001 and p = 0.021, respectively). Technical success and technical efficacy were 100% for both groups.

CONCLUSIONS

This AR navigation system is safe, feasible, and effective; it can decrease radiation exposure and number of CT passes during bone biopsies without increasing duration time.

RELEVANCE STATEMENT

This augmented reality (AR) navigation system is a safe and feasible guidance for bone biopsies; it may ensure a decrease in the number of CT passes and patient's radiation dose.

KEY POINTS

• This AR navigation system is a safe guidance for bone biopsies. • It ensures decrease of number of CT passes and patient's radiation exposure. • Procedure duration was similar to that of standard CT-guided biopsy. • Technical success was 100% as in all patients the target was reached. • Technical efficacy was 100% as the specimen was adequate in all patients.

Predicting risk of metastases and recurrence in soft-tissue sarcomas via Radiomics and Formal Methods

Objective

Soft-tissue sarcomas (STSs) of the extremities are a group of malignancies arising from the mesenchymal cells that may develop distant metastases or local recurrence. In this article, we propose a novel methodology aimed to predict metastases and recurrence risk in patients with these malignancies by evaluating magnetic resonance radiomic features that will be formally verified through formal logic models.

Materials and Methods

This is a retrospective study based on a public dataset evaluating MRI scans T2-weighted fat-saturated or short tau inversion recovery and patients having "metastases/local recurrence" (group B) or "no metastases/no local recurrence" (group A) as clinical outcomes. Once radiomic features are extracted, they are included in formal models, on which is automatically verified the logic property written by a radiologist and his computer scientists coworkers.

Results

Evaluating the Formal Methods efficacy in predicting distant metastases/local recurrence in STSs (group A vs group B), our methodology showed a sensitivity and specificity of 0.81 and 0.67, respectively; this suggests that radiomics and formal verification may be useful in predicting future metastases or local recurrence development in soft tissue sarcoma.

Discussion

Authors discussed about the literature to consider Formal Methods as a valid alternative to other Artificial Intelligence techniques.

Conclusions

An innovative and noninvasive rigourous methodology can be significant in predicting local recurrence and metastases development in STSs. Future works can be the assessment on multicentric studies to extract objective disease information, enriching the connection between the radiomic quantitative analysis and the radiological clinical evidences.

Bizarre parosteal osteochondromatous proliferation: an educational review

Bizarre parosteal osteochondromatous proliferation (BPOP) is a surface-based bone lesion belonging to the group of benign chondrogenic tumors. The aim of this review is to familiarize the readers with imaging features and differential diagnosis of BPOP, also addressing pathological presentation and treatment options. The peak of incidence of BPOP is in the third and fourth decades of life, although it can occur at any age. Hands are the most common location of BPOP (55%), followed by feet (15%) and long bones (25%). On imaging, BPOP appears as a well-marginated mass of heterotopic mineralization arising from the periosteal aspect of the bone. Typical features of BPOP are contiguity with the underlying bone and lack of cortico-medullary continuity, although cortical interruption and medullary involvement have been rarely reported. Histologically, BPOP is a benign bone surface lesion characterized by osteocartilaginous proliferation with disorganized admixture of cartilage with bizarre features, bone and spindle cells. Differential diagnosis includes both benign-such as florid reactive periostitis, osteochondroma, subungual exostosis, periosteal chondroma and myositis ossificans-and malignant lesions-such as periosteal chondrosarcoma and surface-based osteosarcoma. Treatment consists of surgical resection. Local recurrences are common and treated with re-excision.Critical relevance statement Bizarre parosteal osteochondromatous proliferation is a benign mineralized mass arising from the periosteal aspect of bone cortex. Multi-modality imaging characteristics, pathology features and differential diagnosis are here highlighted to familiarize the readers with this entity and offer optimal patient care.

MRI radiomics-based machine learning for classification of deep-seated lipoma and atypical lipomatous tumor of the extremities

PURPOSE

To determine diagnostic performance of MRI radiomics-based machine learning for classification of deep-seated lipoma and atypical lipomatous tumor (ALT) of the extremities.

MATERIAL AND METHODS

This retrospective study was performed at three tertiary sarcoma centers and included 150 patients with surgically treated and histology-proven lesions. The training-validation cohort consisted of 114 patients from centers 1 and 2 (n = 64 lipoma, n = 50 ALT). The external test cohort consisted of 36 patients from center 3 (n = 24 lipoma, n = 12 ALT). 3D segmentation was manually performed on T1- and T2-weighted MRI. After extraction and selection of radiomic features, three machine learning classifiers were trained and validated using nested fivefold cross-validation. The best-performing classifier according to previous analysis was evaluated and compared to an experienced musculoskeletal radiologist in the external test cohort.

RESULTS

Eight features passed feature selection and were incorporated into the machine learning models. After training and validation (74% ROC-AUC), the best-performing classifier (Random Forest) showed 92% sensitivity and 33% specificity in the external test cohort with no statistical difference compared to the radiologist (p = 0.474).

CONCLUSION

MRI radiomics-based machine learning may classify deep-seated lipoma and ALT of the extremities with high sensitivity and negative predictive value, thus potentially serving as a non-invasive screening tool to reduce unnecessary referral to tertiary tumor centers.

Short-Term Precision and Repeatability of Radiofrequency Echographic Multi Spectrometry (REMS) on Lumbar Spine and Proximal Femur: An In Vivo Study

To determine the short-term intra-operator precision and inter-operator repeatability of radiofrequency echographic multi-spectrometry (REMS) at the lumbar spine (LS) and proximal femur (FEM). All patients underwent an ultrasound scan of the LS and FEM. Both precision and repeatability, expressed as root-mean-square coefficient of variation (RMS-CV) and least significant change (LSC) were obtained using data from two consecutive REMS acquisitions by the same operator or two different operators, respectively. The precision was also assessed in the cohort stratified according to BMI classification. The mean (±SD) age of our subjects was 48.9 ± 6.8 for LS and 48.3 ± 6.1 for FEM. Precision was assessed on 42 subjects at LS and 37 subjects on FEM. Mean (±SD) BMI was 24.71 ± 4.2 for LS and 25.0 ± 4.84 for FEM. Respectively, the intra-operator precision error (RMS-CV) and LSC resulted in 0.47% and 1.29% at the spine and 0.32% and 0.89% at the proximal femur evaluation. The inter-operator variability investigated at the LS yielded an RMS-CV error of 0.55% and LSC of 1.52%, whereas for the FEM, the RMS-CV was 0.51% and the LSC was 1.40%. Similar values were found when subjects were divided into BMI subgroups. REMS technique provides a precise estimation of the US-BMD independent of subjects' BMI differences.

Imaging of Anatomical Variants Around the Knee

Several anatomical variants have been described in the knee. These variants may involve intra- and extra-articular structures, such as menisci, ligaments, plicae, bony structures, muscles, and tendons. They have a variable prevalence, are generally asymptomatic, and are usually discovered incidentally in knee magnetic resonance imaging examinations. A thorough knowledge of these findings is essential to avoid overestimating and overinvestigating normal findings. This article reviews most anatomical variants around the knee, describing how to avoid misinterpretation.

MRI-based artificial intelligence to predict infection following total hip arthroplasty failure

PURPOSE

To investigate whether artificial intelligence (AI) can differentiate septic from non-septic total hip arthroplasty (THA) failure based on preoperative MRI features.

MATERIALS AND METHODS

We included 173 patients (98 females, age: 67 ± 12 years) subjected to first-time THA revision surgery after preoperative pelvis MRI. We divided the patients into a training/validation/internal testing cohort (n = 117) and a temporally independent external-testing cohort (n = 56). MRI features were used to train, validate and test a machine learning algorithm based on support vector machine (SVM) to predict THA infection on the training-internal validation cohort with a nested fivefold validation approach. Machine learning performance was evaluated on independent data from the external-testing cohort.

RESULTS

MRI features were significantly more frequently observed in THA infection (P < 0.001), except bone destruction, periarticular soft-tissue mass, and fibrous membrane (P > 0.005). Considering all MRI features in the training/validation/internal-testing cohort, SVM classifier reached 92% sensitivity, 62% specificity, 79% PPV, 83% NPV, 82% accuracy, and 81% AUC in predicting THA infection, with bone edema, extracapsular edema, and synovitis having been the best predictors. After being tested on the external-testing cohort, the classifier showed 92% sensitivity, 79% specificity, 89% PPV, 83% NPV, 88% accuracy, and 89% AUC in predicting THA infection. SVM classifier showed 81% sensitivity, 76% specificity, 66% PPV, 88% NPV, 80% accuracy, and 74% AUC in predicting THA infection in the training/validation/internal-testing cohort based on the only presence of periprosthetic bone marrow edema on MRI, while it showed 68% sensitivity, 89% specificity, 93% PPV, 60% NPV, 75% accuracy, and 79% AUC in the external-testing cohort.

CONCLUSION

AI using SVM classifier showed promising results in predicting THA infection based on MRI features. This model might support radiologists in identifying THA infection.

Shear-wave elastography of the plantar fascia: a systematic review and meta-analysis

PURPOSE

To assess the efficacy of shear-wave elastography (SWE) of the plantar fascia (PF) in identifying plantar fasciitis.

METHODS

A literature search was conducted on the PubMed and Medline databases for articles published up to August 2022. The Newcastle-Ottawa scale was used to assess the risk of bias. We included original research studies in English dealing with the evaluation of patients with plantar fasciitis by means of SWE and including shear modulus (KPa) and/or shear-wave velocity (m/s). We compared healthy and pathologic PF stiffness using the standardised mean difference (SMD) in a random-effects model (95% CI).

RESULTS

Five studies were included with a total of 158 pathologic PFs and 134 healthy PFs. No significant publication bias was detected. Studies were highly heterogeneous (p < 0.00001; I² = 97%). Pathologic PFs showed significantly lower stiffness, with an SMD of - 3.00 m/s (95% confidence interval: - 4.95 to - 1.06, p = 0.002), compared to healthy PF.

CONCLUSION

Pathologic PFs present significantly lower stiffness than healthy PFs. However, the analysed studies are highly heterogeneous.

Ultrasound-guided Musculoskeletal Interventional Procedures Around the Hip: A Practical Guide

Several studies have shown that ultrasound guidance may contribute to improved safety, effectiveness and accuracy of musculoskeletal interventional procedures performed around the hip if compared to those performed with a landmark-guided technique. Different approaches and injectates can be used for treating hip musculoskeletal disorders. These procedures may involve injections in the hip joint, periarticular bursae, tendons, and peripheral nerves. Intra-articular hip injections are mostly used as a conservative approach for treating patients affected by hip osteoarthritis. Ultrasound-guided injection of the iliopsoas bursa is performed in patients with bursitis and/or tendinopathy, to treat those with painful prosthesis due to iliopsoas impingement, or when the lidocaine test is indicated to identify the iliopsoas as a source of pain. Ultrasound-guided interventions are routinely used in patients with greater trochanteric pain syndrome having as target the gluteus medius/minimus tendons and/or the trochanteric bursae. Ultrasound-guided fenestration and platelet-rich plasma injection are applied in patients with hamstring tendinopathy with good clinical outcomes. Last but not least, ultrasound-guided perineural injections can be used for peripheral neuropathies or blocks of the sciatic, lateral femoral cutaneous, and pudendal nerves. In this paper, we discuss the evidence and technical tips for musculoskeletal interventional procedures performed around the hip, highlighting the added value of ultrasound as an imaging guidance modality.

3D vs. 2D MRI radiomics in skeletal Ewing sarcoma: Feature reproducibility and preliminary machine learning analysis on neoadjuvant chemotherapy response prediction

OBJECTIVE

The extent of response to neoadjuvant chemotherapy predicts survival in Ewing sarcoma. This study focuses on MRI radiomics of skeletal Ewing sarcoma and aims to investigate feature reproducibility and machine learning prediction of response to neoadjuvant chemotherapy.

MATERIALS AND METHODS

This retrospective study included thirty patients with biopsy-proven skeletal Ewing sarcoma, who were treated with neoadjuvant chemotherapy before surgery at two tertiary sarcoma centres. 7 patients were poor responders and 23 were good responders based on pathological assessment of the surgical specimen. On pre-treatment T1-weighted and T2-weighted MRI, 2D and 3D tumour segmentations were manually performed. Features were extracted from original and wavelet-transformed images. Feature reproducibility was assessed through small geometrical transformations of the regions of interest mimicking multiple manual delineations, and intraclass correlation coefficient >0.75 defined feature reproducibility. Feature selection also consisted of collinearity and significance analysis. After class balancing in the training cohort, three machine learning classifiers were trained and tested on unseen data using hold-out cross-validation.

RESULTS

1303 (77%) 3D and 620 (65%) 2D radiomic features were reproducible. 4 3D and 4 2D features passed feature selection. Logistic regression built upon 3D features achieved the best performance with 85% accuracy (AUC=0.9) in predicting response to neoadjuvant chemotherapy.

CONCLUSION

Compared to 2D approach, 3D MRI radiomics of Ewing sarcoma had superior reproducibility and higher accuracy in predicting response to neoadjuvant chemotherapy, particularly when using logistic regression classifier.

Comparison between magnetic resonance imaging and electrical impedance myography for evaluating lumbar skeletal muscle composition

Background

To compare electrical impedance myography (EIM) and MRI in assessing lumbar skeletal muscle composition.

Methods

One hundred forty-one patients (78 females, mean age 57 ± 19 years) were prospectively enrolled and underwent lumbar spine MRI, EIM with Skulpt®, and clinical evaluation including the questionnaire SARC-F. MRIs were reviewed to assess the Goutallier score of paravertebral muscles at L3 level and to calculate the cross sectional area (CSA) of both psoas, quadratus lumborum, erector spinae, and multifidus muscles on a single axial slice at L3 level, in order to calculate the skeletal muscle index (SMI=CSA/height2). We tested the correlation between EIM-derived parameters [body fat percentage (BF%) and muscle quality] and body mass index (BMI), Goutallier score (1–4), SMI, and SARC-F scores (0–10) using the Pearson correlation coefficient. The strength of association was considered large (0.5 to 1.0), medium (0.3 to 0.5), small (0.1 to 0.3).

Results

Pearson’s correlation coefficient showed small (0.26) but significant (p < 0.01) positive correlation between BF% obtained with EIM and Goutallier score. Small negative correlation (− 0.22, p < 0.01) was found between EIM muscle quality and Goutallier Score. Large negative correlation (− 0.56, p < 0.01) was found between SMI and Goutallier Score, while SMI showed small negative correlation with SARC-F (− 0.29, p < 0.01). Medium positive correlation was found between Goutallier Score and SARC-F (0.41, p < 0.01). BMI showed medium positive correlation with SMI (r = 0.369, p < 0.01) and small correlation with EIM muscle quality (r = − 0.291, p < 0.05) and BF% (r = 0.227, p < 0.05). We found a substantial increase of the strength of associations of BF% and muscle quality with Goutallier in the 18–40 years (r = 0.485 and r = − 0.401, respectively) and in the 41–70 years group (r = 0.448 and r = − 0.365, respectively).

Conclusions

Muscle quality and BF% measured by EIM device showed only small strength of correlation with other quantitative parameters for assessing muscle mass and fat infiltration. Interesting results have been found in younger patients, but Skulpt Chisel™ should be applied cautiously to assess lumbar skeletal muscle composition. This point deserves further investigation and other studies are warranted.

Trial registration

The registration number of this study is 107/INT/2019.

Knee Muscles Composition Using Electrical Impedance Myography and Magnetic Resonance Imaging

We evaluated the correlation of electrical impedance myography (EIM) measurements of knee muscles composition using Skulpt ChiselTM with MRI data retrieved from muscles segmentation. A total of 140 patients (71 females, 52 ± 21 years) underwent knee MRI, EIM with Skulpt®, and clinical evaluation (SARC-F questionnaire). MRIs were reviewed to assess the cross-sectional area (CSA) and skeletal muscle index (SMI = CSA/height2) of vastus medialis, vastus lateralis, biceps, semimembranosus, and sartorius. We tested the correlations of EIM-derived parameters [body fat-percentage (BF%) and muscle quality] with total CSA, CSA of each muscle, SMI, and SARC-F scores (0−10) using Pearson correlation coefficient. We found medium negative correlation of BF% with SMI (r = −0.430, p < 0.001) and total CSA (r = −0.445, p < 0.001), particularly with biceps (r = −0.479, p < 0.001), sartorius (r = −0.440, p < 0.001), and semimembranosus (r = −0.357, p < 0.001). EIM-derived muscle quality showed small-to-medium positive correlation with MRI measurements, ranging from r = 0.234 of biceps (p = 0.006) to r = 0.302 of total CSA (p < 0.001), except for vastus lateralis (r = 0.014, p = 0.873). SARC-F scores showed small correlations with EIM and MRI data, ranging from r = −0.132 (p = 0.121) with EIM muscle quality to r = −0.288 (p = 0.001) with CSA of vastus medialis. Hence, we observed small-to-medium correlations of muscle parameters derived from Skulpt ChiselTM with SARC-F scores and MRI parameters. We recommend using Skulpt ChiselTM with caution for assessing knee skeletal muscles composition.

Technical Feasibility of Electromagnetic US/CT Fusion Imaging and Virtual Navigation in the Guidance of Spine Biopsies

PURPOSE

 To test the technical feasibility of electromagnetic computed tomography (CT) + ultrasound fusion (US)-guided bone biopsy of spinal lesions.

MATERIALS AND METHODS

 This retrospective study included 14 patients referred for biopsy of spinal bone lesions without cortical disruption or intervertebral disc infection. Lesions were located in the sacrum (n = 4), lumbar vertebral body (n = 7) or intervertebral disc (n = 3). Fusion technology matched a pre-procedure CT scan with real-time ultrasound. The first six procedures were performed under both standard CT and CT + US fusion guidance (group 1). In the last eight procedures, the needle was positioned under fusion imaging guidance alone, and CT was only used at the end of needle placement to confirm correct positioning (group 2). Additionally, we retrieved 8 patients (controls) with location-matched lesions as group 2, which were biopsied in the past with the standard CT-guided technique. The procedure duration and number of CT passes were recorded.

RESULTS

 Mean procedure duration and median CT pass number were significantly higher in group 1 vs. group 2 (45 ± 5 vs. 26 ± 3 minutes, p = 0.002 and 7; 5.25-8.75 vs. 3; 3-3.25, p = 0.001). In controls, the mean procedure duration was 47 ± 4 minutes (p = 0.001 vs. group 2; p = 0.696 vs. group 1) and the number of CT passes was 6.5 (5-8) (p = 0.001 vs. group 2; p = 0.427 vs. group 1). No complications occurred and all specimens were adequate overall. In one case in group 2, the needle position was modified according to CT assessment before specimen withdrawal.

CONCLUSION

 Electromagnetic CT+US fusion-guided bone biopsy of spinal lesions is feasible and safe. Compared to conventional CT guidance, it may reduce procedural time and the number of CT passes.

Intraosseous hibernoma of the appendicular skeleton

Hibernomas are rare lipomatous tumors composed of brown adipocytes. The relative paucity of reported cases involving the bones accounts for the poor understanding of this entity, which is known to affect almost exclusively the axial skeleton. We present a case of intraosseous hibernoma of the humerus, which was found incidentally in a 52-year-old woman and initially misinterpreted as a cartilaginous tumor on magnetic resonance imaging (MRI). The lesion was unchanged in size and morphology at short interval follow-up but increased in size during follow-up over 6 years with an 11 mm increase in the largest diameter. Given the patient's concerns and lesion growth, curettage was performed. Pathology analysis revealed brown fat in keeping with the diagnosis of intraosseous hibernoma. Radiological and pathological findings and pitfalls are herein highlighted to enforce knowledge on this lesion rarely affecting the long bones. Radiologists should think of intraosseous hibernoma if they come across a sclerotic lesion on X-ray or computed tomography, which contains macroscopic fat and shows enhancement on contrast-enhanced MRI. In addition, an intraosseous hibernoma may be picked up incidentally on positron emission tomography-computed tomography due to high fluorodeoxyglucose avidity.

Clinical indications for image-guided interventional procedures in the musculoskeletal system: a Delphi-based consensus paper from the European Society of Musculoskeletal Radiology (ESSR)-part VII, nerves of the lower limb

OBJECTIVES

To perform a Delphi-based consensus on published evidence on image-guided interventional procedures for peripheral nerves of the lower limb (excluding Morton's neuroma) and provide clinical indications.

METHODS

We report the results of a Delphi-based consensus of 53 experts from the European Society of Musculoskeletal Radiology who reviewed the published literature for evidence on image-guided interventional procedures offered around peripheral nerves in the lower limb (excluding Morton's neuroma) to derive their clinical indications. Experts drafted a list of statements and graded them according to the Oxford Centre for evidence-based medicine levels of evidence. Consensus was considered strong when > 95% of experts agreed with the statement or broad when > 80% but < 95% agreed. The results of the Delphi-based consensus were used to write the paper.

RESULTS

Nine statements on image-guided interventional procedures for peripheral nerves of the lower limb have been drafted. All of them received strong consensus. Image-guided pudendal nerve block is safe, effective, and well tolerated with few complications. US-guided perisciatic injection of anesthetic provides good symptom relief in patients with piriformis syndrome; however, the addition of corticosteroids to local anesthetics still has an unclear role. US-guided lateral femoral cutaneous nerve block can be used to provide effective post-operative regional analgesia.

CONCLUSION

Despite the promising results reported by published papers on image-guided interventional procedures for peripheral nerves of the lower limb, there is still a lack of evidence on the efficacy of most procedures.

KEY POINTS

• Image-guided pudendal nerve block is safe, effective, and well tolerated with few complications. • US-guided perisciatic injection of anesthetic provides good symptom relief in patients with piriformis syndrome; however, the addition of corticosteroids to local anesthetics still has an unclear role. • US-guided lateral femoral cutaneous nerve block can be used to provide effective post-operative regional analgesia. The volume of local anesthetic affects the size of the blocked sensory area.

Sarcopenia: imaging assessment and clinical application

Sarcopenia is a progressive, generalized skeletal muscle disorder characterized by reduction of muscle mass and strength. It is associated with increased adverse outcomes including falls, fractures, physical disability, and mortality, particularly, in elderly patients. Nowadays, sarcopenia has become a specific imaging biomarker able to predict clinical outcomes of patients. Muscle fibre reduction has shown to be an unfavourable pre-operative predictive factor in patients with cancer, and is associated with worse clinical outcomes in terms of postoperative complications, morbidity, mortality, and lower tolerance of chemoradiation therapy. Several imaging modalities, including dual-energy X-ray absorptiometry, CT, MRI, and US can be used to estimate muscle mass and quality to reach the diagnosis of sarcopenia. This article reviews the clinical implications of sarcopenia, how this condition can be assessed through different imaging modalities, and future perspectives of imaging of sarcopenia.

MRI radiomics-based machine learning classification of atypical cartilaginous tumour and grade II chondrosarcoma of long bones

Background

Atypical cartilaginous tumour (ACT) and grade II chondrosarcoma (CS2) of long bones are respectively managed with watchful waiting or curettage and wide resection. Preoperatively, imaging diagnosis can be challenging due to interobserver variability and biopsy suffers from sample errors. The aim of this study is to determine diagnostic performance of MRI radiomics-based machine learning in differentiating ACT from CS2 of long bones.

Methods

One-hundred-fifty-eight patients with surgically treated and histology-proven cartilaginous bone tumours were retrospectively included at two tertiary bone tumour centres. The training cohort consisted of 93 MRI scans from centre 1 (n=74 ACT; n=19 CS2). The external test cohort consisted of 65 MRI scans from centre 2 (n=45 ACT; n=20 CS2). Bidimensional segmentation was performed on T1-weighted MRI. Radiomic features were extracted. After dimensionality reduction and class balancing in centre 1, a machine-learning classifier (Extra Trees Classifier) was tuned on the training cohort using 10-fold cross-validation and tested on the external test cohort. In centre 2, its performance was compared with an experienced musculoskeletal oncology radiologist using McNemar's test.

Findings

After tuning on the training cohort (AUC=0.88), the machine-learning classifier had 92% accuracy (60/65, AUC=0.94) in identifying the lesions in the external test cohort. Its accuracies in correctly classifying ACT and CS2 were 98% (44/45) and 80% (16/20), respectively. The radiologist had 98% accuracy (64/65) with no difference compared to the classifier (p=0.134).

Interpretation

Machine learning showed high accuracy in classifying ACT and CS2 of long bones based on MRI radiomic features.

Funding

ESSR Young Researchers Grant.

Sonography of tendon pathology in the hand and wrist

Traumatic and non-traumatic tendon lesions are common at the wrist and hand. For the diagnosis, therapy management, and long-term prognosis of tendon lesions, a detailed understanding of the complex anatomy and knowledge of typical injury patterns is crucial for both radiologists and clinicians. Improvements in high-resolution ultrasound are producing high-quality images of the superficial tendinous and peritendinous structures. Thus, ultrasound is a valuable first-choice tool for visualizing traumatic, inflammatory, and degenerative conditions of the extensor and flexor tendons, particularly with the advantage of possible dynamic examination. The additional use of duplex-Doppler and power Doppler ultrasound imaging is recommended for detection of tenosynovitis in overuse injury, inflammatory disease, infection, and after traumatic conditions. In traumatic tendon injuries, knowing the precise injury zone is important for treatment decision-making. In cases of tendon rupture, the radiologist should report the tear type (i.e., complete or partial-thickness) and assess the degree of tendon retraction and associated avulsion injury, including the degree of fragment displacement. The function of intact flexor tendons may be impaired by thickening, strain, or rupture of corresponding annular pulleys. This review describes in detail the typical ultrasound imaging features of common pathologies of hand and wrist tendons, including annular pulley lesions.

Clinical indications for image-guided interventional procedures in the musculoskeletal system: a Delphi-based consensus paper from the European Society of Musculoskeletal Radiology (ESSR)-part VI, foot and ankle

Objectives

Clarity regarding accuracy and effectiveness for interventional procedures around the foot and ankle is lacking. Consequently, a board of 53 members of the Ultrasound and Interventional Subcommittees of the European Society of Musculoskeletal Radiology (ESSR) reviewed the published literature to evaluate the evidence on image-guided musculoskeletal interventional procedures around this anatomical region.

Methods

We report the results of a Delphi-based consensus of 53 experts from the European Society of Musculoskeletal Radiology who reviewed the published literature for evidence on image-guided interventional procedures offered around foot and ankle in order to derive their clinical indications. Experts drafted a list of statements and graded them according to the Oxford Centre for evidence-based medicine levels of evidence. Consensus was considered strong when > 95% of experts agreed with the statement or broad when > 80% but < 95% agreed. The results of the Delphi-based consensus were used to write the paper that was shared with all panel members for final approval.

Results

A list of 16 evidence-based statements on clinical indications for image-guided musculoskeletal interventional procedures in the foot and ankle were drafted after a literature review. The highest level of evidence was reported for four statements, all receiving 100% agreement.

Conclusion

According to this consensus, image-guided interventions should not be considered a first-level approach for treating Achilles tendinopathy, while ultrasonography guidance is strongly recommended to improve the efficacy of interventional procedures for plantar fasciitis and Morton’s neuroma, particularly using platelet-rich plasma and corticosteroids, respectively.

Key Points

• The expert panel of the ESSR listed 16 evidence-based statements on clinical indications of image-guided musculoskeletal interventional procedures in the foot and ankle.

• Strong consensus was obtained for all statements.

• The highest level of evidence was reached by four statements concerning the effectiveness of US-guided injections of corticosteroid for Morton’s neuroma and PRP for plantar fasciitis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-021-08125-z.

Effects of Interobserver Variability on 2D and 3D CT- and MRI-Based Texture Feature Reproducibility of Cartilaginous Bone Tumors

This study aims to investigate the influence of interobserver manual segmentation variability on the reproducibility of 2D and 3D unenhanced computed tomography (CT)- and magnetic resonance imaging (MRI)-based texture analysis. Thirty patients with cartilaginous bone tumors (10 enchondromas, 10 atypical cartilaginous tumors, 10 chondrosarcomas) were retrospectively included. Three radiologists independently performed manual contour-focused segmentation on unenhanced CT and T1-weighted and T2-weighted MRI by drawing both a 2D region of interest (ROI) on the slice showing the largest tumor area and a 3D ROI including the whole tumor volume. Additionally, a marginal erosion was applied to both 2D and 3D segmentations to evaluate the influence of segmentation margins. A total of 783 and 1132 features were extracted from original and filtered 2D and 3D images, respectively. Intraclass correlation coefficient ≥ 0.75 defined feature stability. In 2D vs. 3D contour-focused segmentation, the rates of stable features were 74.71% vs. 86.57% (p < 0.001), 77.14% vs. 80.04% (p = 0.142), and 95.66% vs. 94.97% (p = 0.554) for CT and T1-weighted and T2-weighted images, respectively. Margin shrinkage did not improve 2D (p = 0.343) and performed worse than 3D (p < 0.001) contour-focused segmentation in terms of feature stability. In 2D vs. 3D contour-focused segmentation, matching stable features derived from CT and MRI were 65.8% vs. 68.7% (p = 0.191), and those derived from T1-weighted and T2-weighted images were 76.0% vs. 78.2% (p = 0.285). 2D and 3D radiomic features of cartilaginous bone tumors extracted from unenhanced CT and MRI are reproducible, although some degree of interobserver segmentation variability highlights the need for reliability analysis in future studies.

Ultrasound-guided musculoskeletal interventional procedures around the shoulder

Ultrasound is a fast, accessible, reliable, and radiation-free imaging modality routinely used to assess the soft tissues around the shoulder. It enables to identify a wide range of pathological conditions. Furthermore, most ultrasound-guided musculoskeletal interventional procedures around the shoulder produce better results in terms of accuracy and clinical efficacy than those performed in a blinded fashion. Indeed, intra-articular and peri-articular interventional procedures can be easily performed under continuous ultrasound monitoring to ensure the correct position of the needle and to deliver the medication to a specific target. Several technical approaches and medications can be used to treat different causes of painful shoulder. Intra-articular injections are applied to treat acromioclavicular osteoarthritis as well as glenohumeral joint osteoarthritis and adhesive capsulitis. Subacromial-subdeltoid bursitis, either presenting as a primary inflammatory condition or secondary to rotator cuff disorders, can be easily approached using ultrasound guidance to aspirate synovial effusion and to inject medications. Ultrasound-guided percutaneous irrigation is a well-established technique increasingly applied to treat patients with rotator cuff calcific tendinopathy. Also, degenerative rotator cuff tendinopathy can be conservatively treated by image-guided interventions, specifically with needling under ultrasound guidance that can be associated with injections of platelet-rich plasma. Lastly, periarticular peripheral nerve block can be quickly and safely performed under ultrasound guidance, particularly in conditions involving the suprascapular nerve in the setting of pre-operative analgesia or pain treatment in glenohumeral osteoarthritis and adhesive capsulitis. In this article, the most common ultrasound-guided procedures around the shoulder have been reviewed to discuss indications and techniques.

Ultrasound-guided musculoskeletal interventional procedures around the elbow, hand and wrist excluding carpal tunnel procedures

Ultrasound is a fast, reliable and radiation-free method for the assessment of a wide range of pathological conditions, as well as for the guidance of percutaneous interventional procedures around the elbow, hand and wrist. Intraarticular and periarticular interventional procedures can be easily performed under continuous ultrasound monitoring to ensure correct needle positioning and medication delivery to a specific target. The most common ultrasound-guided procedures performed around the elbow, wrist, and hand are described in this review, excluding carpal tunnel procedures. Specifically, elbow steroid injections are performed in patients with inflammatory disorders, while hyaluronic acid can be administered in case of osteoarthritis. Septic olecranon bursitis requires percutaneous drainage for diagnosis and appropriate treatment. Dry needling and injection of regenerative medications, such as blood derivatives, are among the treatment options for lateral epicondylosis. Steroid injections are performed to give symptom relief in patients with ulnar neuropathy at the elbow. Hand and wrist steroid injections are performed in case of osteoarthritis, subsequently followed by hyaluronic acid injections, and in inflammatory disorders. Wrist ganglia can be safely aspirated and injected with steroids under ultrasound guidance. De Quervain’s tenosynovitis and trigger finger are chronic tenosynovitides of the wrist and digits, respectively, which can be treated with steroid injections, subsequently followed by hyaluronic acid injections. In conclusion, proper knowledge of the musculoskeletal disorders around the elbow, hand and wrist, as well as US-guided treatment options and operator training, are prerequisites to achieve good outcomes.

Machine Learning to Predict In-Hospital Mortality in COVID-19 Patients Using Computed Tomography-Derived Pulmonary and Vascular Features

Pulmonary parenchymal and vascular damage are frequently reported in COVID-19 patients and can be assessed with unenhanced chest computed tomography (CT), widely used as a triaging exam. Integrating clinical data, chest CT features, and CT-derived vascular metrics, we aimed to build a predictive model of in-hospital mortality using univariate analysis (Mann-Whitney U test) and machine learning models (support vectors machines (SVM) and multilayer perceptrons (MLP)). Patients with RT-PCR-confirmed SARS-CoV-2 infection and unenhanced chest CT performed on emergency department admission were included after retrieving their outcome (discharge or death), with an 85/15% training/test dataset split. Out of 897 patients, the 229 (26%) patients who died during hospitalization had higher median pulmonary artery diameter (29.0 mm) than patients who survived (27.0 mm, p < 0.001) and higher median ascending aortic diameter (36.6 mm versus 34.0 mm, p < 0.001). SVM and MLP best models considered the same ten input features, yielding a 0.747 (precision 0.522, recall 0.800) and 0.844 (precision 0.680, recall 0.567) area under the curve, respectively. In this model integrating clinical and radiological data, pulmonary artery diameter was the third most important predictor after age and parenchymal involvement extent, contributing to reliable in-hospital mortality prediction, highlighting the value of vascular metrics in improving patient stratification.

Pulley, Flexor, and Extensor Tendon Injuries of the Hand

Tendon injuries represent the second most common injury of the hand (after fractures) and are a common scanning indication in radiology. Pulley injuries are very frequent in rock climbers with the A2 pulley the most commonly affected. Tendon and pulley injuries can be reliably evaluated using ultrasound (US) and magnetic resonance imaging (MRI). US can be postulated as a first-line imaging modality, allowing dynamic examination. MRI is essential for cases with ongoing diagnostic doubt post-US and also for preoperative pulley reconstruction assessment.

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

Background

Feature reproducibility and model validation are two main challenges of radiomics. This study aims to systematically review radiomic feature reproducibility and predictive model validation strategies in studies dealing with CT and MRI radiomics of bone and soft-tissue sarcomas. The ultimate goal is to promote achieving a consensus on these aspects in radiomic workflows and facilitate clinical transferability.

Results

Out of 278 identified papers, forty-nine papers published between 2008 and 2020 were included. They dealt with radiomics of bone (n = 12) or soft-tissue (n = 37) tumors. Eighteen (37%) studies included a feature reproducibility analysis. Inter-/intra-reader segmentation variability was the theme of reproducibility analysis in 16 (33%) investigations, outnumbering the analyses focused on image acquisition or post-processing (n = 2, 4%). The intraclass correlation coefficient was the most commonly used statistical method to assess reproducibility, which ranged from 0.6 and 0.9. At least one machine learning validation technique was used for model development in 25 (51%) papers, and K-fold cross-validation was the most commonly employed. A clinical validation of the model was reported in 19 (39%) papers. It was performed using a separate dataset from the primary institution (i.e., internal validation) in 14 (29%) studies and an independent dataset related to different scanners or from another institution (i.e., independent validation) in 5 (10%) studies.

Conclusions

The issues of radiomic feature reproducibility and model validation varied largely among the studies dealing with musculoskeletal sarcomas and should be addressed in future investigations to bring the field of radiomics from a preclinical research area to the clinical stage.

CT-derived Chest Muscle Metrics for Outcome Prediction in Patients with COVID-19

Background Lower muscle mass is a known predictor of unfavorable outcomes, but its prognostic impact on patients with COVID-19 is unknown. Purpose To investigate the contribution of CT-derived muscle status in predicting clinical outcomes in patients with COVID-19. Materials and Methods Clinical or laboratory data and outcomes (intensive care unit [ICU] admission and death) were retrospectively retrieved for patients with reverse transcriptase polymerase chain reaction-confirmed SARS-CoV-2 infection, who underwent chest CT on admission in four hospitals in Northern Italy from February 21 to April 30, 2020. The extent and type of pulmonary involvement, mediastinal lymphadenopathy, and pleural effusion were assessed. Cross-sectional areas and attenuation by paravertebral muscles were measured on axial CT images at the T5 and T12 vertebral level. Multivariable linear and binary logistic regression, including calculation of odds ratios (ORs) with 95% CIs, were used to build four models to predict ICU admission and death, which were tested and compared by using receiver operating characteristic curve analysis. Results A total of 552 patients (364 men and 188 women; median age, 65 years [interquartile range, 54-75 years]) were included. In a CT-based model, lower-than-median T5 paravertebral muscle areas showed the highest ORs for ICU admission (OR, 4.8; 95% CI: 2.7, 8.5; P < .001) and death (OR, 2.3; 95% CI: 1.0, 2.9; P = .03). When clinical variables were included in the model, lower-than-median T5 paravertebral muscle areas still showed the highest ORs for both ICU admission (OR, 4.3; 95%: CI: 2.5, 7.7; P < .001) and death (OR, 2.3; 95% CI: 1.3, 3.7; P = .001). At receiver operating characteristic analysis, the CT-based model and the model including clinical variables showed the same area under the receiver operating characteristic curve (AUC) for ICU admission prediction (AUC, 0.83; P = .38) and were not different in terms of predicting death (AUC, 0.86 vs AUC, 0.87, respectively; P = .28). Conclusion In hospitalized patients with COVID-19, lower muscle mass on CT images was independently associated with intensive care unit admission and in-hospital mortality. © RSNA, 2021 Online supplemental material is available for this article.

Recent advancement on PD-L1 expression quantification: the radiologist perspective on CT-guided FNAC

PURPOSE

We aimed to evaluate the feasibility, accuracy, and safety of Programmed Death-1/ Programmed Death-Ligand 1 (PD-1/ PD-L1) expression quantification in cytology cell-block samples obtained through transthoracic CT-guided fine-needle aspiration cytology (FNAC) from the interventional radiologist's perspective.

METHODS

We performed a consecutive unselected series of 361 CT-guided biopsies of pulmonary nodules and masses which came to our observation from June 2017 to October 2018. For each case, exhaustive clinical, morphologic, molecular and tomographic data were available. All the material obtained was fixed in formalin to obtain a cell-block for the pathologist, who performed immunohistochemical analysis to detect PD-L1 expression levels on each sample.

RESULTS

Of all the analyzed samples, 93.6% (338/361) were defined to be diagnostic, including neoplastic (72%, 260/361) and non-neoplastic lesions (21.6%, 78/361); only 6.4% (23/361) of them resulted in nondiagnostic specimens. Non-small cell lung cancer (NSCLC) accounted for 73.8% of neoplastic lesions (192/260): most of them were adenocarcinoma (83%, 160/192), followed by squamous carcinoma (14%, 27/192) and poorly differentiated carcinoma (3%, 5/192). In 96% of NSCLC (184/192), the diagnosis was reached either in the absence of complications or with early minor complications. PD-L1 expression was evaluated in all 192 NSCLC cytology specimens: 180 immunostainings were found to be adequate for PD-L1 testing. In 76% of cases, PD-L1 expression level was lower than 50%.

CONCLUSION

The findings of our study indicate that PD-L1 quantification using a cell-block approach on CT-guided FNAC is a feasible and safe technique and should be taken into account alongside with core biopsy approach, especially in case of advanced disease and/or fragile and older patients.

Radiomic Machine Learning Classifiers in Spine Bone Tumors: A Multi-Software, Multi-Scanner Study

PURPOSE

Spinal lesion differential diagnosis remains challenging even in MRI. Radiomics and machine learning (ML) have proven useful even in absence of a standardized data mining pipeline. We aimed to assess ML diagnostic performance in spinal lesion differential diagnosis, employing radiomic data extracted by different software.

METHODS

Patients undergoing MRI for a vertebral lesion were retrospectively analyzed (n = 146, 67 males, 79 females; mean age 63 ± 16 years, range 8-89 years) and constituted the train (n = 100) and internal test cohorts (n = 46). Part of the latter had additional prior exams which constituted a multi-scanner, external test cohort (n = 35). Lesions were labeled as benign or malignant (2-label classification), and benign, primary malignant or metastases (3-label classification) for classification analyses. Features extracted via 3D Slicer heterogeneityCAD module (hCAD) and PyRadiomics were independently used to compare different combinations of feature selection methods and ML classifiers (n = 19).

RESULTS

In total, 90 and 1548 features were extracted by hCAD and PyRadiomics, respectively. The best feature selection method-ML algorithm combination was selected by 10 iterations of 10-fold cross-validation in the training data. For the 2-label classification ML obtained 94% accuracy in the internal test cohort, using hCAD data, and 86% in the external one. For the 3-label classification, PyRadiomics data allowed for 80% and 69% accuracy in the internal and external test sets, respectively.

CONCLUSIONS

MRI radiomics combined with ML may be useful in spinal lesion assessment. More robust pre-processing led to better consistency despite scanner and protocol heterogeneity.

Disruption of bone densitometry practice in a Northern Italy Orthopedic Hospital during the COVID-19 pandemic

We report the impact of the COVID-19 pandemic on bone densitometry practice in a Northern Italy Orthopedic Hospital, comparing the first 4 months of 2020 with the corresponding period of 2019. COVID-19 pandemic had a disruptive effect on the daily practice of bone densitometry (about - 50% of examinations).

INTRODUCTION

The Coronavirus Disease 2019 (COVID-19) pandemic radically changes hospital organization to guarantee patient and staff safety, with the unavoidable cessation of normal outpatient activities. We report the impact of the COVID-19 pandemic on dual energy x-ray absorptiometry (DXA) testing in a Northern Italy Orthopedic Hospital.

METHODS

We analyzed the number of DXA examinations performed at our Institution before, during the lockdown, and immediately after outpatient practice reopening (January 24th to May 27th, 2020), comparing them with the corresponding period of 2019.

RESULTS

The number of DXA examinations showed a tremendous reduction from n = 1247 performed from January to May 2019 to n = 623 of 2020 (- 49.9%). No exams were performed in April 2020 (- 100%). On May 2020, a faint resume was observed, with n = 43 DXA (- 84.4% compared to 2019).

CONCLUSION

COVID-19 pandemic had a disruptive effect on the daily practice of bone densitometry with DXA. After reopening, we observed a persistence of DXA examination reduction, confirming the fact that returning to normality will probably be a slow process.

Imaging of calcific tendinopathy around the shoulder: usual and unusual presentations and common pitfalls

Rotator cuff calcific tendinopathy (RCCT) is a very common condition, characterized by calcium deposition over fibrocartilaginous metaplasia of tenocytes, mainly occurring in the supraspinatus tendon. RCCT has a typical imaging presentation: in most cases, calcific deposits appear as a dense opacity around the humeral head on conventional radiography, as hyperechoic foci with or without acoustic shadow at ultrasound and as a signal void at magnetic resonance imaging. However, radiologists have to keep in mind the possible unusual presentations of RCCT and the key imaging features to correctly differentiate RCCT from other RC conditions, such as calcific enthesopathy or RC tears. Other presentations of RCCT to be considered are intrabursal, intraosseous, and intramuscular migration of calcific deposits that may mimic infectious processes or malignancies. While intrabursal and intraosseous migration are quite common, intramuscular migration is an unusual evolution of RCCT. It is important also to know atypical regions affected by calcific tendinopathy as biceps brachii, pectoralis major, and deltoid tendons. Unusual presentations of RCCT may lead to diagnostic challenge and mistakes. The aim of this review is to illustrate the usual and unusual imaging findings of RCCT that radiologists should know to reach the correct diagnosis and to exclude other entities with the purpose of preventing further unnecessary imaging examinations or interventional procedures.