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Considering the current widespread use of imaging as an integral part of managing hip pain, variable hip geometries and anatomical variants are increasingly being detected. These variants are commonly found in the acetabulum and proximal femur, as well as the surrounding capsule-labral tissues. The morphology of specific anatomical spaces confined by the proximal femur and the bony pelvis may also vary significantly among individuals. Familiarity with the spectrum of imaging appearances of the hip is necessary to identify variant hip morphologies with or without potential clinical relevance and reduce an unnecessary work-up and overdiagnosis. We describe anatomical variations and variable morphologies of the bony structures comprising the hip joint and the soft tissues, around the hip. The potential clinical significance of these findings is further analyzed in conjunction with the patient's profile.

The increasing evidence of oncocytic renal tumors positive in 99mTc Sestamibi Single Photon Emission Tomography/Computed Tomography (SPECT/CT) examination calls for the development of diagnostic tools to differentiate these tumors from more aggressive forms. This study combined radiomics analysis with the uptake of 99mTc Sestamibi on SPECT/CT to differentiate benign renal oncocytic neoplasms from renal cell carcinoma. A total of 57 renal tumors were prospectively collected. Histopathological analysis and radiomics data extraction were performed. XGBoost classifiers were trained using the radiomics features alone and combined with the results from the visual evaluation of 99mTc Sestamibi SPECT/CT examination. The combined SPECT/radiomics model achieved higher accuracy (95%) with an area under the curve (AUC) of 98.3% (95% CI 93.7–100%) than the radiomics-only model (71.67%) with an AUC of 75% (95% CI 49.7–100%) and visual evaluation of 99mTc Sestamibi SPECT/CT alone (90.8%) with an AUC of 90.8% (95%CI 82.5–99.1%). The positive predictive values of SPECT/radiomics, radiomics-only, and 99mTc Sestamibi SPECT/CT-only models were 100%, 85.71%, and 85%, respectively, whereas the negative predictive values were 85.71%, 55.56%, and 94.6%, respectively. Feature importance analysis revealed that 99mTc Sestamibi uptake was the most influential attribute in the combined model. This study highlights the potential of combining radiomics analysis with 99mTc Sestamibi SPECT/CT to improve the preoperative characterization of benign renal oncocytic neoplasms. The proposed SPECT/radiomics classifier outperformed the visual evaluation of 99mTc Sestamibii SPECT/CT and the radiomics-only model, demonstrating that the integration of 99mTc Sestamibi SPECT/CT and radiomics data provides improved diagnostic performance, with minimal false positive and false negative results.

The future of musculoskeletal (MSK) radiology is being built on research developments in the field. Over the past decade, MSK imaging research has been dominated by advancements in molecular imaging biomarkers, artificial intelligence, radiomics, and novel high-resolution equipment. Adequate preparation of trainees and specialists will ensure that current and future leaders will be prepared to embrace and critically appraise technological developments, will be up to date on clinical developments, such as the use of artificial tissues, will define research directions, and will actively participate and lead multidisciplinary research. This review presents an overview of the current MSK research landscape and proposes tangible future goals and strategic directions that will fortify the future of MSK radiology.

To propose a new method of simulating the BOLD contrast using a dynamic, easy to construct and operate, low-cost physical phantom. A structure of thin pipelines passing through a gel volume was used to simulate blood vessels in human tissue. Quantitative T2*, R2* measurements were used to study the signal change of the phantom. BOLD fMRI experiments and analysis were performed to evaluate its potential use as an fMRI simulator. Experimental T2*, R2* measurements showed similar behavior with published references. BOLD contrast was successfully achieved with the proposed method. In addition, there were several proposed parameters, like the angle of the phantom relative to B0, which can easily adjust the signal change and the activation area. Coefficients of variation showed good reproducibility within a month period. Statistical t maps were produced with in-house software for the BOLD measurements. T2*maps and BOLD images confirm the potential use of this phantom as an fMRI simulator and also as a tool for studying sensitivity and specificity of BOLD sequences/algorithms.

Wrist osteoarthritis (OA) is a common painful condition that affects the patient’s quality of life by limiting the range of wrist motion and grip strength. Wrist OA often results from scapholunate advanced collapse (SLAC) or scaphoid nonunion advanced collapse (SNAC). Early diagnosis of SLAC and SNAC is crucial because it affects treatment planning. Thus, radiologists should be able to interpret the early imaging findings. This pictorial review discusses the pathophysiology and the clinical symptoms of SLAC and SNAC and presents the imaging findings with emphasis on the proper imaging algorithm. Finally, it focuses on the treatment according to the degenerative status of each of these patterns.

OBJECTIVES In this study, we sought to assess the validity of lung ultrasound (LUS) during the follow-up of patients with a wide spectrum of interstitial lung diseases (ILDs). METHODS Twenty-four patients (13 males, 11 females; mean age ± SD, 65.4 ± 14.3 years; age range, 40-84 years) with a diagnosis of ILDs who were admitted to the Interstitial Lung Disease Unit were prospectively enrolled. Patients were examined with a 56-lung intercostal space LUS protocol in lateral decubitus position, at baseline, 6-months, and 1-year. The LUS score was defined as the sum of B-lines counted in each intercostal space. All patients underwent complete pulmonary function tests at baseline and follow-up time-points. High-resolution computed tomography (HRCT) was performed at baseline and during follow-up, according to personalized patients' needs. All HRCT studies were graded according to the Warrick scoring system (WS). RESULTS Pooled data analysis showed a significant correlation between WS and LUS scores (P

PURPOSE This study aims to provide data, with the use of computed tomography angiography, regarding the level of bifurcation of the peroneal artery to the anterior perforating branch and the lateral calcaneal branch, in relation to the osseous anatomic structures of the tibial plafond, the medial malleolus and the lateral malleolus. METHODS The study included patients who underwent diagnostic computed tomography angiography of the lower extremities. Measurements were performed in two-dimensional reconstructions and included the perpendicular distance from peroneal artery bifurcation into anterior perforating branch and lateral calcaneal branch to the lowest level of tibial plafond (D1), medial malleolus (D2) and lateral malleolus (D3). The distances were also normalized to the length of the tibia. RESULTS Sixty patients and a total of 115 limbs were enrolled in this study. The mean distance ± standard deviation from peroneal artery bifurcation to tibial plafond (D1) was 4.33 ± 1.12 cm (normalized 0.12 ± 0.03) (range 2.54-8.26 cm), to medial malleolus (D2) was 5.53 ± 1.18 cm (normalized 0.16 ± 0.03) (range 3.27-9.5 cm) and to lateral malleolus (D3) was 6.53 ± 1.17 cm (normalized 0.18 ± 0.03) (range 4.71-10.2 cm), respectively. There was no significant difference between right and left limb measurements (p > 0.05). Females presented lower, but not statistically significant (p > 0.05), D1, D2 and D3 measurements compared to males. CONCLUSION The bifurcation of the peroneal artery takes place at lower level compared to previously published studies and consequently extreme caution should be exercised when performing the posterolateral approach to the ankle. This study adds to the understanding of the relevant vascular anatomy of the region and assists in performing the posterolateral approach to the ankle with safety.

Colorectal cancer (CRC) constitutes the third most commonly diagnosed cancer in males and the second in females. Precise histopathological classification of CRC tissue pathology is the cornerstone not only for diagnosis but also for patients’ management decision making. An automated system able to accurately classify different CRC tissue regions may increase diagnostic precision and alleviate clinical workload. However, tissue classification is a challenging task due to the variability in morphological and textural characteristics present in histopathology images. In this study, an artificial neural network was trained to classify between eight classes of CRC tissue image patches derived from a public dataset with 5000 CRC histopathology image tiles. A total of 532 multi-level pathomics features examined at different scales were extracted by visual descriptors such as local binary patterns, wavelet transforms and Gabor filters. An exhaustive evaluation involving a variety of wavelet families and parameters was performed in order to shed light on the impact of scale on pathomics based CRC tissue differentiation. Our model achieved a performance accuracy of 95.3% with tenfold cross validation demonstrating superior performance compared to 87.4% reported in recent studies. Furthermore, we experimentally showed that the first and the second levels of the wavelet approximations can be used without compromising classification performance.

An adult man presented with a 5-month history of anterior right shoulder pain. He denied previous trauma or night pain. On the otherwise normal physical examination, pain was elicited in maximum abduction and external rotation. Radiographs were negative. The primary imaging findings were bone marrow oedema of the inferomedial proximal metaphysis of the humerus on MRI and cortical demineralisation on CT located posteromedially. A superficial elevation was also observed around the lesion. A provisional diagnosis of an osteoid osteoma was made based on these imaging findings. Arthroscopic excision of the lesion was performed, and histopathological examination confirmed the diagnosis of an osteoid osteoma. Diagnosis of intra-articular osteoid osteomas may be challenging due to atypical symptomatology and lack of pathognomonic imaging findings. Arthroscopic excision of such lesions in the shoulder is a safe and reliable option and should be considered as the treatment of choice.

To compare the additive value of immediate post-procedural manipulation versus physiotherapy, following ultrasound (US)-guided hydrodistention of the glenohumeral joint (GHJ) in patients with adhesive capsulitis (AC) and define predictors of outcome.Within a 19-month period, 161 consecutive patients with AC were prospectively enrolled and allocated to two groups according to treatment, based on patients' individual preferences: 1) group-I, US-guided hydrodistension plus immediate post-procedural manipulations and 2) group-II, US-guided hydrodistension plus supervised physiotherapy program. The Disabilities of the Arm, Shoulder, and Hand (DASH) questionnaire and a visual analog scale (VAS) were used for clinical assessment at baseline (immediately after treatment), 1, 3, and 6 months. Comparisons were performed with Mann-Whitney U test and Kolmogorov-Smirnov test. Linear regression was used to identify predictors of outcome. P value.05 defined significance.GHJ hydrodistension with manipulation or physiotherapy was linked to clinical improvement at all follow-up time-points. DASH scores of group-I remained constantly lower than DASH scores of group-II at all time-points (P .001). VAS scores were lower in group-I than group-II at 1 and 3 months (P .001 and P = .0019, respectively). Both groups had improved to a similar degree with respect to pain at 6 months (P = .29). The performance of post-interventional manipulations was predictive of improved shoulder functionality (as assessed with DASH scores) at all time-points, while low-grade disease and milder symptoms at presentation were associated with improved short-term pain.Immediate post-procedural manipulations appeared to be superior to physiotherapy following GHJ hydrodistension for AC in terms of shoulder functionality during a 6-month follow-up period. Post-interventional manipulations, the stage of AC and lower DASH and VAS scores at presentations were predictive of improved outcome.

Achilles tendinopathy is a common overuse condition affecting the adult population. The incidence is on the rise because of greater participation of people in recreational or competitive sporting activities. Chronic Achilles tendinopathy occurs most commonly in the tendon’s mid-portion, and it is challenging to manage, leading to significant patient morbidity. Despite conservative management many patients still require surgical intervention. The mechanism underlying pain is not entirely understood; however, high-resolution color Doppler ultrasound has shown that neovascularisation could be involved. Minimally-invasive treatments for chronic Achilles tendinopathy may prevent the need for surgery when conservative methods have failed. Ultrasound provides an option to guide therapeutic interventions accurately, so that treatment is delivered to the desired site of pathology. High-volume image-guided injection is a relatively new technique where a high volume of liquid is injected between the anterior aspect of the Achilles tendon and the Kager’s fat pad, used to strip away the neovascularity and disrupt the nerve ingrowth seen in chronic cases of Achilles tendinopathy. Highvolume image-guided injection has shown promising results in terms of reducing pain and improving function in patients where conservative measures have failed. This review aims to describe the fundamental technical factors, and investigate the efficacy of high-volume image-guided injection with reference to the available literature.

To identify prognostic factors affecting the clinical outcome in patients treated with rotator cuff ultrasound-guided percutaneous irrigation of calcific tendinopathy (US-PICT), by evaluating the degree of calcium removal, the size and consistency of calcific deposits, and baseline level of shoulder pain and functionality. From January 2017 to December 2019, 79 patients (23 males, 56 females; mean age, 45.7 years) who underwent US-PICT were prospectively enrolled. The calcifications’ location, consistency, and size were evaluated. For US-PICT, local anesthesia, lavage of calcific material, and intrabursal steroid injection were performed. The degree of calcium removal was graded as total/partial. Shoulder pain and functionality were assessed with the visual analogue scale (VAS) in all and Constant score (CS) in a subset of patients, respectively, at 4 time-points. Mann-Whitney U test, Fisher’s test, and linear and binary logistic regression were utilized for analysis. Pain improvement correlated with the presence of larger calcifications and lower baseline VAS score, at 1 week (p = 0.001, p < 0.001, respectively) and 1 year (p < 0.001, p = 0.002, respectively). Improved functionality correlated with total calcification retrieval, higher baseline CS, and fluid/soft calcific consistency at 1 week (p = 0.013, p = 0.003, p = 0.019, respectively). Increased calcification size, cystic appearance, and lower baseline VAS scores independently predicted complete pain resolution at 1 year. Large calcifications and low-grade pain at baseline correlated with short- and long-term pain improvement. The degree of calcium removal did not impact pain or functional improvement beyond 1 week. Increased calcification size, cystic appearance, and low-grade baseline pain predicted complete pain recovery at 1 year. • The presence of larger calcifications and lower-grade baseline pain appear to correlate with pain improvement at 1 week and 1 year after ultrasound-guided irrigation of rotator cuff calcific tendinopathy (US-PICT). • Total calcification retrieval, less affected baseline shoulder functionality, and presence of fluid/soft consistency of calcific deposits appear to correlate with improved shoulder functionality at 1 week post-treatment. • Baseline pain intensity and calcifications’ morphologic characteristics, but not the degree of calcium retrieval, represent predictors of complete pain recovery at 1 year after US-PICT.

Subchondral insufficiency fractures (SIF) and advanced osteoarthritis (OA) of the knee are usually seen in conjunction with bone marrow lesions (BMLs) and their differentiation may pose a significant diagnostic challenge. We aimed to develop a convolutional neural network (CNN) ensemble which could successfully differentiate between these two entities.A total of 212 knees with SIF and 102 knees with advanced OA with BMLs were retrospectively included. Coronal fat suppressed PD-w images were augmented, resized and normalized, reaching a total of 1174 images. Data was used to fine-tune three ImageNet-pretrained CNNs (VGG-16, InceptionV3 and Inception-ResNet-V2). Agreement of at least two networks was recorded as the decision of the network ensemble. Ensemble performance was compared to that of two MSK radiologists on the validation set. Receiver operating characteristics (ROC) curves and the respective areas under the curve (AUC) were used to evaluate human and machine performance.InceptionV3 achieved the highest AUC (93.68%) and VGG-16 the lowest AUC (82.18%) among individual CNNs. CNN ensemble achieved the highest overall performance with an AUC of 95.97%. The first of the two MSK radiologists achieved a performance similar to the ensemble, reaching an AUC of 91.95%. The second radiologist achieved lower AUC of 82.76% which was lower than both the other specialist and the ensemble (P 0.001).A CNN ensemble was highly accurate in differentiating between SIF and OA, achieving a higher or equal performance to MSK radiologists.

Purpose The aim of this study is to introduce a novel DWI-MRI phantom and to compare Apparent Diffusion Coefficient (ADC) measurements, utilizing EPI-DWI and HASTE-DWI sequences and two different fitting algorithms. Materials and Methods 23 test tubes with different sucrose concentrations and polyacrylamide gels were used as a phantom for ADC measurements. The phantom was scanned on a clinical MRI system (1.5 T) over a two-month period utilizing an EPI-DWI and a HASTE-DWI sequence. ADC maps were calculated using a Weighted Linear (WL) and a Non Linear (NL) fitting algorithm. Measurements were performed with two sequences and two fitting algorithms. Geometric Distortions (GD), Ghosting Ratios (GR) and Signal to Structured Noise Ratios (SSNRs) were estimated using both sequences from the resultant ADC parametric maps. Results Polyacrylamide gels reveal lower coefficient of variation (CV%) as compared to sucrose solutions. ADC measurements performed with WL and NL algorithms reveal identical results with both sequences. WL and NL algorithms require approx. 3 s and 7 min respectively, for a single slice. EPI-DWI reveals a mean percent ADC value difference of (+4.5%) as compared to HASTE-DWI, regardless the type of fitting algorithm. Conclusion Polyacrylamide gels can serve as a better means for simulating ADC values, compared with sucrose solutions used in this study. WL can be proposed as the method for ADC measurements in daily clinical practice. WL is significantly faster than NL fitting method and equally precise. SSNR measured directly on ADC maps is an excellent means for testing the precision of ADC measurements.

Background The inverse Laplace transform (ILT) is the most widely used method for T2 relaxometry data analysis. This study examines the qualitative agreement of ILT and a proposed multiexponential (Mexp method) regarding the number of T2 components. We performed a feasibility study for the voxelwise characterisation of heterogeneous tissue with T2 relaxometry. Methods Eleven samples of aqueous, fatty and mixed composition were analysed using ILT and Mexp. The phantom was imaged using a 1.5-T system with a single slice T2 relaxometry 25-echo Carr-Purcell-Meiboom-Gill sequence in order to obtain the T2 decay curve with 25 equidistant echo times. The adjusted R2 goodness of fit criterion was used to determine the number of T2 components using the Mexp method on a voxel-based analysis. Comparison of mean and standard deviation of T2 values for both methods was performed by fitting a Gaussian function to the ILT resulting vector. Results Phantom results showed pure monoexponential decay for acetone and water and pure biexponential behaviour for corn oil, egg yolk, and 35% fat milk cream, while mixtures of egg whites and yolks as well as milk creams with 12–20% fatty composition exhibit mixed monoexponential and biexponential behaviour at different fractions. The number of T2 components by the Mexp method was compared to the ILT-derived spectrum as ground truth. Conclusions Mexp analysis with the adjusted R2 criterion can be used for the detection of the T2 distribution of aqueous, fatty and mixed samples with the added advantage of voxelwise mapping.

The purpose of this study was to compare the measurement of several anatomical features of the medial patellofemoral ligament (MPFL) between magnetic resonance imaging (MRI) and by direct fashion during dissection. We hypothesized that the measurements between these two techniques would agree. MRI of 30 fresh-frozen cadaveric knees was followed by dissection. MPFL patella and femoral attachment were evaluated, their shape, length, and width were measured, and measurements were compared. MRI was deemed unreliable for the determination of several of the aforementioned anatomical features. Important findings include: (a) observations on MPFL attachment at medial patella side and attachment to quadriceps were identical between dissection and MRI, (b) average width at patella insertion was significantly different between the two methods (p = 0.002), and (c) an attachment to the quadriceps tendon was present in 20/30 specimens and d. detailed measurements of a thin, non-linear, and three-dimensional structure, such as the MPFL, cannot be performed on MRI, due to technical difficulties. This anatomical radiological study highlights the shape, anatomical measurements (length and width), and attachment of the MPFL using a relatively large cadaveric sample and suggests that MRI is not reliable for detailed imaging of its three-dimensional anatomy.

The radiologists were traditionally working in the background. What upgraded them as physicians during the second half of the past century was their clinical training and function precipitated by the evolution of Interventional Radiology and Medical Imaging, especially with ultrasonography. These allowed them to participate in patient's diagnosis and treatment by direct contact as well asvia multidisciplinary medical consultations. The wide application of teleradiology and PACS pushed radiologists back again which is no longer acceptable, especially in view of the amazing applications of artificial intelligence (AI) in Radiology. It is our belief that clinical radiologists have to be able to control the penetration of AI in Radiology, securing their work for the benefit of both clinicians and patients.

Differentiation between transient osteoporosis (TOH) and avascular necrosis (AVN) of the hip is a longstanding challenge in musculoskeletal radiology. The purpose of this study was to utilize MRI-based radiomics and machine learning (ML) for accurate differentiation between the two entities. A total of 109 hips with TOH and 104 hips with AVN were retrospectively included. Femoral heads and necks with segmented radiomics features were extracted. Three ML classifiers (XGboost, CatBoost and SVM) using 38 relevant radiomics features were trained on 70% and validated on 30% of the dataset. ML performance was compared to two musculoskeletal radiologists, a general radiologist and two radiology residents. XGboost achieved the best performance with an area under the curve (AUC) of 93.7% (95% CI from 87.7 to 99.8%) among ML models. MSK radiologists achieved an AUC of 90.6% (95% CI from 86.7% to 94.5%) and 88.3% (95% CI from 84% to 92.7%), respectively, similar to residents. The general radiologist achieved an AUC of 84.5% (95% CI from 80% to 89%), significantly lower than of XGboost (p = 0.017). In conclusion, radiomics-based ML achieved a performance similar to MSK radiologists and significantly higher compared to general radiologists in differentiating between TOH and AVN.

Background Anterior knee instability is usually encountered in the context of trauma, with the clinical examination and imaging focusing on anterior cruciate ligament (ACL) disruption. Limited data exist on magnetic resonance imaging (MRI) of acute anterior knee instability in the absence of recent trauma. Purpose To provide the first comprehensive account of MRI findings in acute anterior knee laxity in the absence of acute trauma and to evaluate predictors of ACL integrity and pain. Material and Methods A total of 84 consecutive patients with non-traumatic knee instability were prospectively studied. Instability was assessed with Lachman’s, pivot shift, and Lelli’s tests. MRI findings were recorded, and ACL integrity was surgically confirmed in all 24 cases of MRI suggesting tear and in 21/60 cases of MRI suggesting no tear. Binary logistic regression models were used to identify predictors of ACL tears and pain, and Mann–Whitney U test served for comparisons between continuous variables. The study was approved by the institutional review board. Results Osteoarthritis and notch bony outgrowth (NBO) were present in 44% and 42.9% of all knees, respectively. NBO did not correlate with osteoarthritis ( P = 0.606). NBO (odds ratio [OR] = 4.157; P = 0.016) and ACL grafts (OR = 9.277; P = 0.01) predisposed to non-traumatic ACL tears (torn in 28.6% of total cases). Presence of osteoarthritis was predictive of pain (OR = 17.671; P Conclusion We present a comprehensive analysis of MRI findings in clinically significant non-traumatic anterior instability, showing that NBO and ACL grafts predispose in non-traumatic ACL tears, whereas osteoarthritis is the only predictor of pain.

Computer-aided diagnosis systems aim to assist clinicians in the early identification of abnormal signs in order to optimize the interpretation of medical images and increase diagnostic precision. Multiple sclerosis (MS) and clinically isolated syndrome (CIS) are chronic inflammatory, demyelinating diseases affecting the central nervous system. Recent advances in deep learning (DL) techniques have led to novel computational paradigms in MS and CIS imaging designed for automatic segmentation and detection of areas of interest and automatic classification of anatomic structures, as well as optimization of neuroimaging protocols. To this end, there are several publications presenting artificial intelligence-based predictive models aiming to increase diagnostic accuracy and to facilitate optimal clinical management in patients diagnosed with MS and/or CIS. The current study presents a thorough review covering DL techniques that have been applied in MS and CIS during recent years, shedding light on their current advances and limitations.

Background Persistent type 2 endoleaks (T2EL) require lifelong surveillance to avoid potentially life-threatening complications. Purpose To evaluate the performance of radiomic features (RF) derived from computed tomography angiography (CTA), for differentiating aggressive from benign T2ELs after endovascular aneurysm repair (EVAR). Material and Methods A prospective study was performed on patients who underwent EVAR from January 2018 to January 2020. Analysis was performed in patients who were diagnosed with T2EL based on the CTA of the first postoperative month and were followed at six months and one year. Patients were divided into two groups according to the change of aneurysm sac dimensions. Segmentation of T2ELs was performed and RF were extracted. Feature selection for subsequent machine-learning analysis was evaluated by means of artificial intelligence. Two support vector machines (SVM) classifiers were developed to predict the aneurysm sac dimension changes at one year, utilizing RF from T2EL at one- and six-month CTA scans, respectively. Results Among the 944 initial RF of T2EL, 58 and 51 robust RF from the one- and six-month CTA scans, respectively, were used for the machine-learning model development. The SVM classifier trained on one-month signatures was able to predict sac expansion at one year with an area under curve (AUC) of 89.3%, presenting 78.6% specificity and 100% sensitivity. Similarly, the SVM classifier developed with six-month radiomics data showed an AUC of 95.5%, specificity of 90.9%, and sensitivity of 100%. Conclusion Machine-learning algorithms utilizing CTA-derived RF may predict aggressive T2ELs leading to aneurysm sac expansion after EVAR.

The aim of this study was to define lower dose parameters (tube load and temporal sampling) for CT perfusion that still preserve the diagnostic efficiency of the derived parametric maps. Ninety stroke CT examinations from four clinical sites with 1 s temporal sampling and a range of tube loads (mAs) (100–180) were studied. Realistic CT noise was retrospectively added to simulate a CT perfusion protocol, with a maximum reduction of 40% tube load (mAs) combined with increased sampling intervals (up to 3 s). Perfusion maps from the original and simulated protocols were compared by: (a) similarity using a voxel-wise Pearson’s correlation coefficient r with in-house software; (b) volumetric analysis of the infarcted and hypoperfused volumes using commercial software. Pearson’s r values varied for the different perfusion metrics from 0.1 to 0.85. The mean slope of increase and cerebral blood volume present the highest r values, remaining consistently above 0.7 for all protocol versions with 2 s sampling interval. Reduction of the sampling rate from 2 s to 1 s had only modest impacts on a TMAX volume of 0.4 mL (IQR −1–3) (p = 0.04) and core volume of −1.1 mL (IQR −4–0) (p < 0.001), indicating dose savings of 50%, with no practical loss of diagnostic accuracy. The lowest possible dose protocol was 2 s temporal sampling and a tube load of 100 mAs.

Blood Oxygen Level Dependent (BOLD) is a commonly-used MR imaging technique in studying brain function. The BOLD signal can be strongly affected by specific sequence parameters, especially in small field strengths. Previous small-scale studies have investigated the effect of TE on BOLD contrast. This study evaluates the dependence of fMRI results on echo time (TE) during concurrent activation of the visual and motor cortex at 1.5 T in a larger sample of 21 healthy volunteers. The experiment was repeated using two different TE values (50 and 70 ms) in counterbalanced order. Furthermore, T2* measurements of the gray matter were performed. Results indicated that both peak beta value and number of voxels were significantly higher using TE = 70 than TE = 50 ms in primary motor, primary somatosensory and supplementary motor cortices (p &lt, 0.007). In addition, the amplitude of activation in visual cortices and the dorsal premotor area was also higher using TE = 70 ms (p &lt, 0.001). Gray matter T2* of the corresponding areas did not vary significantly. In conclusion, the optimal TE value (among the two studied) for visual and motor activity is 70 ms affecting both the amplitude and extent of regional hemodynamic activation.

To evaluate the performance of two machine learning models in predicting the long-term complete pain resolution in patients undergoing ultrasound-guided percutaneous irrigation of calcific tendinopathy (US-PICT).Within a 3-year period, 100 consecutive patients who underwent US-PICT for rotator cuff disease were prospectively enrolled. The location, maximum diameter, and type of each calcification were recorded. The degree of calcium retrieval was graded as complete or incomplete. Shoulder pain was assessed with the visual analogue scale (VAS) at baseline, 1-week, 1-month, and 1-year post-treatment. Measurements related to procedural details, patient, and calcification characteristics were used to construct a machine learning model for the prediction of pain at 1-year post-US-PICT. Two distinct models were built, one including VAS data at 1 week and another additionally including pain data at 1-month post-treatment. Variable importance analysis was performed for the 1-week model. Model performance was evaluated by using receiver operating characteristics (ROC) curves and the respective areas under the curve (AUC).The model exhibited an AUC of 69.2% for the prediction of complete pain resolution at 1 year. The addition of VAS scores at 1 month did not significantly alter the performance of the algorithm. Age and baseline VAS scores were the most important variables for classification performance.The presented machine learning model exhibited an AUC of almost 70% in predicting complete pain resolution at 1 year. Pain data at 1 month do not appear to improve the performance of the algorithm.

Purpose To measure the safe range of angles during tunnel drilling and map ideal patella tunnel placement with the use of preoperative computed tomography (CT) scan and compare results after medial patellofemoral ligament (MPFL) reconstruction using a hardware-free patellar fixation technique with two semi-patellar tunnels between a) a free-hand technique, and b) its modification with the use of an anterior cruciate ligament (ACL) tibia aiming device. Methods CT scan was performed on 30 fresh-frozen cadaveric knees a) prior to any intervention and b) after MPFL reconstruction. For MPFL reconstruction, specimens were randomly allocated to 1) Group A, which consisted of knees operated with free-hand, hardware-free patellar fixation technique with two semi-patellar tunnels and 2) Group B, which consisted of knees operated on with a technique modification with the ACL tibia device. Patellar measurements L1 was the maximal patellar length. L2 was the minimum possible distance of placement for the upper tunnel from the proximal pole of the patella. The maximum bone bridge between tunnels was calculated as half of L1 minus the L2 distance (L1/2-L2). We also measured R1 and R2 angles at the proximal and distal tunnel that represent safe angles at the entry point during tunnel drilling (without breaching the anterior cortex or articular cartilage). Results Preoperatively, mean L1 was 3.45 cm (range 3.05–4.52). Mean L2 was 0.62 cm (range 0.49–0.89). The mean maximum possible bone bridge between tunnels (L1/2-L2) was 1.1 cm (range 0.77–1.58). R1 was 6.050 (range 4.78–7.44), R2 was 6.640 (range 4.57–9.03), and their difference reached statistical significance (p = 0.03). Postoperatively, in group A, in 4 out of 15 patellas, multiple attempts were made during tunnel drilling in order to avoid anterior cortex or cartilage breaching. In group B, all tunnels were correctly drilled with the first attempt. Bone bridge between tunnels was significantly shorter postoperatively (0.93 cm, p Conclusion Small-size patellae correlate with short maximum bone bridge between tunnels, which makes anatomic, double-bundle, hardware-free patella fixation, with two semi-patellar tunnels MPFL reconstruction challenging. Furthermore, R angles create a narrow window to avoid intraoperative breaching, rendering the use of the ACL tibia device an extremely useful instrument. Level of evidence II