CT in musculoskeletal imaging: still helpful and for what?

Computed tomography (CT) is a common modality employed for musculoskeletal imaging. Conventional CT techniques are useful for the assessment of trauma in detection, characterization and surgical planning of complex fractures. CT arthrography can depict internal derangement lesions and impact medical decision making of orthopedic providers. In oncology, CT can have a role in the characterization of bone tumors and may elucidate soft tissue mineralization patterns. Several advances in CT technology have led to a variety of acquisition techniques with distinct clinical applications. These include four-dimensional CT, which allows examination of joints during motion; cone-beam CT, which allows examination during physiological weight-bearing conditions; dual-energy CT, which allows material decomposition useful in musculoskeletal deposition disorders (e.g., gout) and bone marrow edema detection; and photon-counting CT, which provides increased spatial resolution, decreased radiation, and material decomposition compared to standard multi-detector CT systems due to its ability to directly translate X-ray photon energies into electrical signals. Advanced acquisition techniques provide higher spatial resolution scans capable of enhanced bony microarchitecture and bone mineral density assessment. Together, these CT acquisition techniques will continue to play a substantial role in the practices of orthopedics, rheumatology, metabolic bone, oncology, and interventional radiology.

Thigh muscle composition changes in knee osteoarthritis patients during weight loss: Sex-specific analysis using data from osteoarthritis initiative.

OBJECTIVES: Sex of patients with knee osteoarthritis (KOA) may impact changes in thigh muscle composition during weight loss, the most well-known disease-modifying intervention. We investigated longitudinal sex-based changes in thigh muscle quality during weight loss in participants with KOA. METHODS: Using Osteoarthritis Initiative (OAI) cohort data, we included females and males with baseline radiographic KOA who experienced > 5 % reduction in Body Mass Index (BMI) over four years. Using a previously validated deep-learning algorithm, we measured Magnetic Resonance Imaging (MRI)-derived biomarkers of thigh muscles at baseline and year-4. Outcomes were the intra- and inter-muscular adipose tissue (Intra-MAT and Inter-MAT) and contractile percentage of thigh muscles between females and males. The analysis adjusted for potential confounders, such as demographics, risk factors, BMI change, physical activity, diet, and KOA status. RESULTS: A retrospective selection of available thigh MRIs from KOA participants who also had a 4-year weight loss (>5 % of BMI) yielded a sample comprising 313 thighs (192 females and 121 males). Female and male participants exhibited a comparable degree of weight loss (females: -9.72 ±â€¯4.38, males: -8.83 ±â€¯3.64, P-value=0.060). However, the changes in thigh muscle quality were less beneficial for females compared to males, as shown by a less degree of longitudinal decrease in Intra-MAT (change difference,95 %CI: 783.44 mm2/4-year, 505.70 to 1061.19, P-value<0.001) and longitudinal increase in contractile percentage (change difference,95 %CI: -3.9 %/4-year, -6.5 to -1.4, P-value=0.019). CONCLUSIONS: In participants with KOA and 4-year weight loss, the longitudinal changes in thigh muscle quality were overall beneficial but to a less degree in females compared to males. Further research is warranted to investigate the underlying mechanisms and develop sex-specific interventions to optimize muscle quality during weight loss.

Screening for Asymptomatic Osteonecrosis of the Hip in Systemic Lupus Erythematous: A Systematic Review and Meta-Analysis of MRI-Based Prevalence.

Objective. This paper aims to estimate asymptomatic hip osteonecrosis prevalence in SLE patients using MRI examination and to determine the prevalence among higher risk subpopulations. Materials and Methods. PubMed, Embase, Cochrane, and SCOPUS were searched from inception to May 9th, 2023. Studies on patients who were clinically diagnosed with systemic lupus erythematosus without reported symptoms attributable to hip osteonecrosis were included. Two independent reviewers extracted data and assessed the risk of bias. Data collected from each study include the study year, the number of hips screened, the number of hips with osteonecrosis, demographics, laboratory data, medications, follow-up time, radiological protocols, and MRI-based osteonecrosis detection and grading criteria. Results. Eleven eligible studies including 503 participants (15-35 years old; 74-100% female) with SLE were identified. Significant risk of bias was determined in one study. The overall prevalence of osteonecrosis of the hip was found to be 14% (184/1006 hip joints, 95% confidence interval: 7-22%, number needed to scan: 7.1). SLE patients who received corticosteroid treatment had a higher prevalence of asymptomatic hip osteonecrosis (18%) compared to non-corticosteroid users (0%, p-value < 0.01). Additionally, meta-regression results revealed that daily corticosteroid dose was associated with increased prevalence of asymptomatic osteonecrosis (0.5%/milligram, p-value < 0.01). Conclusions. The high prevalence of asymptomatic hip osteonecrosis in SLE patients raises concerns about the timeliness of interventions. The limitations of this study include a relatively low number of identified studies; and one study lacked full-text availability.

Erosive hand osteoarthritis and sarcopenia: data from Osteoarthritis Initiative cohort.

OBJECTIVES: There is no evidence linking specific osteoarthritis (OA) types, such as erosive hand OA (EHOA), with distant generalised changes in muscle composition (sarcopenia), which can potentially be modified. This study pioneers the exploration of the association between EHOA and sarcopenia, both of which are predominantly observed in the older adults. METHODS: Using the Osteoarthritis Initiative cohort, we selected hand OA (modified Kellgren and Lawrence (grade ≥2 in ≥1 hand joint) participants with radiographic central erosions in ≥1 joints (EHOA group) and propensity score-matched hand OA participants with no erosion (non-EHOA group). MRI biomarkers of thigh muscles were measured at baseline, year 2 and year 4 using a validated deep-learning algorithm. To adjust for 'local' effects of coexisting knee OA (KOA), participants were further stratified according to presence of radiographic KOA. The outcomes were the differences between EHOA and non-EHOA groups in the 4-year rate of change for both intramuscular adipose tissue (intra-MAT) deposition and contractile (non-fat) area of thigh muscles. RESULTS: After adjusting for potential confounders, 844 thighs were included (211 EHOA:633 non-EHOA; 67.1±7.5 years, female/male:2.9). Multilevel mixed-effect regression models showed that EHOA is associated a different 4-year rate of change in intra-MAT deposition (estimate, 95% CI: 71.5 mm2/4 years, 27.9 to 115.1) and contractile area (estimate, 95% CI: -1.8%/4 years, -2.6 to -1.0) of the Quadriceps. Stratified analyses showed that EHOA presence is associated with adverse changes in thigh muscle quality only in participants without KOA. CONCLUSIONS: EHOA is associated with longitudinal worsening of thigh muscle composition only in participants without concomitant KOA. Further research is needed to understand the systemic factors linking EHOA and sarcopenia, which unlike EHOA is modifiable through specific interventions.

Statin use and longitudinal changes in quantitative MRI-based biomarkers of thigh muscle quality: data from Osteoarthritis Initiative.

OBJECTIVE: To assess whether changes in MRI-based measures of thigh muscle quality associated with statin use in participants with and without/at-risk of knee osteoarthritis. METHODS: This retrospective cohort study used data from the Osteoarthritis Initiative study. Statin users and non-users were matched for relevant covariates using 1:1 propensity-score matching. Participants were further stratified according to baseline radiographic knee osteoarthritis status. We used a validated deep-learning method for thigh muscle MRI segmentation and calculation of muscle quality biomarkers at baseline, 2nd, and 4th visits. Mean difference and 95% confidence intervals (CI) in longitudinal 4-year measurements of muscle quality biomarkers, including cross-sectional area, intramuscular adipose tissue, contractile percent, and knee extensors and flexors maximum and specific contractile force (force/muscle area) were the outcomes of interest. RESULTS: After matching, 3772 thighs of 1910 participants were included (1886 thighs of statin-users: 1886 of non-users; age: 62 ± 9 years (average ± standard deviation), range: 45-79; female/male: 1). During 4 years, statin use was associated with a slight decrease in muscle quality, indicated by decreased knee extension maximum (mean-difference, 95% CI: - 1.85 N/year, - 3.23 to - 0.47) and specific contractile force (- 0.04 N/cm2/year, - 0.07 to - 0.01), decreased thigh muscle contractile percent (- 0.03%/year, - 0.06 to - 0.01), and increased thigh intramuscular adipose tissue (3.06 mm2/year, 0.53 to 5.59). Stratified analyses showed decreased muscle quality only in participants without/at-risk of knee osteoarthritis but not those with established knee osteoarthritis. CONCLUSIONS: Statin use is associated with a slight decrease in MRI-based measures of thigh muscle quality over 4 years. However, considering statins' substantial cardiovascular benefits, these slight muscle changes may be relatively less important in overall patient care.

CT-derived pectoralis composition and incident pneumonia hospitalization using fully automated deep-learning algorithm: multi-ethnic study of atherosclerosis.

BACKGROUND: Pneumonia-related hospitalization may be associated with advanced skeletal muscle loss due to aging (i.e., sarcopenia) or chronic illnesses (i.e., cachexia). Early detection of muscle loss may now be feasible using deep-learning algorithms applied on conventional chest CT. OBJECTIVES: To implement a fully automated deep-learning algorithm for pectoralis muscle measures from conventional chest CT and investigate longitudinal associations between these measures and incident pneumonia hospitalization according to Chronic Obstructive Pulmonary Disease (COPD) status. MATERIALS AND METHODS: This analysis from the Multi-Ethnic Study of Atherosclerosis included participants with available chest CT examinations between 2010 and 2012. We implemented pectoralis muscle composition measures from a fully automated deep-learning algorithm (Mask R-CNN, built on the Faster Region Proposal Network (R-) Convolutional Neural Network (CNN) with an extension for mask identification) for two-dimensional segmentation. Associations between CT-derived measures and incident pneumonia hospitalizations were evaluated using Cox proportional hazards models adjusted for multiple confounders which include but are not limited to age, sex, race, smoking, BMI, physical activity, and forced-expiratory-volume-at-1 s-to-functional-vital-capacity ratio. Stratification analyses were conducted based on baseline COPD status. RESULTS: This study included 2595 participants (51% female; median age: 68 (IQR: 61, 76)) CT examinations for whom we implemented deep learning-derived measures for longitudinal analyses. Eighty-six incident pneumonia hospitalizations occurred during a median 6.67-year follow-up. Overall, pectoralis muscle composition measures did not predict incident pneumonia. However, in fully-adjusted models, only among participants with COPD (N = 507), CT measures like extramyocellular fat index (hazard ratio: 1.98, 95% CI: 1.22, 3.21, p value: 0.02), were independently associated with incident pneumonia. CONCLUSION: Reliable deep learning-derived pectoralis muscle measures could predict incident pneumonia hospitalization only among participants with known COPD. CLINICAL RELEVANCE STATEMENT: Pectoralis muscle measures obtainable at zero additional cost or radiation exposure from any chest CT may have independent predictive value for clinical outcomes in chronic obstructive pulmonary disease patients. KEY POINTS: •Identification of independent and modifiable risk factors of pneumonia can have important clinical impact on patients with chronic obstructive pulmonary disease. •Opportunistic CT measures of adipose tissue within pectoralis muscles using deep-learning algorithms can be quickly obtainable at zero additional cost or radiation exposure. •Deep learning-derived pectoralis muscle measurements of intermuscular fat and its subcomponents are independently associated with subsequent incident pneumonia hospitalization.

Predictive Value of Deep Learning-derived CT Pectoralis Muscle and Adipose Measurements for Incident Heart Failure: Multi-Ethnic Study of Atherosclerosis.

Purpose: To develop a deep learning algorithm capable of extracting pectoralis muscle and adipose measurements and to longitudinally investigate associations between these measurements and incident heart failure (HF) in participants from the Multi-Ethnic Study of Atherosclerosis (MESA). Materials and Methods: MESA is a prospective study of subclinical cardiovascular disease characteristics and risk factors for progression to clinically overt disease approved by institutional review boards of six participating centers (ClinicalTrials.gov identifier: NCT00005487). All participants with adequate imaging and clinical data from the fifth examination of MESA were included in this study. Hence, in this secondary analysis, manual segmentations of 600 chest CT examinations (between the years 2010 and 2012) were used to train and validate a convolutional neural network, which subsequently extracted pectoralis muscle and adipose (intermuscular adipose tissue (IMAT), perimuscular adipose tissue (PAT), extramyocellular lipids and subcutaneous adipose tissue) area measurements from 3031 CT examinations using individualized thresholds for adipose segmentation. Next, 1781 participants without baseline HF were longitudinally investigated for associations between baseline pectoralis muscle and adipose measurements and incident HF using crude and adjusted Cox proportional hazards models. The full models were adjusted for variables in categories of demographic (age, race, sex, income), clinical/laboratory (including physical activity, BMI, and smoking), CT (coronary artery calcium score), and cardiac MRI (left ventricular ejection fraction and mass (% of predicted)) data. Results: In 1781 participants (median age, 68 (IQR,61, 75) years; 907 [51%] females), 41 incident HF events occurred over a median 6.5-year follow-up. IMAT predicted incident HF in unadjusted (hazard ratio [HR]:1.14; 95% CI: 1.03-1.26) and fully adjusted (HR:1.16, 95% CI: 1.03-1.31) models. PAT also predicted incident HF in crude (HR:1.19; 95% CI: 1.06-1.35) and fully adjusted (HR:1.25; 95% CI: 1.07-1.46) models. Conclusion: The study demonstrates that fast and reliable deep learning-derived pectoralis muscle and adipose measurements are obtainable from conventional chest CT, which may be predictive of incident HF.©RSNA, 2023.

Subchondral bone in knee osteoarthritis: bystander or treatment target?

The subchondral bone is an important structural component of the knee joint relevant for osteoarthritis (OA) incidence and progression once disease is established. Experimental studies have demonstrated that subchondral bone changes are not simply the result of altered biomechanics, i.e., pathologic loading. In fact, subchondral bone alterations have an impact on joint homeostasis leading to articular cartilage loss already early in the disease process. This narrative review aims to summarize the available and emerging imaging techniques used to evaluate knee OA-related subchondral bone changes and their potential role in clinical trials of disease-modifying OA drugs (DMOADs). Radiographic fractal signature analysis has been used to quantify OA-associated changes in subchondral texture and integrity. Cross-sectional modalities such as cone-beam computed tomography (CT), contrast-enhanced cone beam CT, and micro-CT can also provide high-resolution imaging of the subchondral trabecular morphometry. Magnetic resonance imaging (MRI) has been the most commonly used advanced imaging modality to evaluate OA-related subchondral bone changes such as bone marrow lesions and altered trabecular bone texture. Dual-energy X-ray absorptiometry can provide insight into OA-related changes in periarticular subchondral bone mineral density. Positron emission tomography, using physiological biomarkers of subchondral bone regeneration, has provided additional insight into OA pathogenesis. Finally, artificial intelligence algorithms have been developed to automate some of the above subchondral bone measurements. This paper will particularly focus on semiquantitative methods for assessing bone marrow lesions and their utility in identifying subjects at risk of symptomatic and structural OA progression, and evaluating treatment responses in DMOAD clinical trials.

Musculoskeletal CT Imaging: State-of-the-Art Advancements and Future Directions.

CT is one of the most widely used modalities for musculoskeletal imaging. Recent advancements in the field include the introduction of four-dimensional CT, which captures a CT image during motion; cone-beam CT, which uses flat-panel detectors to capture the lower extremities in weight-bearing mode; and dual-energy CT, which operates at two different x-ray potentials to improve the contrast resolution to facilitate the assessment of tissue material compositions such as tophaceous gout deposits and bone marrow edema. Most recently, photon-counting CT (PCCT) has been introduced. PCCT is a technique that uses photon-counting detectors to produce an image with higher spatial and contrast resolution than conventional multidetector CT systems. In addition, postprocessing techniques such as three-dimensional printing and cinematic rendering have used CT data to improve the generation of both physical and digital anatomic models. Last, advancements in the application of artificial intelligence to CT imaging have enabled the automatic evaluation of musculoskeletal pathologies. In this review, the authors discuss the current state of the above CT technologies, their respective advantages and disadvantages, and their projected future directions for various musculoskeletal applications.

Impact of immune status on the clinical characteristics, treatment outcomes and mortality of pulmonary nocardiosis: a retrospective analysis in a tertiary care hospital from a low to middle-income country.

Nocardiosis is an opportunistic infection that primarily targets the immunosuppressed. We investigate the differences in demographics and characteristics between immunosuppressed and immunocompetent patients with nocardiosis in a tertiary care hospital in Pakistan. Retrospective records were reviewed for patients diagnosed with pulmonary nocardiosis between 2010 and 2020. Immunosuppressed individuals were identified as those with autoimmune diseases, hematologic diseases and malignancies, HIV, immunosuppressant therapy, etc. Data collected included basic demographics, comorbid conditions, medication history, clinical presentation, radiological and microbiological data, and nocardiosis outcomes and complications. A total of 66 patients with nocardiosis were included in this study out of which 48 were immunosuppressed while 18 were immunocompetent. Both groups were compared for a number of variables including patient characteristics, underlying conditions, radiological findings, treatment regimen and outcomes. Immunosuppressed individuals were younger, and had higher rates of diabetes, chronic renal disease, chronic liver disease, higher platelet counts, surgical intervention, and longer hospital stays. Fever, dyspnea, and sputum production were the most common presentations. Nocardia asteroides was found to be the most common species of Nocardia overall. Nocardiosis presents differently in patients with immunosuppressed and immunocompetent patients consistent with previous studies. Nocardiosis should be considered in any patient presenting with treatment-resistant pulmonary or neurological symptoms.

Higher thyroid hormone has a negative association with lower limb lean body mass in euthyroid older adults: Analysis from the Baltimore Longitudinal study of aging.

Background: Hyperthyroidism is associated with lower lean body mass, as a result of catabolic actions of thyroid hormone. Therefore, higher thyroid hormone levels could be a factor in the development of sarcopenia and age associated functional decline. The relationship between thyroid hormone and muscle mass in ambulatory, euthyroid older adults is not known. Method: We used mixed-effects models to estimate the cross-sectional relationships (accounting for inter-person variability) between thyroid axis hormone measures and lower limb composition or sarcopenia at visits in the Baltimore Longitudinal Study of Aging (BLSA) at which DEXA scans were available and both thyrotropin (TSH) and free thyroxine (FT4) were in the reference range. Analyses were adjusted for levothyroxine use, age, race, sex, BMI, smoking, alcohol intake, cholesterol, and systolic blood pressure. Results: 1442 euthyroid participants (median age 68, 50% female, and 69% white) contributed to 5306 visits from 2003 to 2019. FT4 was negatively associated with lower limb lean mass (beta: 88.49; 95% Confidence Interval (CI): 122.78, -54.20; p < 0.001) and positively associated with sarcopenia (OR: 1.11%, 95% CI: 1.01, 1.22) in the whole cohort. Additionally, higher FT4 was associated with lower leg lean mass (beta: 66.79; 95% CI: 102.24, -31.33; p < 0.001) and sarcopenia (OR:1.09%, 95% CI:1.01, 1.18) in older adults, but not in younger adults alone. Conclusion: In euthyroid older adults, higher FT4 is associated with lower leg lean mass and higher odds of sarcopenia. Understanding the relationship between thyroid hormone and sarcopenia is needed to improve clinical decision-making and avoid functional decline from excess thyroid hormone use in older adults.

Radiographically detectable intra-articular mineralization: Predictor of knee osteoarthritis outcomes or only an indicator of aging? A brief report from the osteoarthritis initiative.

Objective: To determine the association between Intra-articular mineralization (IAM) and knee osteoarthritis (OA) outcomes stratified according to participants' age. Methods: Participants from the Osteoarthritis Initiative (OAI) with baseline radiographic OA (i.e., Kellgren-Lawrence grade ≥2 with Osteoarthritis Research Society International (OARSI) atlas joint space narrowing (JSN)) in either knee were identified. Both knees and dominant hand baseline radiographs were evaluated for the presence of IAM. Whole-grade OARSI-JSN radiographic progression and increased Western Ontario and McMaster universities osteoarthritis index scores of the knees with baseline radiographic OA (assessed annually) were defined as radiographic and symptomatic progression, respectively. Cox proportional-hazards and longitudinal multilevel regression models investigated radiographic and symptomatic progression, respectively. Results: 2010 participants with baseline radiographic OA in either one or both knees (N â€‹= â€‹2976) were identified. 178 participants had baseline IAM (hand radiographs â€‹= â€‹46, knee radiographs â€‹= â€‹166, both â€‹= â€‹34). An adjusted logistic regression model suggests an association between age and IAM (Odds Ratio: 1.06, 95% Confidence Interval (CI): 1.04-1.08). Presence of any IAM was not associated with whole-grade OARSI-JSN (Hazard Ratio (HR): 1.00, 95% CI: 0.73-1.37) or symptomatic progression (Estimated difference: 1.24, p-value: 0.13) in all participants. Using stratification analysis, in younger participants <60 years old, presence of any IAM was associated with radiographic progression (HR: 1.90, 95% CI: 1.01-3.60). Conclusion: Although the presence of any radiographic IAM increases with higher age and does not predict knee OA outcomes across the entire sample of OAI participants, it is associated with knee OA radiographic progression in participants aged <60.

Computed Tomography: State-of-the-Art Advancements in Musculoskeletal Imaging.

ABSTRACT: Although musculoskeletal magnetic resonance imaging (MRI) plays a dominant role in characterizing abnormalities, novel computed tomography (CT) techniques have found an emerging niche in several scenarios such as trauma, gout, and the characterization of pathologic biomechanical states during motion and weight-bearing. Recent developments and advancements in the field of musculoskeletal CT include 4-dimensional, cone-beam (CB), and dual-energy (DE) CT. Four-dimensional CT has the potential to quantify biomechanical derangements of peripheral joints in different joint positions to diagnose and characterize patellofemoral instability, scapholunate ligamentous injuries, and syndesmotic injuries. Cone-beam CT provides an opportunity to image peripheral joints during weight-bearing, augmenting the diagnosis and characterization of disease processes. Emerging CBCT technologies improved spatial resolution for osseous microstructures in the quantitative analysis of osteoarthritis-related subchondral bone changes, trauma, and fracture healing. Dual-energy CT-based material decomposition visualizes and quantifies monosodium urate crystals in gout, bone marrow edema in traumatic and nontraumatic fractures, and neoplastic disease. Recently, DE techniques have been applied to CBCT, contributing to increased image quality in contrast-enhanced arthrography, bone densitometry, and bone marrow imaging. This review describes 4-dimensional CT, CBCT, and DECT advances, current logistical limitations, and prospects for each technique.

Longitudinal MRI-defined Cartilage Loss and Radiographic Joint Space Narrowing Following Intra-Articular Corticosteroid Injection for Knee Osteoarthritis: A Systematic Review and Meta-analysis.

Background: Intra-articular corticosteroid injections (IACS) are interventions which provide pain relief in knee osteoarthritis (OA). It remains unclear whether IACS have a deleterious effect on knee cartilage structure. Purpose: To estimate the effect of IACS on cartilage structure in patients with knee OA, using joint space width (JSW) (in radiographic studies), and cartilage thickness (in magnetic resonance imaging). Materials and methods: A literature search was performed to identify randomized control trials and observational studies published from inception to June 15, 2022. Studies were included if patients received IACS for knee OA, with a control arm. Given the different metrics used in reporting continuous variable outcomes among studies, pooled estimates for cartilage thickness change were assessed using standardized mean differences (defined as the difference between the means of the groups divided by a within-group standard deviation) to odds ratio transformation. Sensitivity analyses were conducted based on outcome metric, imaging modality, and number of injections. Results: Six studies (1437 participants) were identified. The estimated effect of IACS on cartilage structure revealed greater odds of cartilage structure worsening (Odds Ratio (OR): 2.01, 95% Confidence Interval (CI): 1.18,3.44). Sensitivity analyses revealed similar trends, with significant results for singular injections with preference to JSW (OR: 2.44, 95%CI: 1.23,4.82), radiographic outcomes with preference to KL grade (OR: 2.03, 95%CI: 1.01,4.10), binary outcomes with preference to KL grade (OR: 2.93, 95%CI: 1.18,7.25) and quantitative measures (Standardized Mean Differences (SMD): -0.34, 95%CI: -0.66, -0.02). Conclusions: IACS use may contribute to imaging features of knee cartilage loss. Further studies are warranted to investigate the underlying pathogenesis.

Impact of Perfectionism and Resilience on Empathy in Medical Students: A Cross-Sectional Study.

Empathy is a cognitive attribute that forms the cornerstone for good doctor-patient encounters. The formative period for the development of empathy toward patients begins with clinical encounters within medical school. An individual medical student's empathy levels may in part be a product of their resilience and perfectionist attitudes. A cross-sectional study with 320 medical students across all years of study was conducted to determine the correlation of perfectionism and resilience with clinical empathy in medical students. The JSE-S, CD-RISC 10, and APS-R scales were used to assess levels of empathy, resilience, and perfectionism, respectively. The study found that a positive correlation exists between resilience (r = 0.174) and academic year with empathy, and a negative correlation exists between maladaptive perfectionism and empathy (r = -0.138). The resilience score declined progressively as the year of study progressed with a statistically significant. Mean empathy scores were lowest in fifth-year students (96.8 ± 12.5) and highest in third-year students (107.8 ± 13.2). Further longitudinal studies are necessary to better understand the impact of resilience and perfectionism on empathy.

Sarcoidosis: An experience from a tertiary care center in Karachi Pakistan.

OBJECTIVE: To assess the demographic and clinical characteristics and treatment of patients with sarcoidosis in tertiary care settings. METHODS: The descriptive retrospective study was conducted at the Aga Khan University Hospital, Karachi, and comprised data from 2017 to 2019 of patients with established diagnosis of sarcoidosis. Data was collected on a predesigned proforma and it was analysed using SPSS 23. RESULTS: Of the 974 patients evaluated, sarcoidosis was established in 108(11.1%); 58(53.7%) of them being females. The overall mean age was 50.9±12.9 years. Hypertension 49(45.4%) and diabetes mellitus 37(34.3%) were the most frequent co-morbidities. Extra-pulmonary manifestations were found in 27(25%) patients; ophthalmic 9(33.3%), musculoskeletal 8(29.6%) and skin 7(25.9%). Prednisolone was the mainstay of treatment in 93(86.1%) patients. CONCLUSIONS: Sarcoidosis was not found to be rare in Pakistan.

Implementation of 3D Printing and Computer-Aided Design and Manufacturing (CAD/CAM) in Craniofacial Reconstruction.

INTRODUCTION: The need for precision in craniomaxillofacial surgery has necessitated the evolution of new technology to improve patient outcomes and subsequently augment the road to recovery. Surgical planning has variables that may influence outcomes, including the image quality, image acquisition and image processing. Our review focuses on the advancement of three dimensional (3D) printing to create patient-specific constructs and therefore aims to study the current trends in the implementation of 3-D printing in craniofacial surgeries, including preferred 3-D printing techniques and materials, computer-aided design and manufacturing techniques, and outcomes as measured by recent studies. METHODS: The authors conducted a systematic review following PRISMA guidelines to query PubMed, Embase, Cochrane library and ProQuest electronic databases. Mesh combinations and synonyms of "3Dprinting", "3Dprinted", "Craniofacial" were used. The authors included all original human studies that focused on the surgical implementation of 3D-printed implants for craniofacial defects. RESULTS: After screening 1253 studies, the authors included 49 articles consisting of a total of 745 subjects for qualitative analysis. Titanium (n = 13) and polycaprolactone (n = 6) were the most common 3D printed materials studied while Color Jet Printing (n = 12) and Stereolithography (n = 11) were the most common techniques. All studies that compared implants acquired by 3D printing with those acquired by conventional approaches showed a significantly better prognosis, and reductions in operative time, length of stay, and immediate complications. CONCLUSIONS: The use of patient-specific alternative materials, planning software and 3-D printing techniques shows satisfactory results in craniofacial reconstruction. Future studies should include standard levels of objective measurements to make better comparisons.

Deep learning applications in neuro-oncology.

Deep learning (DL) is a relatively newer subdomain of machine learning (ML) with incredible potential for certain applications in the medical field. Given recent advances in its use in neuro-oncology, its role in diagnosing, prognosticating, and managing the care of cancer patients has been the subject of many research studies. The gamut of studies has shown that the landscape of algorithmic methods is constantly improving with each iteration from its inception. With the increase in the availability of high-quality data, more training sets will allow for higher fidelity models. However, logistical and ethical concerns over a prospective trial comparing prognostic abilities of DL and physicians severely limit the ability of this technology to be widely adopted. One of the medical tenets is judgment, a facet of medical decision making in DL that is often missing because of its inherent nature as a "black box." A natural distrust for newer technology, combined with a lack of autonomy that is normally expected in our current medical practices, is just one of several important limitations in implementation. In our review, we will first define and outline the different types of artificial intelligence (AI) as well as the role of AI in the current advances of clinical medicine. We briefly highlight several of the salient studies using different methods of DL in the realm of neuroradiology and summarize the key findings and challenges faced when using this nascent technology, particularly ethical challenges that could be faced by users of DL.