No stone left unturned and nothing left behind - A pictorial guide for retained surgical items.

Retained surgical instruments (RSI) remain an unsolved problem with serious implications for patients and healthcare providers. Although radiographs are commonly obtained whenever a surgical count is incorrect or incomplete, they have a very low prevalence of positive findings. With the majority of these studies being negative, it is difficult for radiologists and trainees to develop expertise in the detection of RSI, and comfort with reporting and documenting their findings. It is also important for the radiologist to be familiar with the documentation and communication requirements of their own institution in regards to intraoperative radiographs and their interpretation. This pictorial essay is intended to provide guidance to these "best practices" for the management of these cases. A series of case examples is also provided. In this manuscript we illustrate potential pitfalls and avoidable sources of error in the interpretation of these challenging cases.

Collaborative Learning in Radiology: From Peer Review to Peer Learning and Peer Coaching.

BACKGROUND: A Radiology Research Alliance Task Force was assembled in 2018 to review the literature on peer review and report on best practices for peer learning and peer coaching. FINDINGS: This report provides a historical perspective on peer review and the transition to peer collaborative learning and peer coaching. Most forms of current peer review have fulfilled regulatory requirements but have failed to significantly impact quality improvement or learning opportunities. Peer learning involves joint intellectual efforts by two or more individuals to study best practices and review error collaboratively. Peer coaching is a process in which individuals in a trusted environment work to expand, refine, and build new skills in order to facilitate self-directed learning and professional growth. We discuss the value in creating opportunities for peer learning and peer coaching. CONCLUSION: Peer collaborative learning combined with peer coaching provides opportunities for teams to learn and grow together, benefit from each other's expertise and experience, improve faculty morale, and provide more opportunities for collaborations between faculty.

The correlation of symptoms, pulmonary function tests and exercise testing with high-resolution computed tomography in patients with idiopathic interstitial pneumonia in a tertiary care hospital in South India.

CONTEXT: For the follow-up of patients with idiopathic interstitial pneumonias (IIP), it is unclear which parameters of pulmonary function tests (PFT) and exercise testing would correlate best with high-resolution computed tomography (HRCT).. AIM: To find out the correlation of symptom scores, PFTs and exercise testing with HRCT scoring in patients diagnosed as idiopathic interstitial pneumonia. SETTINGS AND DESIGN: Cross-sectional study done in pulmonary medicine outpatients department of a tertiary care hospital in South India. MATERIALS AND METHODS: Consecutive patients who were diagnosed as IIP by a standard algorithm were included into the study. Cough and dyspnea were graded for severity and duration. Pulmonary function tests and exercise testing parameters were noted. HRCT was scored based on an alveolar score, an interstitial score and a total score. The HRCT was correlated with each of the clinical and physiologic parameters. Pearson's/Spearman's correlation coefficient was used for the correlation of symptoms and parameters of ABG, PFT and 6MWT with the HRCT scores. RESULTS: A total of 94 patients were included in the study. Cough and dyspnea severity (r = 0.336 and 0.299), FVC (r = -0.48), TLC (r = -0.439) and DLCO and distance saturation product (DSP) (r = -0.368) and lowest saturation (r = -0.324) had significant correlation with total HRCT score. Among these, DLCO, particularly DLCO corrected % of predicted, correlated best with HRCT score (r = -0.721).. CONCLUSION: Symptoms, PFT and exercise testing had good correlation with HRCT. DLCO corrected % of predicted correlated best with HRCT.

Review of the dimensions of the median nerve and carpal tunnel using sonography in asymptomatic adults.

OBJECTIVE: The study aims to establish the normal range of all sonologic measurements of carpal tunnel (CT) structures in an asymptomatic population. METHODS: Sonological evaluation of 150 wrists in 75 asymptomatic adults was performed. The cross-sectional area (CSA) of the median nerve at four levels, the flattening ratio (FR) at three levels, the antero-posterior (AP) diameter of the CT and the distance of the transverse carpal ligament (TCL) from the trapezium-hamate (TmH) line were measured. RESULTS: The mean (standard deviation (SD)) CSA of the median nerve at the distal forearm, CT inlet, mid and outlet were 6.8 (1.3), 7.4 (1.1), 7.5 (1.0), 7.1 (1.0) mm(2) , respectively. The mean (SD) FR at the CT inlet, mid and outlet were 2.66 (0.54), 2.55 (0.54), 3.69 (0.82), respectively. The mean (SD) AP diameter of the CT was 10.4 mm (1.1). Volar bowing of the retinaculum was seen in 7.3% of normal wrists. CONCLUSIONS: The normal range at two SDs of the CSA of the median nerve at the inlet was 5.2-9.6 mm(2) . The upper limit of volar bowing of the flexor retinaculum was 0.8 mm. The FR overlaps with values obtained in other studies of patients with carpal tunnel syndrome. The mean AP diameter of the CT was 10.4 mm (SD 1.1). To the best of our knowledge, this is the largest study performed in an asymptomatic population assessing the different sonological parameters related to the CT.

Parameter estimation in stochastic mammogram model by heuristic optimization techniques.

The appearance of disproportionately large amounts of high-density breast parenchyma in mammograms has been found to be a strong indicator of the risk of developing breast cancer. Hence, the breast density model is popular for risk estimation or for monitoring breast density change in prevention or intervention programs. However, the efficiency of such a stochastic model depends on the accuracy of estimation of the model's parameter set. We propose a new approach-heuristic optimization-to estimate more accurately the model parameter set as compared to the conventional and popular expectation-maximization (EM) algorithm. After initial segmentation of a given mammogram, the finite generalized Gaussian mixture (FGGM) model is constructed by computing the statistics associated with different image regions. The model parameter set thus obtained is estimated by particle swarm optimization (PSO) and evolutionary programming (EP) techniques, where the objective function to be minimized is the relative entropy between the image histogram and the estimated density distributions. When our heuristic approach was applied to different categories of mammograms from the Mini-MIAS database, it yielded lower floor of estimation error in 109 out of 112 cases (97.3 %), and 101 out of 102 cases (99.0%), for the number of image regions being five and eight, respectively, with the added advantage of faster convergence rate, when compared to the EM approach. Besides, the estimated density model preserves the number of regions specified by the information-theoretic criteria in all the test cases, and the assessment of the segmentation results by radiologists is promising.