Morphological changes after open lumbar microdiscectomy at 2-year follow-up.

BACKGROUND: It is known that a possible decrease in disc height (DH) and foraminal size after open lumbar microdiscectomy (OLM) may cause pain in the long term. However, there is still insufficient information about the short- or long-term pathoanatomical and morphological effects of microdiscectomy. For example, the exact temporal course of the change in DH is not well known. OBJECTIVE: The purpose of this study was to examine morphological changes in DH and foramen dimensions after OLM. METHODS: In patients who underwent OLM for single-level lumbar disc herniation, MRI scans were obtained before surgery, and at an average of two years after surgery. In addition to DH measurements, foraminal area (FA), foraminal height (FH), superior foraminal width (SFW), and inferior foraminal width (IFW), were measured bilaterally. RESULTS: A postoperative increase in DH was observed at all vertebral levels, with an average of 5.5%. The mean right FHs were 15.3 mm and 15.7 mm before and after surgery, respectively (p= 0.062), while the left FHs were 14.8 mm and 15.8 mm before and after surgery (p= 0.271). The mean right SFW was 5.4 mm before surgery and 5.7 mm after surgery, while the mean right IFW ranged from 3.6 mm to 3.9 mm. The mean left SFW was 4.8 mm before surgery and 5.2 mm after surgery, while the mean left IFW ranged from 3.5 mm to 3.9 mm. Before surgery, the FAs were, on average, 77.1 mm2 and 75.6 mm2 on the right and left sides, respectively. At the 2-year follow-up, the mean FAs were 84.0 mm2 and 80.2 mm2 on the right and left sides, respectively. CONCLUSIONS: Contrary to prevalent belief, in patients who underwent single-level unilateral OLM, we observed that there may be an increase rather than a decrease in DH or foramen size at the 2-year follow-up. Our findings need to be confirmed by studies with larger sample sizes and longer follow-ups.

The effects of clinicopathological and imaging findings on recurrence and survival in mammary Paget's disease.

OBJECTIVE: Mammary Paget's disease (MPD) is a rare presentation type of breast cancer. The aim of this study was to evaluate the clinicopathological and imaging features affecting the invasive component, loco-regional recurrence, prognosis, and survival of MPD. METHODS: Patients who had undergone surgery due to MPD in a 10-year period were included. Parameters including mammography and magnetic resonance imaging (MRI) findings, tumor stage, molecular subtype, axillary involvement, presence of invasive carcinoma, loco-regional recurrence, overall survival (OS), and disease-free survival (DFS) were recorded and statistically analyzed. P<0.05 was determined as statistically significant. RESULTS: The study group consisted of 49 women with a mean age of 67.05±14.43 (range: 23-90) years. There was a significant association between the presence of invasive carcinoma and a mass lesion in the MRI (p=0.002). The frequency of sentinel lymph node (SLN) metastasis was significantly higher in patients with multicentric tumors (p=0.029; p<0.05). Locoregional recurrence and distant metastasis were significantly more frequent in patients with axillary involvement (p=0.0336; p<0.05). The mean DFS was 115.02±7.28 months, while the mean OS was 119.29±6.57 months. CONCLUSION: The presence of a mass lesion on MRI was determined to be significant in recognizing invasive carcinoma in MPD. The rate of SLN metastasis was higher in patients with multicentric tumors than in patients with unifocal tumors. Axillary involvement was associated with impaired DFS.

Chronic recurrent multifocal osteomyelitis: A multidisciplinary experience of 22 pediatric cases with a mean follow-up of 27 months.

BACKGROUND: Chronic recurrent multifocal osteomyelitis (CRMO) is not a well known disorder among nonpediatricians. The aim of this study is to retrospectively evaluate the clinical outcomes of twenty-two CRMO patients presenting to two referral centres. METHODS: This retrospective study included twenty-two children (12 males, 10 females; mean age 13 years; range 7-17 years). The diagnosis was based on clinical, radiological, and pathological findings. Data were retrieved from hospital charts. RESULTS: The mean delay in diagnosis was 26 months (range, 0-96 months). The mean follow-up after diagnosis was 27.4 months (range, 6-47 months). Symptoms included pain, limping, local swelling, morning stiffness, and fever. 18 patients had multifocal and 4 patients had unifocal disease. Bone lesions were detected with whole-body or local MRI (Magnetic Resonance Imaging). The mean number of bone lesions was 2.5 (range, 1-8). Ten cases underwent biopsy to exclude malignancy and infection. Prior to diagnosis, cast immobilization or curettage was erroneously performed in four patients. One patient suffered from vertebral compression fracture. There is no growth disturbance or deformity in any patient. CONCLUSION: This study demonstrated that early recognition of the disease can be improved by using Bristol criteria which should be evaluated by a multidisciplinary team rather than one single specialist. In this way, the reliability of these criteria is improved and the treatment could be given earlier with decreased delay in diagnosis. This multidisciplinary approach is also important for decision for biopsy, timely aggressive medical treatment, and follow-up of the disease to minimise possible complications.

Radiomics Features Based on MRI-ADC Maps of Patients with Breast Cancer: Relationship with Lesion Size, Features Stability, and Model Accuracy.

Objective: To predict breast cancer molecular subtypes with neural networks based on magnetic resonance imaging apparent diffusion coefficient (ADC) radiomics and to detect the relation of lesion size with the stability of radiomics features. Methods: This retrospective study included 221 consecutive patients (224 lesions) with breast cancer imaged between January 2015 and January 2020. Three sample size configurations were identified based on tumor size (experiment 1: all cases, experiment 2: >1 cm3, and experiment 3: >2 cm3). The tumors were segmented by three observers based on diffusion-weighted imaging-registered ADC maps, and the volumetric agreement of these segmentations was evaluated using the Dice coefficient. Stability of radiomics features (n=851) was evaluated with intraclass correlation coefficient (ICC, >0.75) and coefficient of variation (CoV, <0.15). Feature selection was made with variance inflation factor (VIF, <10) and least absolute shrinkage and selection operator regression. Outcomes were identified as molecular subtypes (Luminal A, Luminal B, HER2-enriched, triple-negative). Neural network performance was presented as an area under the curve and accuracies. Results: Of the 851 radiomics features, 611 had ICC >0.75, and 37 remained stable in the first experiment, 49 in the second, and 59 in the third based on CoV and VIF analysis. High accuracy was demonstrated by the Luminal B, HER2-enriched, and triple-negative models in the first experiment (>80%), all models in the second experiment, and HER2-enriched and triple-negative models in the third experiment. Conclusions: A positive stability is indicated by an increased lesion size related to radiomics features. Neural networks may predict moleculer subtypes of breast cancers over 1 cm3 with high accuracy.

Comparison of Magnetic Resonance Imaging With Positron Emission Tomography/Computed Tomography in the Evaluation of Response to Neoadjuvant Therapy of Breast Cancer.

INTRODUCTION: The present study aims to determine the diagnostic accuracy of magnetic resonance imaging (MRI) and positron emission tomography-computed tomography (PET-CT) in predicting a pathological response of molecular subtypes of breast cancer to neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS: We retrospectively analyzed patients with breast cancer who were operated after NAC between January 2018 and May 2020. Radiological responses were evaluated as per the Response Evaluation Criteria in Solid Tumors (RECIST) and changes in contrast enhancement patterns on MRI and the classification of PET Response Criteria in Solid Tumors (PERCIST) on PET-CT. The presence of a pathological response was evaluated based on the Sataloff classification. The agreement between the radiological response determined through imaging modalities before and after the NAC and the postoperative pathological complete response (pCR) was evaluated and compared statistically. Among the patients diagnosed with breast cancer between the ages of 18 and 80 y, those with N (+) at the time of diagnosis, those with T2 and advanced tumors, and those who were planned for breast conserving surgery were included in our study. Male patients, patients with distant metastases at the time of diagnosis, and patients with other system malignancies were excluded. RESULTS: The study included 88 patients who had undergone surgery for breast cancer after NAC between January 2018 and May 2020. The study was conducted retrospectively in a single center. The tumor diameters and standard uptake values significantly decreased after NAC (P < 0.001). Estrogen receptor (ER) and progesterone receptor (PR) positivity were negatively associated with pCR (P = 0.03 and P = 0.03, respectively), whereas there was a significant positive association between HER-2 positivity and pCR (P = 0.004). There was a moderate agreement between the RECIST criteria used with MRI and pCR (k: 0.46). Moreover, a good agreement between PET-CT-PERCIST and pCR was detected (k: 0.61). In predicting pCR after NAC, MRI showed a selectivity of 80.7%, a sensitivity of 65.2%, a positive predictive value (PPV) of 75%, and a negative predictive value (NPV) of 72.4%. The corresponding rates for PET-CT were 75.7%, 100%, 57.9%, and 100%. CONCLUSIONS: When evaluating pCR after NAC, MRI was found to be more sensitive in patients with ER-positive cancer cell nuclei with weak to medium staining intensity and a loss of E-cadherin expression, whereas PET-CT was found to be more sensitive in patients with HER-2 overexpression, Luminal B, or Ki-67 proliferation >14% (P = 0.01).

Multivariable Diagnostic Prediction Model to Detect Hormone Secretion Profile From T2W MRI Radiomics with Artificial Neural Networks in Pituitary Adenomas.

Objective: This study aims to develop neural networks to detect hormone secretion profiles in the pituitary adenomas based on T2 weighted magnetic resonance imaging (MRI) radiomics. Methods: This retrospective model-development study included a cohort of patients with pituitary adenomas (n=130) from January 2015 to January 2020 in one tertiary center. The mean age was 46.49±13.69 years, and 76/130 (58.46%) were women. Three observers segmented lesions on coronal T2 weighted MRI, and an interrater agreement was evaluated using the Dice coefficient. Predictors were determined as radiomics features (n=851). Feature selection was based on intraclass correlation coefficient, coefficient variance, variance inflation factor, and LASSO regression analysis. Outcomes were identified as 7 hormone secretion profiles [non-functioning pituitary adenoma, growth hormone-secreting adenomas, prolactinomas, adrenocorticotropic hormone-secreting adenomas, pluri-hormonal secreting adenomas (PHA), follicle-stimulating hormone and luteinizing hormone-secreting adenomas, and thyroid-stimulating hormone adenomas]. A multivariable diagnostic prediction model was developed with artificial neural networks (ANN) for 7 outcomes. ANN performance was presented as an area under the receiver operating characteristic curve (AUC) and accepted as successful if the AUC was >0.85 and p-value was <0.01. Results: The performance of the ANN distinguishing prolactinomas from other adenomas was validated (AUC=0.95, p<0.001, sensitivity: 91%, and specificity: 98%). The model distinguishing PHA had the lowest AUC (AUC=0.74 and p<0.001). The AUC values for the other five ANN were >0.85 and p values were <0.001. Conclusions: This study was successful in training neural networks that could differentiate the hormone secretion profile of pituitary adenomas.

Radiological approach to basilar invagination type B: Reliability and accuracy.

OBJECTIVES: This study aims to determine the reliability of the radiological tests used in the diagnosis of basilar invagination (BI). METHODS: Patients diagnosed with type B basilar invagination, who had both magnetic resonance (MR) and computed tomography (CT) imaging between January 2014 and November 2019 were included in this retrospective reliability study. In this study, distance from odontoid apex to Chamberlain's line (OA-CL) was accepted as a reference method for the diagnosis. Forty-two BI cases and 79 controls were included. Three radiologists with different levels of experience individually evaluated OA-CL, Boogard's angle (BoA), clivo-axial angle (CXA), clivo-dens angle (CDA), and clivo-palate angle (CPA) on midsagittal CT and MR images. Statistical analysis was made with the intraclass correlation coefficient (ICC), t-test, and receiver operating characteristic (ROC) curve. RESULTS: The ICC for CT and MR were; 0.977-0.973 (OA-CL), 0.912-0.882 (BoA), 0.845-0.846 (CXA), 0.862-0.864 (CDA), and 0.762-0.747 (CPA) respectively (P < 0.001). The areas under the ROC curve were 0.977 (BoA), 0.832 (CXA), 0.852 (CDA), and 0.719 (CPA) (P < 0.001). The cut-off measures were ≥137.84° (BoA), ≤149.25° (CXA), ≤129.58° (CDA), and ≤61.83° (CPA). The diagnostic accuracies were 0.954 (BoA), 0.664 (CXA), 0.704 (CDA), 0.438 (CPA) (P < 0.001). CONCLUSIONS: OA-CL and BoA express excellent inter-rater agreement than CXA, CDA, and CPA, which are limited due to morphological variations and head spatial position. BoA is the second most reliable diagnostic test. CXA, CDA, should only be used for complementary information. CPA was found inadequate for the diagnosis of BI..

Is vaccination necessary for COVID-19 patients? A retrospective cohort study investigating reinfection rates and symptomatology in a tertiary hospital.

BACKGROUND: Durability of immune response by the COVID-19 natural infection and the necessity of vaccines in recovered patients are important inquiries for the healthcare provider. RESEARCH DESIGN AND METHODS: Here, we investigated the characteristics and the rate of cases with reinfection that have been admitted to our tertiary hospital. RESULTS: A total of 119985 patients were applied between March 2020 and May 2021. Of these patients, 32607 (27%, 32,607/119985) tested positive. A total of 27 (0.08%, 27/32607) patients were found to be reinfected beyond 90 days. Only one of these reinfected patients (0.003, 1/32607) had novel COVID-19 pneumonia and was hospitalized for the second time. Other 26 reinfected patients were followed up as outpatients. CONCLUSIONS: COVID-19 reinfection is extremely rare. However, the reinfection may be severe in patients with immune deficiency. Healthcare providers may prioritize uninfected and immune-compromised patients for vaccination.

Successful Treatment of Acanthamoeba Meningoencephalitis in an Immunocompetent Child.

Acanthamoeba meningoencephalitis is a very rare entity with high mortality rate. Its diagnosis is usually delated, and the optimal approach for its treatment is uncertain. In presented case, early diagnosis was made with direct examination of cerebral spinal fluid, and immediate initiation of accurate treatment with amphotericin B and fluconazole survived patient.