Tag: statistics

J Cytol. 2023 Jan-Mar;40(1):1-4. doi: 10.4103/joc.joc_70_22. Epub 2023 Jan 17.

ABSTRACT

CONTEXT: Central nervous system lesions are diverse and remain one of the most challenging domains for neuropathologists. Intraoperative cytological diagnosis is now a universally accepted technique in diagnosis of central nervous system (CNS) lesions.

AIMS: 1) To analyze and compare cytomorphological features of CNS lesions in intraoperative squash smears with histopathology, immunohistochemistry, and preoperative radiological diagnosis and 2) to determine the diagnostic accuracy, sensitivity, and specificity of intraoperative squash cytology.

SETTINGS AND DESIGN: Prospective study conducted at a tertiary healthcare centre over a period of two years.

METHODS AND MATERIAL: All biopsy materials which underwent squash cytology and histopathological examination were collected, evaluated, classified, and graded according to WHO classification of CNS Tumors, 2016. The squash cytosmear diagnosis was compared with histopathological features and radiological diagnosis. Discordances were evaluated.

STATISTICAL ANALYSIS USED: The cases were categorized into true positives, false positives, true negatives, and false negatives. Diagnostic accuracy, sensitivity, and specificity were calculated from 2*2 table.

RESULTS: A total of 190 cases were included in the study. A total of 182 cases (95.70%) were neoplastic of which 87.36% were primary CNS neoplasms. Diagnostic accuracy in non-neoplastic lesions was 88.8%. Most common neoplastic lesions were glial tumors (35.7%), meningioma (17.3%), tumors of cranial and spinal nerves (12%), and metastatic lesions (12%). Diagnostic accuracy of squash cytology was higher in glial tumors (93.8%), meningioma (96.7%), and metastatic lesions (95.45%). Diagnostic accuracy of radiological modalities was 85.78%.

CONCLUSIONS: A good familiarity with cytomorphological features of CNS lesions, clinical details, radiological findings, and intraoperative impression of neurosurgeon enables the pathologist to improve diagnostic accuracy and reduce errors.

PMID:37179963 | PMC:PMC10167832 | DOI:10.4103/joc.joc_70_22

Quant Imaging Med Surg. 2023 May 1;13(5):3161-3173. doi: 10.21037/qims-22-1227. Epub 2023 Mar 28.

ABSTRACT

BACKGROUND: The image quality of computed tomography (CT) can be adversely affected by a low radiation dose, and reconstruction algorithms of an appropriate level may be useful in reducing this impact.

METHODS: Eight sets of CT images of a phantom were reconstructed with filtered back projection (FBP); adaptive statistical iterative reconstruction-Veo (ASiR-V) at 30% (AV-30), 50% (AV-50), 80% (AV-80), and 100% (AV-100); and deep learning image reconstruction (DLIR) at low (DL-L), medium (DL-M), and high (DL-H) levels. The noise power spectrum (NPS) and task transfer function (TTF) were measured. Thirty consecutive patients underwent low-dose radiation contrast-enhanced abdominal CT scans that were reconstructed using FBP, AV-30, AV-50, AV-80, and AV-100, and three levels of DLIR. The standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) of the hepatic parenchyma and paraspinal muscle were evaluated. Two radiologists assessed the subjective image quality and lesion diagnostic confidence using a 5-point Likert scale.

RESULTS: In the phantom study, both a higher DLIR and ASiR-V strength and a higher radiation dose led less noise. The NPS peak and average spatial frequency of the DLIR algorithms were closer to those of FBP, as the tube current increased and declined as the level of ASiR-V and DLIR strengthened. The NPS average spatial frequency of DL-L were higher than those of AISR-V. In clinical studies, AV-30 demonstrated a higher SD and lower SNR and CNR compared to DL-M and DL-H (P<0.05). For qualitative assessment, DL-M produced the highest qualitative image quality scores, with the exception of overall image noise (P<0.05). The NPS peak, average spatial frequency, and SD were the highest and the SNR, CNR, and subjective scores were the lowest with FBP.

CONCLUSIONS: Compared with FBP and ASiR-V, DLIR provided better image quality and noise texture both in the phantom and clinical studies, and DL-M maintained the best image quality and lesion diagnostic confidence in low-dose radiation abdominal CT.

PMID:37179954 | PMC:PMC10167467 | DOI:10.21037/qims-22-1227

Quant Imaging Med Surg. 2023 May 1;13(5):3080-3087. doi: 10.21037/qims-22-484. Epub 2023 Feb 6.

ABSTRACT

BACKGROUND: Incidental thyroid abnormalities found on magnetic resonance imaging (MRI) of the neck are not uncommon. This study aimed to investigate the prevalence of incidental thyroid abnormalities in the cervical spine MRI of the degenerative cervical spondylosis (DCS) population indicated for surgery and to identify patients who require additional workup based on the recommendations of the American College of Radiology (ACR).

METHODS: All consecutive patients with DCS and indications for cervical spine surgery from October 2014 to May 2019 in the Affiliated Hospital of Xuzhou Medical University were reviewed. All MRI scans of the cervical spine routinely include the thyroid. Cervical spine MRI scans were retrospectively evaluated for the prevalence, size, morphologic characteristics, and location of incidental thyroid abnormalities.

RESULTS: A total of 1,313 patients were included in the analysis, 98 (7.5%) of whom were found to have incidental thyroid abnormalities. The most frequent thyroid abnormality was thyroid nodules (5.3%), followed by goiters (1.4%). Other thyroid abnormalities included Hashimoto thyroiditis (0.4%) and thyroid cancer (0.5%). There was a statistically significant difference in age and sex between patients with DCS with and without incidental thyroid abnormalities (P=0.018 and P=0.007). Stratified by age, the results showed that the highest incidence of incidental thyroid abnormalities was found in patients aged 71 to 80 years (12.4%). Eighteen patients (1.4%) needed further ultrasound (US) and relevant workups.

CONCLUSIONS: Incidental thyroid abnormalities are common in cervical MRI, with a prevalence of 7.5% identified in patients with DCS. Incidental thyroid abnormalities are large or have suspicious imaging features, and further evaluation with a dedicated thyroid US examination should be completed before cervical spine surgery is undertaken.

PMID:37179951 | PMC:PMC10167457 | DOI:10.21037/qims-22-484

Quant Imaging Med Surg. 2023 May 1;13(5):3199-3212. doi: 10.21037/qims-22-879. Epub 2023 Mar 27.

ABSTRACT

BACKGROUND: It is of clinical importance to assess the histopathological features of rectal cancer. The adipose tissue microenvironment is closely associated with tumor formation and progression. The chemical shift-encoded magnetic resonance imaging (CSE-MRI) sequence can noninvasively quantify adipose tissue. In this study, we aimed to investigate the feasibility of using CSE-MRI and diffusion-weighted imaging (DWI) to predict the histopathological features of rectal adenocarcinoma.

METHODS: In this retrospective study, 84 patients with rectal adenocarcinoma and 30 healthy controls were consecutively enrolled at the Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology. CSE-MRI and DWI sequences were performed. The intratumoral proton density fat fraction (PDFF) and R2* of rectal tumors and normal rectal walls were measured. The histopathological features, including pathological T/N stage, tumor grade, mesorectum fascia (MRF) involvement, and extramural venous invasion (EMVI) status were analyzed. The Mann-Whitney test, Spearman correlation, and receiver operating characteristic (ROC) curves were used for statistical analyses.

RESULTS: Patients with rectal adenocarcinoma demonstrated significantly lower PDFF and R2* values than did the control participants (5.35%±1.70% vs. 11.55%±3.41%, P<0.001; 35.60 s^-1±7.30 s^-1 vs. 40.15 s^-1±5.72 s^-1, P=0.003). PDFF and R2* were significantly different in the discrimination of T/N stage, tumor grade, and MRF/EMVI status (P=0.000-0.005). A significant difference was only noted in the differentiation of the T stage for the apparent diffusion coefficient (ADC) (1.09±0.26×10^-3 mm²/s vs. 1.00±0.11×10^-3 mm²/s; P=0.001). PDFF and R2* exhibited positive correlations with all the histopathological features (r=0.306-0.734; P=0.000-0.005), while ADC was negatively correlated with the T stage (r=-0.380; P<0.001). PDFF demonstrated diagnostic ability, with a sensitivity of 95.00% and a specificity of 87.50%, while R2* had a sensitivity of 95.00% and a specificity of 79.20% in differentiating T stage; both demonstrated a better diagnostic performance than did ADC.

CONCLUSIONS: Quantitative CSE-MRI imaging might serve as a noninvasive biomarker for assessing the histopathological features of rectal adenocarcinoma.

PMID:37179942 | PMC:PMC10167423 | DOI:10.21037/qims-22-879

Quant Imaging Med Surg. 2023 May 1;13(5):2807-2821. doi: 10.21037/qims-22-729. Epub 2023 Mar 10.

ABSTRACT

BACKGROUND: T2* relaxation times in the spinal cartilage endplate (CEP) measured using ultra-short echo time magnetic resonance imaging (UTE MRI) reflect aspects of biochemical composition that influence the CEP’s permeability to nutrients. Deficits in CEP composition measured using T2* biomarkers from UTE MRI are associated with more severe intervertebral disc degeneration in patients with chronic low back pain (cLBP). The goal of this study was to develop an objective, accurate, and efficient deep-learning-based method for calculating biomarkers of CEP health using UTE images.

METHODS: Multi-echo UTE MRI of the lumbar spine was acquired from a prospectively enrolled cross-sectional and consecutive cohort of 83 subjects spanning a wide range of ages and cLBP-related conditions. CEPs from the L4-S1 levels were manually segmented on 6,972 UTE images and used to train neural networks utilizing the u-net architecture. CEP segmentations and mean CEP T2* values derived from manually- and model-generated segmentations were compared using Dice scores, sensitivity, specificity, Bland-Altman, and receiver-operator characteristic (ROC) analysis. Signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were calculated and related to model performance.

RESULTS: Compared with manual CEP segmentations, model-generated segmentations achieved sensitives of 0.80-0.91, specificities of 0.99, Dice scores of 0.77-0.85, area under the receiver-operating characteristic curve values of 0.99, and precision-recall (PR) AUC values of 0.56-0.77, depending on spinal level and sagittal image position. Mean CEP T2* values and principal CEP angles derived from the model-predicted segmentations had low bias in an unseen test dataset (T2* bias =0.33±2.37 ms, angle bias =0.36±2.65°). To simulate a hypothetical clinical scenario, the predicted segmentations were used to stratify CEPs into high, medium, and low T2* groups. Group predictions had diagnostic sensitivities of 0.77-0.86 and specificities of 0.86-0.95. Model performance was positively associated with image SNR and CNR.

CONCLUSIONS: The trained deep learning models enable accurate, automated CEP segmentations and T2* biomarker computations that are statistically similar to those from manual segmentations. These models address limitations with inefficiency and subjectivity associated with manual methods. Such techniques could be used to elucidate the role of CEP composition in disc degeneration etiology and guide emerging therapies for cLBP.

PMID:37179932 | PMC:PMC10167428 | DOI:10.21037/qims-22-729

Quant Imaging Med Surg. 2023 May 1;13(5):3185-3198. doi: 10.21037/qims-22-1017. Epub 2023 Apr 17.

ABSTRACT

BACKGROUND: Cardiac and respiratory motions in clinical positron emission tomography (PET) are a major contributor to inaccurate PET quantification and lesion characterisation. In this study, an elastic motion-correction (eMOCO) technique based on mass preservation optical flow is adapted and investigated for positron emission tomography-magnetic resonance imaging (PET-MRI) applications.

METHODS: The eMOCO technique was investigated in a motion management QA phantom and in twenty-four patients who underwent PET-MRI for dedicated liver imaging and nine patients for cardiac PET-MRI evaluation. Acquired data were reconstructed with eMOCO and gated motion correction techniques at cardiac, respiratory and dual gating modes, and compared to static images. Standardized uptake value (SUV), signal-to-noise ratio (SNR) of lesion activities from each gating mode and correction technique were measured and their means/standard deviation (SD) were compared using 2-ways ANOVA analysis and post-hoc Tukey’s test.

RESULTS: Lesions’ SNR are highly recovered from phantom and patient studies. The SD of the SUV resulted from the eMOCO technique was statistically significantly less (P<0.01) than the SD resulted from conventional gated and static SUVs at the liver, lung and heart.

CONCLUSIONS: The eMOCO technique was successfully implemented in PET-MRI in a clinical setting and produced the lowest SD compared to gated and static images, and hence provided the least noisy PET images. Therefore, the eMOCO technique can potentially be used on PET-MRI for improved respiratory and cardiac motion correction.

PMID:37179930 | PMC:PMC10167465 | DOI:10.21037/qims-22-1017

Quant Imaging Med Surg. 2023 May 1;13(5):3213-3221. doi: 10.21037/qims-22-1193. Epub 2023 Apr 3.

ABSTRACT

BACKGROUND: To compare qualitative and quantitative superb microvascular imaging (SMI) and determine the value of SMI in the diagnosis of thyroid nodules (TNs) ≤10 mm based on the Chinese Thyroid Imaging Reporting and Data System 4 (C-TIRADS 4).

METHODS: From October 2020 to June 2022, 106 patients with 109 C-TIRADS 4 (C-TR4) TNs (81 malignant, 28 benign) at the Peking Union Medical College Hospital were included. Qualitative SMI reflected the vascular pattern of the TNs and quantitative SMI was recorded by the vascular index (VI) of the nodules.

RESULTS: The VI was significantly higher in malignant nodules versus benign nodules both in the longitudinal (19.9±11.4 vs. 13.8±10.6, P=0.01) and transverse (20.2±12.1 vs. 11.3±8.7, P=0.001) sections. The area under the curve (AUC) of qualitative and quantitative SMI did not show a statistical difference in the longitudinal {0.657 [95% confidence interval (CI): 0.560-0.745] vs. 0.646 (95% CI: 0.549-0.735), P=0.79} and transverse [0.696 (95% CI: 0.600-0.780) vs. 0.725 (95% CI: 0.632-0.806), P=0.51] sections. Next, we combined qualitative and quantitative SMI to upgrade and downgrade the C-TIRADS classification. If a C-TR4B nodule had VIsum >12.2 or intra-nodular vascularity, the original C-TIRADS was upgraded to C-TR4C. If a C-TR4C or C-TR4B nodule manifested VIsum ≤12.2 and no intra-nodular vascularity, the original C-TIRADS was downgraded to C-TR4A. As a result, 18 C-TR4C nodules were downgraded to C-TR4A and 14 C-TR4B nodules were upgraded to C-TR4C. The new model of SMI + C-TIRADS showed high sensitivity (93.8%) and accuracy (79.8%).

CONCLUSIONS: There is no statistical difference between qualitative and quantitative SMI in the diagnosis of C-TR4 TNs. The combination of qualitative and quantitative SMI may have the potential to manage diagnosis of C-TR4 nodules.

PMID:37179929 | PMC:PMC10167443 | DOI:10.21037/qims-22-1193

Quant Imaging Med Surg. 2023 May 1;13(5):2860-2870. doi: 10.21037/qims-22-926. Epub 2023 Mar 8.

ABSTRACT

BACKGROUND: Open-wedge high tibial osteotomy (OWHTO) may cause adverse changes in the mechanical environment of the patellofemoral joint. For patients with lateral patellar compression syndrome or patellofemoral arthritis, intraoperative management is still challenging. The effect of lateral retinacular release (LRR) on patellofemoral joint mechanics after OWHTO remains unclear. Our study aimed to evaluate the effect of OWHTO and LRR on the patellar position based on lateral and axial radiographs of the knee joint.

METHODS: The study comprised 101 knees (OWHTO group) undergoing OWHTO alone and 30 knees (LRR group) undergoing OWHTO and concomitant LRR. The following radiological parameters were statistically analyzed preoperatively and postoperatively: femoral tibial angle (FTA), medial proximal tibial angle (MPTA), weight-bearing line percentage (WBLP), Caton-Deschamps index (CDI), Insall-Salvati index (ISI), lateral patellar tilt angle (LPTA), and lateral patellar shift (LPS). The follow-up duration ranged from 6 to 38 months, with a mean of 13.51±6.84 months in the OWHTO group and 12.47±7.81 months in the LRR group. The Kellgren-Lawrence (KL) grading system was used to evaluate changes in patellofemoral osteoarthritis (OA).

RESULTS: Regarding the patellar height, preliminary analysis demonstrated a statistically significant decrease in the CDI and ISI in both groups (P<0.05). However, there was no significant difference in changes in CDI or ISI between the groups (P>0.05). In the OWHTO group, although there was a significant increase in the LPTA (P=0.033), the postoperative decrease in the LPS was not significant (P=0.981). In the LRR group, both the LPTA and LPS significantly decreased postoperatively (P=0.000). The mean changes in LPS were 0.03 mm in the OWHTO group and 1.44 mm in the LRR group, indicating a significant change in LPS (P=0.000). However, there was no significant difference in changes in LPTA between the groups, which was contrary to our expectations. Imaging showed no change in patellofemoral OA in the LRR group and progressive changes (from KL grade I to II) in patellofemoral OA in 2 (1.98%) patients in the OWHTO group.

CONCLUSIONS: OWHTO can cause a significant decrease in patellar height and an increase in lateral tilt. LRR can significantly improve the lateral tilt and shift of the patella. The concomitant arthroscopic LRR should be considered for the treatment of patients with lateral patellar compression syndrome or patellofemoral arthritis.

PMID:37179926 | PMC:PMC10167460 | DOI:10.21037/qims-22-926

Quant Imaging Med Surg. 2023 May 1;13(5):3088-3103. doi: 10.21037/qims-22-1008. Epub 2023 Mar 13.

ABSTRACT

BACKGROUND: Recent reports have shown the potential for deep learning (DL) models to automatically segment of Couinaud liver segments and future liver remnant (FLR) for liver resections. However, these studies have mainly focused on the development of the models. Existing reports lack adequate validation of these models in diverse liver conditions and thorough evaluation using clinical cases. This study thus aimed to develop and perform a spatial external validation of a DL model for the automated segmentation of Couinaud liver segments and FLR using computed tomography (CT) in various liver conditions and to apply the model prior to major hepatectomy.

METHODS: This retrospective study developed a 3-dimensional (3D) U-Net model for the automated segmentation of Couinaud liver segments and FLR on contrast-enhanced portovenous phase (PVP) CT scans. Images were obtained from 170 patients from January 2018 to March 2019. First, radiologists annotated the Couinaud segmentations. Then, a 3D U-Net model was trained in Peking University First Hospital (n=170) and tested in Peking University Shenzhen Hospital (n=178) in cases with various liver conditions (n=146) and in candidates for major hepatectomy (n=32). The segmentation accuracy was evaluated using the dice similarity coefficient (DSC). Quantitative volumetry to evaluate the resectability was compared between manual and automated segmentation.

RESULTS: The DSC in the test data sets 1 and 2 for segments I to VIII was 0.93±0.01, 0.94±0.01, 0.93±0.01, 0.93±0.01, 0.94±0.00, 0.95±0.00, 0.95±0.00, and 0.95±0.00, respectively. The mean automated FLR and FLR% assessments were 493.51±284.77 mL and 38.53%±19.38%, respectively. The mean manual FLR and FLR% assessments were 500.92±284.38 mL and 38.35%±19.14%, respectively, in test data sets 1 and 2. For test data set 1, when automated segmentation of the FLR% was used, 106, 23, 146, and 57 cases were categorized as candidates for a virtual major hepatectomy of types 1, 2, 3, and 4, respectively; however, when manual segmentation of the FLR% was used, 107, 23, 146, and 57 cases were categorized as candidates for a virtual major hepatectomy of types 1, 2, 3, and 4, respectively. For test data set 2, all cases were categorized as candidates for major hepatectomy when automated and manual segmentation of the FLR% was used. No significant differences in FLR assessment (P=0.50; U=185,545), FLR% assessment (P=0.82; U=188,337), or the indications for major hepatectomy were noted between automated and manual segmentation (McNemar test statistic 0.00; P>0.99).

CONCLUSIONS: The DL model could be used to fully automate the segmentation of Couinaud liver segments and FLR with CT prior to major hepatectomy in an accurate and clinically practicable manner.

PMID:37179921 | PMC:PMC10167444 | DOI:10.21037/qims-22-1008

Quant Imaging Med Surg. 2023 May 1;13(5):2933-2940. doi: 10.21037/qims-22-186. Epub 2023 Mar 9.

ABSTRACT

BACKGROUND: Coronary computed tomography angiography (CTA) has been increasingly used to identify the degree of coronary artery stenosis and plaque lesions in vessels. This study evaluated the feasibility of using high-definition (HD) scanning with high-level deep learning image reconstruction (DLIR-H) to improve the image quality and spatial resolution when imaging calcified plaques and stents in coronary CTA as compared to the standard definition (SD) reconstruction mode with adaptive statistical iterative reconstruction-V (ASIR-V).

METHODS: A total of 34 patients (age 63.3±10.9 years; 55.88% female) with calcified plaques and/or stents who underwent coronary CTA in HD-mode were included in this study. Images were reconstructed with SD-ASIR-V, HD-ASIR-V, and HD-DLIR-H. Subjective image quality with image noise and clarity of vessels, calcifications, and stented lumens was evaluated by 2 radiologists using a 5-point scale. The kappa (κ) test was used to analyze the interobserver agreement. Objective image quality with image noise, signal-to-noise-ratio (SNR), and contrast-to-noise-ratio (CNR) was measured and compared. Image spatial resolution and beam-hardening artifacts (BHAs) were also evaluated using the calcification diameter and CT numbers in 3 points along the stented lumen (inside, at the proximal and distal ends just outside stent).

RESULTS: There were 45 calcified plaques and 4 coronary stents. HD-DLIR-H images had the highest overall image quality score (4.50±0.63) with the lowest image noise (22.59±3.59 HU) and the highest SNR (18.30±4.88) and CNR (26.56±6.33), followed by SD-ASIR-V50% image quality score (4.06±2.49), image noise (35.02±8.09 HU), SNR (12.77±1.59), CNR(15.67±1.92) and HD-ASIR-V50% image quality score (3.90±0.64), image noise (57.7±12.03 HU), SNR (8.16±1.86), CNR (10.01±2.39). HD-DLIR-H images also had the smallest calcification diameter measurement (2.36±1.58 mm), followed by HD-ASIR-V50% (3.46±2.07 mm) and SD-ASIR-V50% (4.06±2.49 mm). HD-DLIR-H images had the closest CT value measurements for the 3 points along the stented lumen, indicating much less BHA. Interobserver agreement on the image quality assessment was good to excellent (HD-DLIR-H: κ value =0.783; HD-ASIR-V50%: κ value =0.789; SD-ASIR-V50%: κ value =0.671).

CONCLUSIONS: Coronary CTA with HD scan mode and DLIR-H significantly improves the spatial resolution for displaying calcifications and in-stent lumens while simultaneously reducing image noise.

PMID:37179907 | PMC:PMC10167454 | DOI:10.21037/qims-22-186