Unnecessary Biopsies Research Articles

Sonographic features of sternal pseudotumour in children

AbstractIntroductionSternal pseudotumour is an important but rare entity thought to be an inflammatory, non‐neoplastic lesion that can mimic tumours. The purpose of this paper was to illustrate the imaging features of this lesion to avoid unnecessary investigations.MethodsThe clinical notes and imaging features of four patients with a diagnosis of sternal pseudotumour were reviewed over a period from February 2016 to July 2019.ResultsAll patients were afebrile with no history of trauma. The median age at presentation was 12.5 months. The median length of symptoms prior to presentation was 3.5 days. One patient had a mildly elevated C‐reactive protein. Chest radiographs showed a pre‐sternal soft‐tissue mass, with or without osseous destruction of the subjacent sternum. Ultrasound showed a heterogeneous, hypoechoic pre‐sternal soft‐tissue mass with variable internal vascularity with extension between sternal ossification centres. CT and MRI showed an enhancing dumbbell‐shaped lesion with a pre‐sternal and retro‐sternal soft‐tissue component. The median time to complete resolution was 3 months. One patient had a biopsy that showed chronic inflammation and fibrosis.DiscussionThese lesions present in young children typically with a 1‐ to 2‐week history of a focal 2‐ to 4‐cm swelling over the sternum. The aetiology is unknown but may be on the basis of a yet‐to‐be identified pathogen. Inflammatory markers and cultures are normal or mildly elevated. Important differential considerations include sternal osteomyelitis or neoplastic causes such as Ewing sarcoma, rhabdomyosarcoma, Langerhans cell histiocytosis and infantile fibrosarcoma.ConclusionSternal pseudotumor is a rare but important entity to be aware of to avoid unnecessary invasive biopsy or further investigations. Our suggestion is that this is a ‘Don't touch’ lesion that requires close short‐interval follow‐up at a surgical outpatient clinic and with ultrasound until resolution.

Radiomics and artificial intelligence for risk stratification of pulmonary nodules: Ready for primetime?

Pulmonary nodules are ubiquitously found on computed tomography (CT) imaging either incidentally or via lung cancer screening and require careful diagnostic evaluation and management to both diagnose malignancy when present and avoid unnecessary biopsy of benign lesions. To engage in this complex decision-making, clinicians must first risk stratify pulmonary nodules to determine what the best course of action should be. Recent developments in imaging technology, computer processing power, and artificial intelligence algorithms have yielded radiomics-based computer-aided diagnosis tools that use CT imaging data including features invisible to the naked human eye to predict pulmonary nodule malignancy risk and are designed to be used as a supplement to routine clinical risk assessment. These tools vary widely in their algorithm construction, internal and external validation populations, intended-use populations, and commercial availability. While several clinical validation studies have been published, robust clinical utility and clinical effectiveness data are not yet currently available. However, there is reason for optimism as ongoing and future studies aim to target this knowledge gap, in the hopes of improving the diagnostic process for patients with pulmonary nodules.

Key learning on the promise and limitations of MRI in prostate cancer screening.

MRI retains its ability to reduce the harm of prostate biopsies by decreasing biopsy rates and the detection of indolent cancers in population-based screening studies aiming to find clinically significant prostate cancers. Limitations of low positive predictive values and high reader variability in diagnostic performance require optimisations in patient selection, imaging protocols, interpretation standards, diagnostic thresholds, and biopsy methods. Improvements in diagnostic accuracy could come about through emerging technologies like risk calculators and polygenic risk scores to select men for MRI. Furthermore, artificial intelligence and workflow optimisations focused on streamlining the diagnostic pathway, quality control, and assurance measures will improve MRI variability. CLINICAL RELEVANCE STATEMENT: MRI significantly reduces harm in prostate cancer screening, lowering unnecessary biopsies and minimizing the overdiagnosis of indolent cancers. MRI maintains the effective detection of high-grade cancers, thus improving the overall benefit-to-harm ratio in population-based screenings with or without using serum prostate-specific antigen (PSA) for patient selection. KEY POINTS: • The use of MRI enables the harm reduction benefits seen in individual early cancer detection to be extended to both risk-stratified and non-stratified prostate cancer screening populations. • MRI limitations include a low positive predictive value and imperfect reader variability, which require standardising interpretations, biopsy methods, and integration into a quality diagnostic pathway. • Current evidence is based on one-time point use of MRI in screening; MRI effectiveness in multiple rounds of screening is not well-documented.

Preoperative prediction of microsatellite instability status: development and validation of a pan-cancer PET/CT-based radiomics model.

The purpose of this study is to verify the feasibility of preoperative prediction of patients' microsatellite instability status by applying a PET/CT-based radiation model. This retrospective study ultimately included 142 patients. Three prediction models have been developed. The predictive performance of all models was evaluated by the receiver operating characteristic curve and area under the curve values. The PET/CT radiological histology score (Radscore) was calculated to evaluate the microsatellite instability status, and the corresponding nomogram was established. The correlation between clinical factors and radiological characteristics was analyzed to verify the value of radiological characteristics in predicting microsatellite instability status. Twelve features were retained to establish a comprehensive prediction model of radiological and clinical features. M phase of the tumor has been proven to be an independent predictor of microsatellite instability status. The receiver operating characteristic results showed that the area under the curve values of the training set and the validation set of the radiomics model were 0.82 and 0.75, respectively. The sensitivity, specificity, positive predictive value and negative predictive value of the training set were 0.72, 0.78, 0.83 and 0.66, respectively. The sensitivity, specificity, positive predictive value and negative predictive value of the validation set were 1.00, 0.50, 0.76 and 1.00, respectively. The risk of patients with microsatellite instability was calculated by Radscore and nomograph, and the cutoff value was -0.4385. The validity of the results was confirmed by the decision and calibration curves. Radiological models based on PET/CT can provide clinical and practical noninvasive prediction of microsatellite instability status of several different cancer types, reducing or avoiding unnecessary biopsy to a certain extent.

Improved cancer risk stratification of isoechoic thyroid nodules to reduce unnecessary biopsies using quantitative ultrasound.

Gray-scale ultrasound (US) is the standard-of-care for evaluating thyroid nodules (TNs). However, the performance is better for the identification of hypoechoic malignant TNs (such as classic papillary thyroid cancer) than isoechoic malignant TNs. Quantitative ultrasound (QUS) utilizes information from raw ultrasonic radiofrequency (RF) echo signal to assess properties of tissue microarchitecture. The purpose of this study is to determine if QUS can improve the cancer risk stratification of isoechoic TNs. Patients scheduled for TN fine needle biopsy (FNB) were recruited from the Thyroid Health Clinic at Boston Medical Center. B-mode US and RF data (to generate QUS parameters) were collected in 274 TNs (163 isoechoic, 111 hypoechoic). A linear combination of QUS parameters (CQP) was trained and tested for isoechoic [CQP(i)] and hypoechoic [CQP(h)] TNs separately and compared with the performance of conventional B-mode US risk stratification systems. CQP(i) produced an ROC AUC value of 0.937+/- 0.043 compared to a value of 0.717 +/- 0.145 (p >0.05) for the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) and 0.589 +/- 0.173 (p >0.05) for the American Thyroid Association (ATA) risk stratification system. In this study, CQP(i) avoids unnecessary FNBs in 73% of TNs compared to 55.8% and 11.8% when using ACR TI-RADS and ATA classification system. This data supports that a unique QUS-based classifier may be superior to conventional US stratification systems to evaluate isoechoic TNs for cancer and should be explored further in larger studies.

Diagnostic value comparison of the combination of prostate-specific membrane antigen-body PET/MR and the prostate health index with each alone in early diagnosis of prostate cancer

ObjectiveThis study aimed to figure out whether the combination of the prostate health index (PHI) and prostate-specific membrane antigen (PSMA)-PET/MR could improve the diagnostic accuracy for prostate cancer (PCa) than that of each individual method used alone. MethodsIn this prospective, observational study, 41 patients who underwent the systematic prostate biopsy between June 2019 and September 2022 were enrolled. Both the PHI test and 18F-PSMA-1007-PET/MR were performed prior to biopsies. The diagnostic accuracy of different models was compared by logistic regression, areas under the curve (AUCs) of the receiver operating characteristic and net reclassification index (NRI). ResultsAmong the 41 patients, 14 (34.1%) were pathologically diagnosed with PCa. The PHI in the PCa group was significantly higher than that in the benign group (44.4 vs. 35.0, p=0.048). Similarly, all the patients in the PCa group received positive results of 18F-PSMA-1007-PET/MR, of which the positive rate was significantly higher than that in benign group (100% vs. 62.96%, p=0.025). The 18F-PSMA-1007-PET/MR provided additional diagnostic values to the PHI (AUC: 0.802 vs. 0.692, p=0.025). However, there was no significant difference between the combination model and the 18F-PSMA-1007-PET/MR alone (AUC 0.802 vs. 0.685, p=0.071). The optimal PHI cutoff of the combination model is 32, with which the model could significantly reduce unnecessary biopsies (NRI: 22.22%, 95% confidence interval: 6.54%–37.90%, p=0.005). However, among patients with the PHI of ≥43.5, there was no significant difference between the combination model and the PHI alone (NRI: 11.11%, 95% confidence interval: −0.74%–22.97%, p=0.066). ConclusionThe combination of the PHI and 18F-PSMA-1007-PET/MR outperforms the PHI alone for predicting PCa, especially in avoiding unnecessary biopsies. However, for patients with the PHI of ≥43.5, the addition of 18F-PSMA-1007-PET/MR to the PHI does not yield additional benefits.

Creating a novel multiparametric magnetic resonance imaging-based biopsy strategy for reducing unnecessary prostate biopsies: a retrospective cohort study.

The overdiagnosis of prostate cancer (PCa) caused by unnecessary prostate biopsy has become a worldwide problem that urgently requires a solution. We aimed to reduce the unnecessary prostate biopsies and increase the detection rate of clinically significant PCa (csPCa) by creating a novel multiparametric magnetic resonance imaging (mpMRI)-based strategy. A total of 1,194 eligible patients who underwent transperineal prostate biopsies from January 2018 to December 2022 were included in this retrospective study. Of these patients, 1,080 who received prostate biopsies from January 2018 to July 2022 were regarded as cohort 1 for primary analysis, and 114 patients who received prostate biopsies from August 2022 to December 2022 were collected in cohort 2 for validation. All the mpMRI images were quantitatively evaluated by the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v. 2.1). The diagnostic performances were assessed through the receiver operating characteristic (ROC) curve and area under the curve (AUC) and were compared with the DeLong test. Cancer diagnosis-free survival analysis was performed using the Kaplan-Meier method and log-rank test. The primary endpoint of this study was clinically significant PCa with an International Society of Urological Pathology (ISUP) grade ≥2. In cohort 1, the results of ROC curves demonstrated that the PI-RADS score had a higher diagnostic accuracy (AUC =0.898 for any-grade PCa; AUC =0.917 for csPCa) than did the other clinical variables (P<0.001). Under the novel mpMRI-based biopsy strategy, all patients with PI-RADS 1 can safely avoid prostate biopsy. For patients with PI-RADS 2, prostate biopsy should be considered for patients with prostate-specific antigen density (PSAD) ≥0.3 ng/mL2 and prostate volume <65 mL. As for patients with PI-RADS 3, structured surveillance programs can be a viable option if PSAD <0.3 ng/mL2 and prostate volume ≥65 mL. Finally, patients with a PI-RADS score of 4 and 5 should undergo prostate biopsy due to the high probability of clinically significant PCa. In the validation analysis of cohort 2, 48 patients were placed into a biopsy-spared group with no csPCa cases, while 66 patients were placed in a biopsy-needed group, with an csPCa detection rate of 50.0%. Overall, the novel strategy demonstrated a sensitivity, specificity, positive predictive value, and negative predictive value of 98.9%, 57.5%, 50.5%, and 99.2%, respectively, for diagnosing csPCa. An mpMRI-based biopsy strategy can effectively avoid about 40% of prostate biopsies and maintain a high detection rate for clinically significant PCa. It can further provide valuable guidance for patients and physicians in considering the necessity of prostate biopsy.

Stockholm3 validation in a multi-ethnic cohort for prostate cancer (SEPTA) detection: A multicentered, prospective trial.

262 Background: Stockholm3 is a multiparametric blood test incorporating germline risk, proteins and clinical data which improves prostate cancer (PC) risk stratification compared to PSA, however no validation exists in an ethnically diverse population. Methods: SEPTA is a prospective trial (NCT04583072) aimed to validate Stockholm3 in an ethnically diverse cohort of men referred for prostate biopsy at 17 North American sites from 2019 to 2023 (supplemented with bio-banked specimens 2008-2020). The trial had two prespecified primary aims when comparing Stockholm3 (≥15) compared to PSA (≥4 ng/ml): (1) Demonstrate non-inferior sensitivity in detecting clinically significant PC (csPC) (defined as ISUP Gleason Grade group ≥2) compared to PSA (non-inferiority margin of 20%). (2) Prove superior specificity thereby reducing the number of biopsies compared to PSA in men with benign or ISUP 1 biopsies. Both aims were assessed using a one-sided alpha of 0.025. A secondary aim was to evaluate Stockholm3 and PSA across ethnic subgroups. Statistical analysis plans were published before the analysis commenced. Results: The study involved 2,129 biopsied participants, categorized into self-identified groups: African American/Black (24%), White/Caucasian (46%), Hispanic/Latino (14%), and Asian (16%). Median participant age was 63 years. PSA and Stockholm3 median values were 6.1 ng/mL and 17, respectively. A total of 16% underwent MRI-targeted biopsies and 20% had a prior benign biopsy. On either systematic or targeted biopsy, csPC was found in 29%, 14% had ISUP 1 cancer, and 57% benign. The detection rate for csPC across groups were: African American/Black (37%), White/Caucasian (28%), Hispanic/Latino (29%), and Asian (21%). Overall, Stockholm3≥15 showed non-inferior sensitivity compared to PSA≥4 ng/ml (relative sensitivity: 0.95 [95% CI: 0.92-0.99]) and nearly 3 times superior specificity (relative specificity: 2.91 [95% CI: 2.63-3.22]). Results were consistent across ethnic subgroups: non-inferior sensitivity (0.91-0.98) and superior specificity (2.51-4.70). Stockholm3 ≥15 would have reduced benign and ISUP 1 biopsies by 45% overall and between 42-52% across ethnic subgroups compared to PSA ≥4 ng/ml. Stockholm3 exhibited higher AUC (0.82) compared to PSA (0.66), with similar trends in ethnic subgroups. Conclusions: In an ethnically diverse population, Stockholm3 would significantly reduce unnecessary prostate biopsies and diagnosis of ISUP 1 cancer at a similar sensitivity of PSA for detecting clinically significant cancer. Clinical trial information: NCT04583072 . [Table: see text]

Advances in radiology and pathology of prostate cancer: a review for the pathologist.

Multiparametric magnetic resonance imaging (mpMRI) has improved systematic prostate biopsy procedures in the diagnosis of clinically significant prostate cancer (csPCa) by reducing the number of unnecessary biopsies; numerous level one evidence studies have confirmed the accuracy of MRI-targeted biopsy, but, still today, systematic prostate biopsy is recommended to reduce the 15-20% false negative rate of mpMRI. New advanced imaging has been proposed to detect suspicious lesions and perform targeted biopsies especially when mpMRI cannot be performed. Transrectal ultrasound (TRUS) modalities are emerging as methods with greater sensitivity and specificity for the detection of PCa compared to the traditional TRUS; these techniques include elastography and contrast-enhanced ultrasound, as well as improved B-mode and Doppler techniques. These modalities can be combined to define a novel ultrasound approach: multiparametric ultrasound (mpUS). More recently, micro-ultrasound (MicroUS) and prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) have demonstrated to be sensitive for the detection of primary prostatic lesions resulting highly correlated with the aggressiveness of the primary prostatic tumor. In parallel, artificial intelligence is advancing and is set out to deeply change both radiology and pathology. In this study we address the role, advantages and shortcomings of novel imaging techniques for Pca, and discuss future directions including the applications of artificial intelligence-based techniques to imaging as well as histology. The significance of these findings for the practicing pathologist is discussed.

The impact of pre-biopsy MRI and additional testing on prostate cancer screening outcomes: A rapid review.

This work aims to examine the latest evidence on the impact of pre-biopsy MRI, in addition to prostate-specific antigen (PSA) testing, on health outcomes and quality of life. We conducted a literature search including PubMed and Cochrane Central Register of Controlled Trials (CENTRAL) databases, with a limited scan of (i) guidelines and (ii) references from trial reports, from January 2005 to 25th January 2023. Two independent reviewers selected randomised controlled trials (RCT) and cohort studies which met our inclusion criteria. One hundred thirty-seven articles were identified, and seven trial articles were selected. Trial interventions were as follows: (i) PSA blood test, (ii) additional tests such as pre-biopsy multiparametric magnetic resonance imaging (mpMRI) and Biparametric MRI (bpMRI), and (iii) MRI targeted biopsy and standard biopsy. Compared with standard biopsy, MRI-based interventions led to increased detection of clinically significant cancers in three studies and decreased detection of clinically insignificant cancer (Gleason grade 3 + 3) in four studies. However, PROstate Magnetic resonance Imaging Study (PROMIS) and Stockholm3 with MRI (STHLM3-MRI) studies reported different trends depending on the scenario studied in PROMIS (MRI triage and MRI directed biopsy vs. MRI triage and standard biopsy) and thresholds used in STHLM3-MRI (≥0·11 and ≥0·15). MRI also helped 8%-49% of men avoid biopsy, in six out of seven studies, but not in STHLM3-MRI at ≥0.11. Interestingly, the proportion of men who experienced sepsis and UTI was low across studies. This review found that a combination of approaches, centred on the use of pre-biopsy MRI, may improve the detection of clinically significant cancers and reduce (i) the diagnosis of clinically insignificant cancers and (ii) unnecessary biopsies, compared with PSA testing and standard biopsy alone. However, the impact of such interventions on longer term outcomes such as prostate cancer-specific mortality has not yet been assessed.

Predictors of Clonality and Underlying Mastocytosis in Mast Cell Activation Syndromes.

Mast cell (MC) activation can present with a wide range of symptoms. The mechanisms that cause such activation are varied. One of them is the presence of clonal MCs which is defined, within other possible changes, by the presence of a somatic, activating mutation in the KIT gene. The clinical course and prognosis of patients with this underlying disease may be different from other causes of MC activation (MCA). For this reason, it is important to early diagnose, or at least suspect, which patients with MCA are due to clonal MCs. The diagnosis of clonality must be made in a comprehensive manner. However, this paper reviews chronologically each of the stages from the patient's first visit to the doctor's office which can be indicative of clonality: clinical presentation of MCA, physical examination, analytical determinations of tryptase, and/or KIT mutational analysis and bone involvement, among others. The different clonality predictive scores proposed are also reviewed and compared. Although the gold standard for the diagnosis of certainty of MC clonality is the performance of a bone marrow (BM) biopsy, there are clinical symptoms, signs, and biological parameters suggestive of clonality, as well as predictive scores, which can guide (or rule out) an early diagnosis and avoid unnecessary BM biopsies.

Phytotherapy Might Have a Role in Reducing Unnecessary Prostate Biopsies: Results from an Exploratory, Randomized Controlled Trial of Two Different Phytotherapeutic Agents.

We aimed to evaluate the impact of two different phytotherapeutic agents on decision making regarding prostate biopsy for patients with higher-than-normal prostate-specific antigen (PSA) levels. From June 2022 to May 2023, all patients attending two urological institutions due to higher-than-normal PSA levels were randomized to receive either oral capsules of Curcuma Longa, Boswellia, Pinus pinaster and Urtica dioica (Group A) or Serenoa Repens 320 mg (Group B) for 3 months. At the follow-up visit after 3 months, all patients underwent PSA tests and multiparametric magnetic resonance imaging (mpMRI). In the per-protocol analysis, data from 66 patients in Group A and 76 in Group B were analyzed. Fifty patients in Group A (75.7%) showed a significant reduction in total PSA compared to forty-nine in Group B (64.4%) (p < 0.001). Twenty-eight patients had PI-RADS III or higher in mpMRI: twelve in Group A and fourteen in Group B. Twenty-three patients (34.8%) in Group A and fifty-nine (77.6%) in Group B (p < 0.001) underwent prostate biopsy based on the mpMRI findings and PSA values. Three patients in Group A showed a significant reduction in total PSA values while having positive mpMRI findings (6%) compared with nine in Group B (19.5%) (p < 0.001). On the contrary, 7 patients in Group A did not show significant reduction in total PSA values and had negative mpMRI findings (43%) compared to 22 in Group B (81.4%) (p < 0.001). In conclusion, a three-month course of a combination of Curcuma Longa, Boswellia, Pinus pinaster and Urtica dioica seems to be an interesting tool to avoid unnecessary prostate biopsies among men with higher-than-normal PSA levels.

Dual-modal radiomics nomogram based on contrast-enhanced ultrasound to improve differential diagnostic accuracy and reduce unnecessary biopsy rate in ACR TI-RADS 4–5 thyroid nodules

BackgroundAmerican College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS, TR) 4 and 5 thyroid nodules (TNs) demonstrate much more complicated and overlapping risk characteristics than TR1-3 and have a rather wide range of malignancy possibilities (> 5%), which may cause overdiagnosis or misdiagnosis. This study was designed to establish and validate a dual-modal ultrasound (US) radiomics nomogram integrating B-mode ultrasound (BMUS) and contrast-enhanced ultrasound (CEUS) imaging to improve differential diagnostic accuracy and reduce unnecessary fine needle aspiration biopsy (FNAB) rates in TR 4–5 TNs.MethodsA retrospective dataset of 312 pathologically confirmed TR4-5 TNs from 269 patients was collected for our study. Data were randomly divided into a training dataset of 219 TNs and a validation dataset of 93 TNs. Radiomics characteristics were derived from the BMUS and CEUS images. After feature reduction, the BMUS and CEUS radiomics scores (Rad-score) were built. A multivariate logistic regression analysis was conducted incorporating both Rad-scores and clinical/US data, and a radiomics nomogram was subsequently developed. The performance of the radiomics nomogram was evaluated using calibration, discrimination, and clinical usefulness, and the unnecessary FNAB rate was also calculated.ResultsBMUS Rad-score, CEUS Rad-score, age, shape, margin, and enhancement direction were significant independent predictors associated with malignant TR4-5 TNs. The radiomics nomogram involving the six variables exhibited excellent calibration and discrimination in the training and validation cohorts, with an AUC of 0.873 (95% CI, 0.821–0.925) and 0.851 (95% CI, 0.764–0.938), respectively. The marked improvements in the net reclassification index and integrated discriminatory improvement suggested that the BMUS and CEUS Rad-scores could be valuable indicators for distinguishing benign from malignant TR4-5 TNs. Decision curve analysis demonstrated that our developed radiomics nomogram was an instrumental tool for clinical decision-making. Using the radiomics nomogram, the unnecessary FNAB rate decreased from 35.3 to 14.5% in the training cohort and from 41.5 to 17.7% in the validation cohorts compared with ACR TI-RADS.ConclusionThe dual-modal US radiomics nomogram revealed superior discrimination accuracy and considerably decreased unnecessary FNAB rates in benign and malignant TR4-5 TNs. It could guide further examination or treatment options.

Knot-and-ear sign: a pathognomonic ultrasonographic feature of suture granuloma after thyroid surgery.

This study investigated the clinical and ultrasonographic (US) findings of suture granulomas and recurrent tumors, and aimed to identify specific characteristics of suture granulomas through an experimental study. This retrospective study included 20 pathologically confirmed suture granulomas and 40 recurrent tumors between January 2010 and December 2020. The clinical findings included suture material, surgery, and initial TNM stage. The US findings included shape, size, margin, echogenicity, heterogeneity, vascularity, and internal echogenic foci. The distribution, paired appearance, and "knot-and-ear" appearance of internal echogenic foci were assessed. An experiment using pork meat investigated the US configuration of suture knots. Eighteen patients with 20 suture granulomas (15 women; mean age, 52±13 years) and 37 patients with 40 recurrent tumors (24 women; 54±18 years) were included. Patients with suture granulomas exhibited earlier initial T and N stages than those with recurrent tumors. The knot-and-ear appearance, defined as an echogenic dot accompanied by two adjacent echogenic dots or lines based on experimental findings, was observed in 50% of suture granulomas, but not in recurrent tumors (P<0.001). Central internal echogenic foci (68.8%, P=0.023) and paired appearance (75.0%, P<0.001) were more frequent in suture granulomas. During follow-up, 94.1% of suture granulomas shrunk. The knot-and-ear appearance is a potential pathognomonic finding of suture granuloma, and central internal echogenic foci with paired appearance were typical US features. Clinically, suture granulomas showed early T and N stages and size reduction during follow-up. Understanding these features can prevent unnecessary biopsy or diagnostic surgery.

A neural network with a human learning paradigm for breast fibroadenoma segmentation in sonography

BackgroundBreast fibroadenoma poses a significant health concern, particularly for young women. Computer-aided diagnosis has emerged as an effective and efficient method for the early and accurate detection of various solid tumors. Automatic segmentation of the breast fibroadenoma is important and potentially reduces unnecessary biopsies, but challenging due to the low image quality and presence of various artifacts in sonography.MethodsHuman learning involves modularizing complete information and then integrating it through dense contextual connections in an intuitive and efficient way. Here, a human learning paradigm was introduced to guide the neural network by using two consecutive phases: the feature fragmentation stage and the information aggregation stage. To optimize this paradigm, three fragmentation attention mechanisms and information aggregation mechanisms were adapted according to the characteristics of sonography. The evaluation was conducted using a local dataset comprising 600 breast ultrasound images from 30 patients at Suining Central Hospital in China. Additionally, a public dataset consisting of 246 breast ultrasound images from Dataset_BUSI and DatasetB was used to further validate the robustness of the proposed network. Segmentation performance and inference speed were assessed by Dice similarity coefficient (DSC), Hausdorff distance (HD), and training time and then compared with those of the baseline model (TransUNet) and other state-of-the-art methods.ResultsMost models guided by the human learning paradigm demonstrated improved segmentation on the local dataset with the best one (incorporating C3ECA and LogSparse Attention modules) outperforming the baseline model by 0.76% in DSC and 3.14 mm in HD and reducing the training time by 31.25%. Its robustness and efficiency on the public dataset are also confirmed, surpassing TransUNet by 0.42% in DSC and 5.13 mm in HD.ConclusionsOur proposed human learning paradigm has demonstrated the superiority and efficiency of ultrasound breast fibroadenoma segmentation across both public and local datasets. This intuitive and efficient learning paradigm as the core of neural networks holds immense potential in medical image processing.

Development and validation of a predictive model based on clinical and MpMRI findings to reduce additional systematic prostate biopsy

ObjectivesTo develop and validate a predictive model based on clinical features and multiparametric magnetic resonance imaging (mpMRI) to reduce unnecessary systematic biopsies (SBs) in biopsy-naïve patients with suspected prostate cancer (PCa).MethodsA total of 274 patients who underwent combined cognitive MRI-targeted biopsy (MRTB) with SB were retrospectively enrolled and temporally split into development (n = 201) and validation (n = 73) cohorts. Multivariable logistic regression analyses were used to determine independent predictors of clinically significant PCa (csPCa) on cognitive MRTB, and the clinical, MRI, and combined models were established respectively. Area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analyses were assessed.ResultsProstate imaging data and reporting system (PI-RADS) score, index lesion (IL) on the peripheral zone, age, and prostate-specific antigen density (PSAD) were independent predictors and included in the combined model. The combined model achieved the best discrimination (AUC 0.88) as compared to both the MRI model incorporated by PI-RADS score, IL level, and zone (AUC 0.86) and the clinical model incorporated by age and PSAD (AUC 0.70). The combined model also showed good calibration and enabled great net benefit. Applying the combined model as a reference for performing MRTB alone with a cutoff of 60% would reduce 43.8% of additional SB, while missing 2.9% csPCa.ConclusionsThe combined model based on clinical and mpMRI findings improved csPCa prediction and might be useful in making a decision about which patient could safely avoid unnecessary SB in addition to MRTB in biopsy-naïve patients.Critical relevance statementThe combined model based on clinical and mpMRI findings improved csPCa prediction and might be useful in making a decision about which patient could safely avoid unnecessary SB in addition to MRTB in biopsy-naïve patients.Key points• Age, PSAD, PI-RADS score, and peripheral index lesion were independent predictors of csPCa.• Risk models were used to predict the probability of detecting csPCa on cognitive MRTB.• The combined model might reduce 43.8% of unnecessary SBs, while missing 2.9% csPCa.Graphical

Is multiparametric MRI always needed in biopsy-naïve patients with abnormal digital rectal examination? A single-institutional experience combining clinical and micro-ultrasonography-based factors to optimize prostate cancer detection.

To assess the diagnostic performance of microultrasound-targeted biopsy (microUSTBx) and systematic biopsy (SBx) in detecting clinically significant prostate cancer (csPCa) among men with abnormal digital rectal examination (DRE) and suspicious lesions at multiparametric magnetic resonance imaging (mpMRI), and to compare the diagnostic performance of this approach with a mpMRI-guided targeted biopsy (MTBx) plus SBx-based strategy. Biopsy-naïve men with suspicious lesions at mpMRI and abnormal DRE were prospectively evaluated between October 2017 and January 2023. csPCa detection rate by microUSTBx plus SBx and MTBx plus SBx was assessed and then compared by McNemar's test. The added value of prostate-specific antigen density (PSAd) was also evaluated. Overall, 182 biopsy naïve men were included. MicroUSTBx plus SBx achieved comparable detection rate to MTBx plus SBx in diagnosis of ciPCa and csPCa (ciPCa: 9.3% [17/182] vs 10% [19/182]; csPCa: 63% [114/182] vs 62% [113/182]). MicroUSTBx outperformed MTBx (ciPCa: 5.5% [10/182] vs 6.0% [11/182]; csPCa: 57% [103/182] vs 54% [99/182]). Using microUSTBx plus SBx would have avoided 68/182 (37%) unnecessary mpMRI, while missing only 2/116 (1.7%) csPCa. The decision curve analysis of suspicious microUS plus PSAd ≥ 0.15ng/ml showed higher net benefit in the ability to identify true positives and reduce the number of unnecessary prostate biopsy in this subcategory of patients. The combination of microUSTBx and SBx showed equal diagnostic performance to an mpMRI-based approach in biopsy-naïve patients with an abnormal DRE. The combination of this approach with PSAd maximize the diagnostic accuracy while lowering the need for unnecessary biopsies.

Impression cytology of ocular surface in xeroderma pigmentosum.

To describe cellular alterations detected by impression cytology of the ocular surface in patients with xeroderma pigmentosum. The secondary objective was to assess the reliability of impression cytology in diagnosing ocular surface squamous neoplasia. Patients with xeroderma pigmentosum underwent a single-day complete ophthalmological examination and impression cytology for ocular surface evaluation using 13 mm diameter mixed cellulose esters membrane filters and combined staining with Periodic Acid Schiff, Hematoxylin and Eosin, and Papanicolaou stains followed by microscopic analysis. The cytological findings were correlated with the clinical diagnosis. The impression cytology findings at baseline and one-year follow-up were correlated with the clinical course (no tumor, treated tumor, residual tumor recurrent tumor, new tumor). Of the 42 patients examined, impression cytology was performed in 62 eyes of 34 participants (65% females). The mean age of patients was 29.6 ± 17 years (range 7-62). Fifteen eyes had a clinical diagnosis of ocular surface squamous neoplasia. Impression cytology showed goblet cells (47, 75%), inflammatory cells (12, 19%), keratinization (5, 8%), and squamous metaplasia (30, 48%). Impression cytology was positive for atypical cells in 18 patients (12 with and 6 without ocular surface squamous neoplasia). The sensitivity, specificity, positive predictive value, and negative predictive value of impression cytology (at baseline) for diagnosis of ocular surface squamous neoplasia were 80%, 87%, 67%, and 93%, respectively, using clinical diagnosis of ocular surface squamous neoplasia as the reference standard. Impression cytology has a moderate positive predictive value for the diagnosis of ocular surface squamous neoplasia in patients with xeroderma pigmentosum. However, the lack of detection of atypical cells on impression cytology has a high negative predictive value for ocular surface squamous neoplasia. Integration of impression cytology in the long-term management of high-risk patients, such as patients with xeroderma pigmentosum, can avoid unnecessary diagnostic biopsies.

Cytomorphological Patterns of AFB Positive Tubercular Lymphadenitis: A Cross-sectional Study

Introduction: Tuberculosis (TB) remains a global threat despite advancements in diagnostic technologies and treatment options. Tubercular lymphadenitis is the most common presentation of Extra Pulmonary Tuberculosis (EPTB) in developing countries, accounting for approximately 30-52% of cases. Fine Needle Aspiration Cytology (FNAC) plays a crucial role in the cost- effective and efficient outpatient diagnosis of tubercular lymphadenitis. Understanding the different cytomorphological patterns and Acid Fast Bacilli (AFB) density in tubercular lymphadenitis aids in early diagnosis, management, and reducing morbidity and mortality. Aim: To analyse the various cytomorphological patterns observed in tubercular lymphadenitis, along with AFB density. Materials and Methods: The present cross-sectional cytomorphological study study was conducted between September and October 2021. Data from September 2020 to August 2021 were collected from the records of Shanthabai Devarao Shivaram(SDS) Tuberculosis Research Centre and Rajiv Gandhi Institute of Chest Diseases, a tertiary care hospital in Bengaluru, Karnataka, India. Out of a total of 128 patients with lymphadenopathy who underwent FNAC, four cases were excluded due to failed aspiration. The remaining 124 cases were available for analysis. Smears that exhibited features suggestive of tuberculosis were selected and categorised based on cytomorphological patterns into the following groups: Pattern-1 (Exudative), Pattern-2 (Epithelioid granuloma without necrosis), Pattern-3 (Epithelioid granuloma with necrosis), and Pattern-4 (Predominantly Necrosis without epithelioid granuloma). Ziehl-Neelsen (ZN) stained AFB positive smears were further categorised into four groups based on mycobacterial load. The categories included scant (1-9 AFB in 100 fields), 1+ (10-99 AFB in 100 fields), 2+ (1-10 AFB per field), and 3+ (&gt;10 AFB per field). Higher numbers indicated greater infectivity. Statistical analysis was performed using the Chi-square test. A probability level of less than 0.05 (p&lt;0.05) was considered statistically significant. Results: Out of the 124 cases studied, 81 (65.32%) were females and 43 (34.68%) were males, with a female preponderance (1.9:1). The overall prevalence of tubercular lymphadenopathy was 89 cases (71.77%), with Pattern 4 (Acellular necrosis without granuloma) being the most common cytomorphological pattern 25 cases (28.09%) followed closely by Pattern-2 (Epithelioid cell granuloma without necrosis) 23 cases (25.84%). AFB positivity was observed in 57 cases (64.04%). Pattern-1 (Exudative pattern) showed 100% AFB positivity (21 out of 21 cases), while Pattern 4 (Predominantly necrosis without epithelioid granuloma) demonstrated 92% AFB positivity (23 out of 25 cases). Conclusion: Understanding the various cytomorphological patterns in tubercular lymphadenitis is crucial for its diagnosis. Additionally, identifying AFB positivity, acid-fast bacilli distribution, and Bacterial Index (BI) in various patterns aids in planning early treatment and ensuring a favourable prognosis. FNAC serves as an easy, inexpensive, and quick procedure that can help avoid unnecessary surgical intervention or biopsy in the diagnosis of tubercular lymphadenitis.

Dermoscopy-based Radiomics Help Distinguish Basal Cell Carcinoma and Actinic Keratosis: A Large-scale Real-world Study Based on a 207-combination Machine Learning Computational Framework.

This study has used machine learning algorithms to develop a predictive model for differentiating between dermoscopic images of basal cell carcinoma (BCC) and actinic keratosis (AK). We compiled a total of 904 dermoscopic images from two sources - the public dataset (HAM10000) and our proprietary dataset from the First Affiliated Hospital of Dalian Medical University (DAYISET 1) - and subsequently categorised these images into four distinct cohorts. The study developed a deep learning model for quantitative analysis of image features and integrated 15 machine learning algorithms, generating 207 algorithmic combinations through random combinations and cross-validation. The final predictive model, formed by integrating XGBoost with Lasso regression, exhibited effective performance in the differential diagnosis of BCC and AK. The model demonstrated high sensitivity in the training set and maintained stable performance in three validation sets. The area under the curve (AUC) value reached 1.000 in the training set and an average of 0.695 in the validation sets. The study concludes that the constructed discriminative diagnostic model based on machine learning algorithms has excellent predictive capabilities that could enhance clinical decision-making efficiency, reduce unnecessary biopsies, and provide valuable guidance for further treatment.