Błędy w diagnostyce ultrasonograficznej nerek, moczowodów oraz pęcherza moczowego

Prediction of kidney function and chronic kidney disease (CKD) through kidney ultrasound imaging has long been considered desirable in clinical practice because of its safety, convenience, and affordability. However, this highly desirable approach is beyond the capability of human vision. We developed a deep learning approach for automatically determining the estimated glomerular filtration rate (eGFR) and CKD status. We exploited the transfer learning technique, integrating the powerful ResNet model pretrained on an ImageNet dataset in our neural network architecture, to predict kidney function based on 4,505 kidney ultrasound images labeled using eGFRs derived from serum creatinine concentrations. To further extract the information from ultrasound images, we leveraged kidney length annotations to remove the peripheral region of the kidneys and applied various data augmentation schemes to produce additional data with variations. Bootstrap aggregation was also applied to avoid overfitting and improve the model’s generalization. Moreover, the kidney function features obtained by our deep neural network were used to identify the CKD status defined by an eGFR of <60 ml/min/1.73 m 2 . A Pearson correlation coefficient of 0.741 indicated the strong relationship between artificial intelligence (AI)- and creatinine-based GFR estimations. Overall CKD status classification accuracy of our model was 85.6% —higher than that of experienced nephrologists (60.3%–80.1%). Our model is the first fundamental step toward realizing the potential of transforming kidney ultrasound imaging into an effective, real-time, distant screening tool. AI-GFR estimation offers the possibility of noninvasive assessment of kidney function, a key goal of AI-powered functional automation in clinical practice.

show abstract

“…5 Furthermore, the assigned score of each parameter remains subjective with undefined interobserver reliability. 5,19…”

Section: Introductionmentioning

confidence: 99%

Automation of the kidney function prediction and classification through ultrasound-based kidney imaging using deep learning

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Although carcinoma is the most commonly diagnosed lesion in the bladder, particularly when hematuria is also present, there also are numerous conditions that may mimic it. Therefore, an ultrasound examination conducted properly with adequate filling of the bladder is a condition necessary for avoiding diagnostic pitfalls ( 34 , 35 ) . Carcinoma of the urinary bladder is a dangerous neoplasm that requires active surgical treatment and therefore, each doubt in the diagnosis must be resolved in a histopathological analysis.…”

Section: Discussionmentioning

confidence: 99%

Guzy i zmiany guzopodobne imitujące raka pęcherza moczowego w badaniu ultrasonografi cznym

Smereczyński¹,

Szopiński²,

Gołąbek³

et al. 2014

J Ultrason

View full text Add to dashboard Cite

One of the basic abdominal organs that is assessed during transabdominal ultrasound examination for urological reasons is the urinary bladder. The bladder must be filled with urine. This is a prerequisite for a reliable assessment and, at the same time, an acoustic window in examining adjacent structures and organs, for instance the prostate gland. In some cases, doubts occur with respect to the nature of lesions detected. The paper presents anatomic lesions, defects and pathologies which might be erroneously interpreted as tumors of the urinary bladder, i.e. transitional cell carcinoma of the urinary bladder. The following lesions are discussed: 1) anatomic defects (including urachus remnants, ligaments that stabilize the bladder or cyst in the opening of the ureter into the bladder – ureterocele); 2) tumor- like lesions in the lumen of the urinary bladder (such as blood clots, fungus balls, stones or foreign bodies); 3) bladder wall pathologies (i.e. cystitis or endometriosis), focal decidual transformation of stromal cells or inflammatory pseudotumor; 4) lesions impressing on the bladder from the outside (the mesentery of the sigmoid colon, the bowel, pathological lesions in organs adjacent to the urinary bladder, inflammatory infiltration, vasogenic compression of the bladder, pelvic lipomatosis, pathological lesions of the pubic symphysis); 5) postoperative lesions. All these lesions may mimic carcinoma of the urinary bladder in sonography. Bearing this fact in mind is significant in establishing a diagnosis. Due to the malignant character of carcinoma of the urinary bladder and the need for aggressive surgical treatment, a correct diagnosis of this disease is essential for patients, particularly because the lack of adequate treatment and delayed treatment considerably affect prognosis.

show abstract

“…Ultrasound examination of the thyroid gland is the leading imaging modality thereof. Frequently, the evaluation of the thyroid parenchyma and its focal lesions poses challenges, as is the case with other organs too ( 13 – 17 ) . In the case of thyroid ultrasound, the resulting mistakes may be due to a faulty examination technique, or the similarity of the neighboring anatomical structures to the abnormal changes within the gland.…”

Section: Discussionmentioning

confidence: 99%

Błędy i pomyłki w diagnostyce ultrasonografi cznej tarczycy

Dobruch‐Sobczak¹,

Jędrzejowski²,

Jakubowski³

et al. 2014

J Ultrason

View full text Add to dashboard Cite

Ultrasound examination of the thyroid gland permits to evaluate its size, echogenicity, margins, and stroma. An abnormal ultrasound image of the thyroid, accompanied by other diagnostic investigations, facilitates therapeutic decision-making. The ultrasound image of a normal thyroid gland does not change substantially with patient's age. Nevertheless, erroneous impressions in thyroid imaging reports are sometimes encountered. These are due to diagnostic pitfalls which cannot be prevented by either the continuing development of the imaging equipment, or the growing experience and skill of the practitioners. Our article discusses the most common mistakes encountered in US diagnostics of the thyroid, the elimination of which should improve the quality of both the ultrasound examination itself and its interpretation. We have outlined errors resulting from a faulty examination technique, the similarity of the neighboring anatomical structures, and anomalies present in the proximity of the thyroid gland. We have also pointed out the reasons for inaccurate assessment of a thyroid lesion image, such as having no access to clinical data or not taking them into account, as well as faulty qualification for a fine needle aspiration biopsy. We have presented guidelines aimed at limiting the number of misdiagnoses in thyroid diseases, and provided sonograms exemplifying diagnostic mistakes.

show abstract

Błędy w diagnostyce ultrasonograficznej nerek, moczowodów oraz pęcherza moczowego

Cited by 10 publications

References 3 publications

Automation of the kidney function prediction and classification through ultrasound-based kidney imaging using deep learning

Automation of the kidney function prediction and classification through ultrasound-based kidney imaging using deep learning

Guzy i zmiany guzopodobne imitujące raka pęcherza moczowego w badaniu ultrasonografi cznym

Błędy i pomyłki w diagnostyce ultrasonografi cznej tarczycy

Contact Info

Product

Resources

About