scholarly journals AIBx, artificial intelligence model to risk stratify thyroid nodules

2021 ◽  
Author(s):  
Johnson Thomas ◽  
Tracy Haertling
Keyword(s):  
Artificial Intelligence ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Thyroid Nodules ◽  
Classification Systems ◽  
Image Similarity ◽  
Ultrasound Images ◽  
Similarity Model ◽  
Sensitivity Specificity

AbstractBackgroundCurrent classification systems for thyroid nodules are very subjective. Artificial intelligence (AI) algorithms have been used to decrease subjectivity in medical image interpretation. 1 out of 2 women over the age of 50 may have a thyroid nodule and at present the only way to exclude malignancy is through invasive procedures. Hence, there exists a need for noninvasive objective classification of thyroid nodules. Some cancers have benign appearance on ultrasonogram. Hence, we decided to create an image similarity algorithm rather than image classification algorithm.MethodsUltrasound images of thyroid nodules from patients who underwent either biopsy or thyroid surgery from February of 2012 through February of 2017 in our institution were used to create AI models. Nodules were excluded if there was no definitive diagnosis of benignity or malignancy. 482 nodules met the inclusion criteria and all available images from these nodules were used to create the AI models. Later, these AI models were used to test 103 thyroid nodules which underwent biopsy or surgery from March of 2017 through July of 2018.ResultsNegative predictive value of the image similarity model was 93.2%. Sensitivity, specificity, positive predictive value and accuracy of the model was 87.8%, 78.5%, 65.9% and 81.5% respectively.ConclusionWhen compared to published results of ACR TIRADS and ATA classification system, our image similarity model had comparable negative predictive value with better sensitivity specificity and positive predictive value. By using image similarity AI models, we can eliminate subjectivity and decrease the number of unnecessary biopsies. Using image similarity AI model, we were able to create an explainable AI model which increases physician’s confidence in the predictions.

scholarly journals A Control Study on the Value of the Ultrasound Grayscale Ratio for the Differential Diagnosis of Thyroid Micropapillary Carcinoma and Micronodular Goiter in Two Medical Centers

2021 ◽  
Vol 10 ◽  
Author(s):  
Zhijiang Han ◽  
Na Feng ◽  
Yidan Lu ◽  
Mingkui Li ◽  
Peiying Wei ◽  
...  
Keyword(s):  
Differential Diagnosis ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Medical Center ◽  
Threshold Sensitivity ◽  
Ultrasound Images ◽  
Diagnostic Efficacy ◽  
Medical Centers ◽  
Sensitivity Specificity

ObjectiveTo investigate the value of ultrasound gray-scale ratio (UGSR) for the differential diagnosis of papillary thyroid microcarcinoma (PTMC) and micronodular goiter (MNG) in two medical centers.MethodsUltrasound images of 881 PTMCs from 785 patients and 744 MNGs from 687 patients in center A were retrospectively analyzed and compared with 243 PTMCs from 203 patients and 251 MNGs from 198 patients in center B. All cases were confirmed by surgery and histology. The grayscale values of thyroid lesions and surrounding normal tissues were measured, and the UGSR was calculated. The optimal UGSR threshold for identifying PTMCs and MNGs in two medical centers was determined by receiver operating characteristic (ROC) curve, and the area under the curve (AUC), optimal UGSR threshold, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were compared between the two medical centers.ResultsThe UGSR values of PTMCs and MNGs in medical center A were 0.5537 (0.4699, 0.6515) and 0.8708 (0.7616, 1.0123) (Z = -27.691, P = 0), respectively, whereas those in medical center B were 0.5517 (0.4698, 0.6377) and 0.8539 (0.7366, 0.9929) (Z = -16.057, P = 0), respectively. The UGSR of PTMCs and MNGs did not differ significantly between the two medical centers (Z = -0.609, P = 0.543 and Z = -1.394, P = 0.163, respectively). The AUC, optimal UGSR threshold, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the two medical centers were 0.898 vs. 0.918, 0.7214 vs. 0.6911, 0.881 vs. 0.868, 0.817 vs. 0.833, 0.851 vs. 0.834, 0.853 vs. 0.867, and 0.852 vs. 0.850, respectively.ConclusionsUGSR can quantify the echo intensity of PTMCs and MNGs and is therefore valuable for the differential diagnosis of the two diseases. The diagnostic efficacy was consistent between the two medical centers. This method should be widely promoted and applied.

Comparative Analysis of Diagnostic Value for Shear Wave Elastography and Real-Time Elastographic Imaging for Thyroid Nodules

2019 ◽  
Vol 9 (2) ◽  
pp. 334-338
Author(s):  
Qing Yang ◽  
Wenhong Zhou ◽  
Jiyu Li ◽  
Guojun Wu ◽  
Feng Ding ◽  
...  
Keyword(s):  
Differential Diagnosis ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Shear Wave ◽  
Predictive Value ◽  
Thyroid Nodules ◽  
Shear Wave Elastography ◽  
Roc Curves ◽  
Diagnostic Value ◽  
Sensitivity Specificity

Objective: To compare the diagnostic value of shear wave elastography (SWE) and real-time elastography (RTE) in the diagnosis of benign and malignant thyroid nodules. Methods: A total of 34 patients who ever received thyroidectomy in our hospital from January 2016 to January 2018 were identified. Meanwhile, all the patients received SWE and RTE before surgery, and all the diagnoses were confirmed by pathological examinations. With respect to SWE technique, the Subject Operating Characteristics (ROC) curves were drawn, in order to obtain the optimal threshold and then make differential diagnoses of benign and malignant thyroid nodules. In terms of RTE, the Rago 5 scoring method was utilized to make differential diagnoses of benign and malignant thyroid nodules. Besides, the pathological examinations after surgery could be considered as the golden standard. At last, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of SWE and RTE were calculated, respectively. Results: A total of 51 thyroid nodules were identified, and 41 nodules were benign, 10 nodules were malignant. On the basis of ROC curves, with respect to SWE, the best threshold for differential diagnosis of benign and malignant thyroid nodules is 38.3 kPa. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of SWE were 72.7% (8/11), 85% (34/40), 82.4% (42/51), 68.4% (13/19), and 87.5% (35/40), respectively. And the diagnostic indicators of RTE were 81.8% (9/11), 87.5% (35/40), 84.3% (43/51), 73.7% (14/19), and 90.0% (36/40). The sensitivity of quasi-static elastography in differential diagnosis of benign and malignant thyroid nodules with diameter ≤1 cm was 87.5% (7/8), and the sensitivity of SWE was 50.0% (5/10). In addition, the accuracy of SWE in differential diagnosis of benign and malignant thyroid nodules with diameter ≥3 cm was 100% (6/6), and the accuracy of RTE for this kind of thyroid nodules was 66.7% (4/6). Conclusion: Both SWE and RTE technology have good application value in differential diagnosis of benign and malignant thyroid nodules. But, SWE is preferable when making diagnosis of benign and malignant thyroid nodules with diameter ≥3 cm, and RTE was superior in detecting benign and malignant thyroid nodules with diameter ≤1 cm.

scholarly journals Qualitative analysis of contrast-enhanced ultrasound in the diagnosis of small, TR3–5 benign and malignant thyroid nodules measuring ≤1 cm

2020 ◽  
Vol 93 (1111) ◽  
pp. 20190923
Author(s):  
Xin Li ◽  
Feng Gao ◽  
Fan Li ◽  
Xiao-xia Han ◽  
Si-hui Shao ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Qualitative Analysis ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Diagnostic Performance ◽  
Thyroid Nodules ◽  
Area Under The Curve ◽  
Contrast Enhanced Ultrasound ◽  
Contrast Enhanced ◽  
Sensitivity Specificity

Objective: To evaluate the performance of contrast-enhanced ultrasound in the diagnosis of small, solid, TR3–5 benign and malignant thyroid nodules (≤1 cm). Methods: From January 2016 to March 2018, 185 thyroid nodules from 154 patients who underwent contrast enhanced ultrasound (CEUS) and fine-needle aspiration or thyroidectomy in Shanghai General Hospital were included. The χ2 test was used to compare the CEUS characteristics of benign and malignant thyroid nodules, and the CEUS features of malignant nodules assigned scores. The total score of the CEUS features and the scores of the above nodules were evaluated according to the latest 2017 version of the Thyroid Imaging Reporting and Data System (TI-RADS). The diagnostic performance of the two were compared based on the receiver operating characteristic curves generated for benign and malignant thyroid nodules. Results: The degree, enhancement patterns, boundary, shape, and homogeneity of enhancement in thyroid small solid nodules were significantly different (p＜0.05). No significant differences were seen between benign and malignant thyroid nodules regarding completeness of enhancement and size of enhanced lesions (p＞0.05). The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the TI-RADS classification TR5 in diagnosis of malignant nodules were 90.10%, 55.95%, 74.59%, 72.22%, and 82.46%, respectively (area under the curve [AUC]=0.738; 95% confidence interval[CI], 0.663–0.813). The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the total score of CEUS qualitative analysis indicators were 86.13%, 89.29%, 87.57%, 90.63%, and 84.27% respectively (AUC = 0.916; 95% CI, 0.871–0.961). Conclusion: CEUS qualitative analysis is superior to TI-RADS in evaluating the diagnostic performance of small, solid thyroid nodules. Qualitative analysis of CEUS has a significantly higher specificity for diagnosis of malignant thyroid nodules than TI-RADS. Advances in knowledge: The 2017 version of TI-RADS has recently suggested the malignant stratification of thyroid nodules by ultrasound. In this paper we applied this system and CEUS to evaluate 185 nodules and compare the results with pathological findings to access the diagnostic performance.

scholarly journals Foundational Statistical Principles in Medical Research: Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value

Medicina ◽  
2021 ◽  
Vol 57 (5) ◽  
pp. 503
Author(s):  
Thomas F. Monaghan ◽  
Syed N. Rahman ◽  
Christina W. Agudelo ◽  
Alan J. Wein ◽  
Jason M. Lazar ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Medical Literature ◽  
Disease Prevalence ◽  
Positive Test Result ◽  
Predictive Values ◽  
Sensitivity Specificity ◽  
Test Result ◽  
Test Probability

Sensitivity, which denotes the proportion of subjects correctly given a positive assignment out of all subjects who are actually positive for the outcome, indicates how well a test can classify subjects who truly have the outcome of interest. Specificity, which denotes the proportion of subjects correctly given a negative assignment out of all subjects who are actually negative for the outcome, indicates how well a test can classify subjects who truly do not have the outcome of interest. Positive predictive value reflects the proportion of subjects with a positive test result who truly have the outcome of interest. Negative predictive value reflects the proportion of subjects with a negative test result who truly do not have the outcome of interest. Sensitivity and specificity are inversely related, wherein one increases as the other decreases, but are generally considered stable for a given test, whereas positive and negative predictive values do inherently vary with pre-test probability (e.g., changes in population disease prevalence). This article will further detail the concepts of sensitivity, specificity, and predictive values using a recent real-world example from the medical literature.

Diagnostic accuracy of monofilament test to detect diabetic neuropathy

2021 ◽  
Vol 10 (1) ◽  
pp. 20-25
Author(s):  
Sujan Shrestha ◽  
Mamen Prasad Gorhaly ◽  
Manil Ratna Bajracharya
Keyword(s):  
Peripheral Neuropathy ◽  
Positive Predictive Value ◽  
Diagnostic Accuracy ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Diabetic Peripheral Neuropathy ◽  
Perception Threshold ◽  
Sensitivity Specificity ◽  
Vibration Perception ◽  
Monofilament Test

Background Diabetic peripheral neuropathy (DPN) is a significant independent risk factor for diabetic foot, and an effective screening instrument is required to diagnose DPN early to prevent future ulceration and amputation. This study aims to determine the diagnostic accuracy of monofilament test to detect diabetic peripheral neuropathy. Methods This cross-sectional study was conducted in National Academy of Medical Sciences, Bir hospital, Mahabouddha, Kathmandu from February 2016 to January 2017. A total of 96 diabetic patients attending inpatient and outpatient Department were selected. Diabetic peripheral neuropathy was assessed by measurement of loss of protective sensation (LOPS) by monofilament test and compared with vibration perception threshold by standard biothesiometer. The sensitivity, specificity, positive predictive value and negative predictive value of monofilament test were calculated. Results The prevalence of diabetic peripheral neuropathy was 26%. The sensitivity, specificity, positive predictive value and negative predictive value of monofilament test were found to be 92.0%, 95.8%, 88.5% and 97.1% respectively. There was strong association between LOPS by monofilament and vibration perception threshold by biothesiometer. Conclusion This study showed a strong diagnostic accuracy of monofilament test to detect DPN when compared with biothesiometer. As monofilament test is a cheap, easily available, and portable, it can be used in the periphery where biothesiometer is not available.  

DIAGNOSTIC ACCURACY OF GRAY SCALE ULTRASONOGRAPHY VERSUS COLOR DOPPLER IN SUSPECTED CASES OF ACUTE APPENDICITIS

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Tahir Iqbal ◽  
Muhammad Usman Shahid ◽  
Ishfaq Ahmad Shad ◽  
Shahzad Karim Bhatti ◽  
Syed Amir Gilani ◽  
...  
Keyword(s):  
Acute Appendicitis ◽  
Positive Predictive Value ◽  
Diagnostic Accuracy ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Color Doppler ◽  
Diagnostic Tools ◽  
Gray Scale ◽  
Versus Color ◽  
Sensitivity Specificity

ABSTRACT: BACKGROUND: A common surgical emergency is acute appendicitis. Various diagnostic tools are available to diagnosis acute appendicitis. Radiological investigations play an important role in making accurate and early diagnosis and thus preventing morbidity associated with the disease. OBJECTIVE: To determine the diagnostic accuracy of gray scale ultrasonography versus color Doppler in suspected cases of acute appendicitis. MATERIALS AND METHODS: The study was carried in the department of Radiology of Mayo Hospital, Lahore. A total of 75 patients were enrolled of age 18-40 years, both genders who were suspected cases of acute appendicitis. All patients underwent baseline investigations along with gray scale ultrasonography and color Doppler. All patients were subjected to surgery to confirm the diagnosis and findings were subjected to statistical analysis. RESULTS: The mean age of the patients was 23.25 ±10.55 and mean transverse diameter of appendix was 8.37 ±3.39. There were 62.7% males and 37.3%females. Findings of gray scale ultrasonography and color Doppler were then correlated with surgical findings to calculate the diagnostic accuracy of these modalities. The results revealed that gray scale ultrasonography sensitivity, specificity, positive predictive value, negative predictive value and accuracy was 92.7%, 94.32%, 95%, 91.4% and 93.3% respectively, whereas color Doppler had sensitivity, specificity, positive predictive value, negative predictive value and accuracy of 97.7%, 93.9%, 95.3%, 97% and 96% respectively. Diagnostic accuracy of both modalities together was 98.6%. CONCLUSION: Color Doppler has better diagnostic accuracy than gray scale ultrasonography for diagnosis of acute appendicitis and the combination of both modalities yields diagnostic accuracy that is similar to gold standard.

scholarly journals Comparison of RMI 3 and RMI 4 in pre-operative evaluation of ovarian masses

2019 ◽  
Vol 8 (9) ◽  
pp. 3602
Author(s):  
Badugu Rao Bahadur ◽  
Gangadhara Rao Koneru ◽  
Prabha Devi Kodey ◽  
Jyothi Melam
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Malignant Tumors ◽  
Clinical Approach ◽  
Ovarian Mass ◽  
Medical College ◽  
Operative Evaluation ◽  
Sensitivity Specificity ◽  
Final Confirmation

Background: To differentiate ovarian mass as benign or malignant could change clinical approach. Finding a screening and diagnostic method for ovarian cancer is challenging due to high mortality and insidious symptoms. Risk malignancy index (RMI) has the advantage of rapid and exact triage of patients with ovarian mass.Methods: Prospective study carried for 2 years at NRI Medical College and General Hospital, Chinakakani, Mangalagiri, Andhra Pradesh, India. 79 patients with ovarian mass were investigated and risk malignancy index (RMI-3 and RMI-4) calculated. Final confirmation was done based on histopathological report. Sensitivity, specificity, positive predictive value and negative predictive value were calculated for RMI 3 and RMI 4 taking histopathology as control and comparison was done.Results: (n=79); 50 (63.29%) cases were benign and 29 (36.70%) were malignant based on histopathology. RMI 4 is more sensitive (68.96%) than RMI 3 (62.06%), but RMI 3 is more specific (94%) than RMI 4 (92%).The positive predictive value of RMI-3 and RMI-4 were 85.71%  and 83.33% respectively. The negative predictive value for RMI-4 and RMI-3 were 83.63% and 81.03% respectively.Conclusions: With increasing age, chance of malignancy increases. RMI 4 was more sensitive than RMI-3, however less specific than RMI 3 in differentiating benign and malignant tumors. The positive predictive value is slightly more for RMI 3, than RMI 4. Negative predictive value is slightly more for RMI 4, than RMI 3. 

Συγκριτική μελέτη της μορφομετρίας κατά τον κλασικό ακτινολογικό έλεγχο (MRX) και της μορφομετρίας με χρήση απορροφησιομετρίας (VFA) στον καθορισμό σπονδυλικών παραμορφώσεων σε οστεοπορωτικούς ασθενείς μετά από κυφοπλαστική

2017 ◽  
Author(s):  
Ευστάθιος Δράμπαλος
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Correlation Coefficient ◽  
Intraclass Correlation Coefficient ◽  
Predictive Value ◽  
Intraclass Correlation ◽  
Sensitivity Specificity

Σκοπός: H εφαρμογή για πρώτη φορά διεθνώς της μορφομετρίας της σπονδυλικής στήλης με χρήση απορροφησιομετρίας (VFA) σε ασθενείς με κυφοπλαστική. Αναλύονται τα πλεονεκτήματα και μειονεκτήματα της μεθόδου, ελέγχεται η αξιοπιστία της και συγκρίνεται με την μορφομετρία κατά τον κλασσικό ακτινολογικό έλεγχο (ΜRΧ) στην εκτίμηση των σπονδυλικών παραμορφώσεων στους συγκεκριμένους ασθενείς.Υλικά και Μέθοδος: Πραγματοποιήθηκαν μετρήσεις σε 42 ασθενείς με κυφοπλαστική λόγω οστεοπορωτικών σπονδυλικών καταγμάτων και αναλύθηκαν οι σπόνδυλοι από τον T4 μέχρι τον L4 με την VFA και την MRX. Μετρήθηκαν το πρόσθιο (ha), μέσο (hm) και οπίσθιο (hp) ύψος του σπονδυλικού σώματος και προσδιορίσθηκαν οι λόγοι ha/hp και hm/hp. Αναλύθηκαν για την VFA η συμφωνία αποτελεσμάτων του ίδιου παρατηρητή (IOA) και η συμφωνία αποτελεσμάτων μεταξύ ανεξάρτητων παρατηρητών (INA) για τους λόγους ha/hp και hm/hp καθώς και για την μέθοδο Genant σε επίπεδο σπονδύλου, ‘περιοχής της σπονδυλικής στήλης (θωρακική/ΘΜΣΣ ή οσφυϊκή/ΟΜΣΣ), σε επίπεδο ‘γειτονικών προς την κυφοπλαστική σπονδύλων’, και σε επίπεδο ‘σπονδύλων με κυφοπλαστική’. Σε κάθε επίπεδο χρησιμοποιήθηκε η μέση τιμή ha/hp και hm/hp. Στη συνέχεια, αναλύσαμε την συμφωνία μεταξύ VFA και MRX στον καθορισμό των λόγων ha/hp και hm/hp καθώς και μετά την διχοτόμηση των λόγων ha/hp περί της τιμής όριο που συνήθως χρησιμοποιείται για τον καθορισμό ενός κατάγματος. Αποτελέσματα: Οι IOA και INA για τους λόγους ha/hp και hm/hp στην VFA ήταν ‘σχεδόν τέλεια’ σε όλα τα επίπεδα (ICC 0.94-0.98). Η εφαρμογή της μεθόδου Genant κατά την VFA ανέδειξε επίσης ‘σχεδόν τέλεια’ INA (ICC=0.833). Η ανάλυση σε επίπεδο σπονδύλου έδειξε ‘σχεδόν τέλεια’ συμφωνία μεταξύ VFA και MRX για τον λόγο ha/hp [intraclass correlation coefficient, ICC=0.85], και ‘ισχυρή συμφωνία’ για τον λόγο hm/hp (ICC=0.78). Για τον λόγο ha/hp η συμφωνία ήταν ‘σχεδόν τέλεια’ τόσο στην ΘΜΣΣ (ICC=0.82) όσο και στην ΟΜΣΣ (ICC=0.87), ενώ για τον λόγο hm/hp η συμφωνία ήταν ‘ισχυρή’ στην ΘΜΣΣ (ICC=0.75) και ‘σχεδόν τέλεια’ στην ΟΜΣΣ (ICC=0.80). Η συμφωνία ήταν εξίσου ‘σχεδόν τέλεια’ σε επίπεδο ‘σπονδύλων με κυφοπλαστική’ (ICC=0.83) όσο και σε επίπεδο ‘γειτονικών προς την κυφοπλαστική σπονδύλων’ (ICC=0.80) για τον λόγο ha/hp. Όταν οι λόγοι ha/hp μετατράπηκαν σε κατάγματα (ναι ή όχι κάταγμα) χρησιμοποιώντας διαφορετικές τιμές κατώφλι για την διάγνωση κατάγματος (λόγοι ha/hp 0.75, 0.80 και 0.85) η συμφωνία μεταξύ των μεθόδων ήταν λιγότερο καλή, από μέτρια έως ουσιώδης (κ 0.52-0.63 στην ΟΜΣΣ και 0.53-0.66 στην ΘΜΣΣ). Χρησιμοποιώντας την κατάταξη Genant οι διαφορές στην ταξινόμηση των σπονδύλων ήταν περισσότερο προς την κατεύθυνση της MRX με 32 αναγνωρισμένα κατάγματα μόνο από την MRX και μόνο 5 μόνο από την VFA. Στη μελέτη αυτή, με επιπολασμό σφηνοειδών σπονδυλικών καταγμάτων 9.3%, οι δείκτες ακρίβειας sensitivity, specificity, positive predictive value (PPV) και negative predictive value (NPV) υπολογίστηκαν σε 0.522, 0.97, 0.87 και 0.92 αντίστοιχα. Συμπεράσματα: Η εφαρμογή της VFA σε ασθενείς με κυφοπλαστική έχει υψηλή επαναληψιμότητα και αναπαραγωγιμότητα. Η συμφωνία μεταξύ VFA και MRX στην εκτίμηση των λόγων ha/hp και hm/hm ήταν από ‘ισχυρή’ έως ‘σχεδόν τέλεια’ ανάλογα με το επίπεδο εξέτασης. Η συμφωνία στην αναγνώριση των σπονδυλικών καταγμάτων ήταν μέτρια. Οι διαφορές ήταν περισσότερο προς την κατεύθυνση της MRX. Η υψηλή τιμή του δείκτη NPV της VFA στους ασθενείς με κυφοπλαστική, δείχνει ότι η μέθοδος θα μπορούσε να χρησιμοποιηθεί για τον εντοπισμό αυτών που χρήζουν περαιτέρω ακτινολογικού ελέγχου.

Diagnostic Value of WB-DWI Versus 18 F-FDG PET/CT for the Detection of Multiple Myeloma

2020 ◽  
Author(s):  
Bei Zhang ◽  
Li Zhang ◽  
Bingyang Bian ◽  
Fang Lin ◽  
Zining Zhu ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
False Positive ◽  
Fdg Pet ◽  
Pet Ct ◽  
Adc Values ◽  
Sensitivity Specificity ◽  
Fdg Pet Ct

Abstract BACKGROUND Whole body diffusion weighted imaging (WB-DWI) is commonly used for the detection of multiple myeloma (MM). Comparative data on the efficiency of WB-DWI compared with 18 F positron emission tomography computed tomography ( 18 F-FDG PET/CT) to detect MM are lacking. METHODS This was a retrospective, single-center study of twenty-two patients with MM enrolled from January 2019 to December 2019. All patients underwent WB-DWI and 18 F-FDG PET/CT. Pathological and clinical manifestations as well as radiologic follow-up were used for diagnosis. The overall accuracy, sensitivity, specificity, positive predictive value and negative predictive value of both methods were compared. The appearance diffusion coefficient (ADC) values of MM lesions and false-positive lesions were estimated. RESULTS A total of 214 MM bone lesions were evaluated. WB-DWI showed a higher overall accuracy than PET/CT (75.7% and 55.6%, respectively; < 0.05). However, for sensitivity, specificity, positive predictive value and negative predictive value, there were no significant differences for WB-DWI vs PET/CT (99.3% and 83.9%, 64.9% and 94.8%, 63.6% and 54.2%, 98.1% and 65.3%, respectively). The ADC value for MM lesions was significantly lower than that for false-positive lesions (p < 0.001). Receiver operating curve (ROC) curve analysis showed that the AUC was 0.846, and when the cut-off value was 0.745×10 -3 mm 2 /s, the sensitivity and specificity were 86.0% and 82.4%, respectively, which distinguished MM lesions from non-MM lesions. CONCLUSION WB-DWI may be a useful tool for the diagnosis of MM bone disease due to to higher overall accuracy and measurements of ADC values compared with PET/CT.

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