BackgroundThe heart-to-mediastinum ratio (HMR) of 123I-metaiodobenzylguanidine (MIBG) showed variations among institutions and needs to be standardized among various scinticamera-collimator combinations.MethodsA total of 225 phantom experiments were performed in 84 institutions to calculate cross-calibration coefficients of HMR. Based on phantom studies, a conversion coefficient for each camera-collimator system was created, including low-energy (LE, n = 125) and a medium-energy (ME, n = 100) collimators. An average conversion coefficient from the most common ME group was used to calculate the standard HMR. In clinical MIBG studies (n = 52) from three institutions, HMRs were standardized from both LE- and ME-type collimators and classified into risk groups of <1.60, 1.60-2.19, and ≥2.20.ResultsThe average conversion coefficients from the individual camera-collimator condition to the mathematically calculated reference HMR ranged from 0.55 to 0.75 for LE groups and from 0.83 to 0.95 for ME groups. The conversion coefficient of 0.88 was used to unify HMRs from all acquisition conditions. Using the standardized HMR, clinical studies (n = 52) showed good agreement between LE and ME types regarding three risk groups (κ = 0.83, P < .0001, complete agreement in 90%, 42% of the patients reclassified into the same risk group).ConclusionBy using the reference HMR and conversion coefficients for the system, HMRs with various conditions can be converted to the standard HMRs in a range of normal to low HMRs.

Conventional CT or MRI has low accuracy in assessing chest wall invasion in patients with peripheral lung cancer. For preoperative evaluation of chest wall invasion by peripheral lung cancer, respiratory dynamic (RD) MRI was carried out in 98 patients in whom conventional CT scan showed that the tumour was abutting the pleural surface, but there was no evidence of definite tumour invasion. We used 1.5-T MR equipment. RD MR images were acquired by snapshot fast field echo sequence (repetition time = 8, echo time = 3, flip angle = 100) and 25 consecutive images were taken while the patient took deep breaths. These images were evaluated in cine mode to assess tumour movement along the chest wall. Sixty-one patients underwent surgical resection of the tumour and RD MR findings were compared with those in pathological specimens. RD MR showed free tumour movement along the chest wall in 34 patients. At pathological examination, the RD MR findings were proved correct in all patients. Pathologically, 20 patients had chest wall invasion and their RD MR was positive (sensitivity 100%). There were seven false-positive results among the 41 patients without chest wall invasion (specificity 82.9%). RD MR may improve the accuracy of conventional CT scan or MRI in the prediction of chest wall invasion of lung cancer, especially in patients in whom the results of conventional CT scan or MRI appear equivocal in the presence of a peripheral mass abutting the chest wall surface without obvious chest wall invasion.

BackgroundArtificial neural network (ANN)-based bone scan index (BSI), a marker of the amount of bone metastasis, has been shown to enhance diagnostic accuracy and reproducibility but is potentially affected by training databases. The aims of this study were to revise the software using a large number of Japanese databases and to validate its diagnostic accuracy compared with the original Swedish training database.MethodsThe BSI was calculated with EXINIbone (EB; EXINI Diagnostics) using the Swedish training database (n = 789). The software using Japanese training databases from a single institution (BONENAVI version 1, BN1, n = 904) and the revised version from nine institutions (version 2, BN2, n = 1,532) were compared. The diagnostic accuracy was validated with another 503 multi-center bone scans including patients with prostate (n = 207), breast (n = 166), and other cancer types. The ANN value (probability of abnormality) and BSI were calculated. Receiver operating characteristic (ROC) and net reclassification improvement (NRI) analyses were performed.ResultsThe ROC analysis based on the ANN value showed significant improvement from EB to BN1 and BN2. In men (n = 296), the area under the curve (AUC) was 0.877 for EB, 0.912 for BN1 (p = not significant (ns) vs. EB) and 0.934 for BN2 (p = 0.007 vs. EB). In women (n = 207), the AUC was 0.831 for EB, 0.910 for BN1 (p = 0.016 vs. EB), and 0.932 for BN2 (p < 0.0001 vs. EB). The optimum sensitivity and specificity based on BN2 was 90% and 84% for men and 93% and 85% for women. In patients with prostate cancer, the AUC was equally high with EB, BN1, and BN2 (0.939, 0.949, and 0.957, p = ns). In patients with breast cancer, the AUC was improved from EB (0.847) to BN1 (0.910, p = ns) and BN2 (0.924, p = 0.039). The NRI using ANN between EB and BN1 was 17.7% (p = 0.0042), and that between EB and BN2 was 29.6% (p < 0.0001). With respect to BSI, the NRI analysis showed downward reclassification with total NRI of 31.9% ( p < 0.0001).ConclusionIn the software for calculating BSI, the multi-institutional database significantly improved identification of bone metastasis compared with the original database, indicating the importance of a sufficient number of training databases including various types of cancers.

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Background: It is important to detect preinvasive bronchial lesions before they become invasive cancer, because detection of early cancer is expected to lead to a cure. Autofluorescence bronchoscopy is a useful device in the detection of preinvasive and cancerous lesions. Recently, a new autofluorescence bronchoscopic system, autofluorescence imaging (AFI) system, has been developed. Objectives: We evaluated the efficacy of AFI in the diagnosis of precancerous and cancerous lesions. Methods: A total of 31 patients underwent both conventional white-light bronchoscopy (WLB) and AFI from January 2002 to September 2004. We evaluated autofluorescence findings using a four-point scale: AFI-I, II, III, and B. The findings in WLB were evaluated on a three-point scale: WLB-I, II, and III. Abnormal areas by WLB and AFI were biopsied for histopathological examinations. Results: A total of 64 lesions were evaluated. When the AFI-III finding was regarded as positive in AFI and WLB-III as positive in WLB, sensitivity for severe dysplasia or worse was 94.7% with AFI and 73.7% with WLB, respectively. Conclusions: AFI is an effective system for the detection of precancerous and cancerous lesions.